3D Analysis of Human Movement, Sport, and Health Promotion

Edited by Luca Petrigna

mdpi.com/journal/jfmk

## **3D Analysis of Human Movement, Sport, and Health Promotion**

## **3D Analysis of Human Movement, Sport, and Health Promotion**

Editor

**Luca Petrigna**

Basel • Beijing • Wuhan • Barcelona • Belgrade • Novi Sad • Cluj • Manchester

*Editor* Luca Petrigna Scienze Biomediche e Biotecnologiche University of Catania Catania Italy

*Editorial Office* MDPI St. Alban-Anlage 66 4052 Basel, Switzerland

This is a reprint of articles from the Special Issue published online in the open access journal *Journal of Functional Morphology and Kinesiology* (ISSN 2411-5142) (available at: https://www.mdpi. com/journal/jfmk/special issues/3D Human Movement).

For citation purposes, cite each article independently as indicated on the article page online and as indicated below:

Lastname, A.A.; Lastname, B.B. Article Title. *Journal Name* **Year**, *Volume Number*, Page Range.

**ISBN 978-3-0365-9741-6 (Hbk) ISBN 978-3-0365-9740-9 (PDF) doi.org/10.3390/books978-3-0365-9740-9**

© 2023 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) license.

## **Contents**

Inertial Sensor

Reprinted from: *J. Funct. Morphol. Kinesiol.* **2023**, *8*, 22, doi:10.3390/jfmk8010022 .......... **119**

#### **Luca Petrigna and Giuseppe Musumeci**

The Metaverse: A New Challenge for the Healthcare System: A Scoping Review Reprinted from: *J. Funct. Morphol. Kinesiol.* **2022**, *7*, 63, doi:10.3390/jfmk7030063 .......... **137**

### *Editorial* **3D Analysis of Human Movement, Sport, and Health Promotion**

**Luca Petrigna \* and Giuseppe Musumeci**

Department of Biomedical and Biotechnological Sciences, Section of Anatomy, Histology and Movement Science, School of Medicine, University of Catania, Via S. Sofia 97, 95123 Catania, Italy<EMAIL_ADDRESS>**\*** Correspondence<EMAIL_ADDRESS>
This Special Issue, "3D Analysis of Human Movement, Sport, and Health Promotion", aimed to collect studies that assessed motor functions and alterations. The idea was to focus attention on objective and quantitative evaluation methods in both sport and, primarily, health promotion. According to the World Health Organization, health is a "complete physical, mental and social well-being, and not merely the absence of disease or infirmity" [1]. It is consequently important to think about well-designed health interventions in this way, to reduce the risks of correlated health status problems and reduce costs in healthcare systems [2,3]. On the one hand, the education of the population is fundamental for better knowledge on healthy habits; on the other hand, it is important to perform regular screening to evaluate health status [4,5].

It is possible to evaluate health status with laboratory tests (which usually present higher reliability and validity) and field tests (which are cheaper and easier to administer) [6]. Usually, field tests are more ecologically valid, making them a good solution for population-based studies [7]. Both solutions have to be investigated to achieve high-quality evaluations, as well as tests that can be performed involving more people in less time. One aspect that laboratory and field evaluations should have in common is the scientific quality of the protocol. Recently, the concept of the standard operating procedure in physical fitness evaluation has been proposed [8]. The idea of this concept is a detailed step-by-step description of the protocol to increase the quality of the research, allow the repetition of the protocol, and compare the data [8]. It is a concept adopted in other disciplines such as in the fields of medicine and engineering, where errors are not allowed [8]; consequently, it should also be suitable for the field of health evaluation.

The importance of evaluation with three-dimensional (3D) analysis is that it allows a vision of the human body on the three planes to be obtained, increasing the possibility of better understanding all aspects that could bring functional alterations [9]. The idea behind 3D testing is that kinematic analysis, especially if performed in 3D, helps in the evaluation of the quality of movements [10]. This is extremely helpful in the rehabilitation setting, as the study of the human kinematics for movement quantification is fundamental for evaluating improvements in patients, such as after a stroke [11,12], in scoliosis evaluation [13], or for digital postural analysis [14].

The articles included in this Special Issue address the 3D evaluation of human movement in different populations, the practical application of postural analysis, and possible future directions of research in this field. Different methods could be adopted in 3D evaluation, such as multicamera systems, machine learning approaches, or specific software for computers and smartphones. One of the studies included in this Special Issue adopted four infrared 3D cameras using the SMART Integrated System [15]. Russo and colleagues, in their article [15], evaluated the impact of Nordic walking pole length on healthy participants. The authors of [15] adopted a technique that is considered the gold standard for dynamic evaluation, but the price of the instrument limits its use. An alternative method detected in the included studies in the present Special Issue for human 3D evaluation is photogrammetry. It is a radiation-free, easy, inexpensive, and rapid tool that can help in pos-

**Citation:** Petrigna, L.; Musumeci, G. 3D Analysis of Human Movement, Sport, and Health Promotion. *J. Funct. Morphol. Kinesiol.* **2023**, *8*, 157. https://doi.org/10.3390/ jfmk8040157

Received: 23 October 2023 Accepted: 3 November 2023 Published: 7 November 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

1

tural screening and repetitive controls. It was adopted in the study by Belli and colleagues, who suggest that this instrument works especially well in bending evaluation [16].

The above systems are not always accessible for all clinicians due to their cost and the skills required to use them, suggesting the use of more economical techniques such as the calculation of body angles from photographs or the use of goniometry may be more attainable [17]. Following this principle, the study in [18] adopted software that evaluated human posture after the positioning of markers on specific anatomical landmarks. The authors in [18] analyzed body posture accurately and the software adopted was Dartfish ProSuite 6 (Dartfigh, Fribourg, Switzerland). Another study [19] adopted a mobile app named Apecs (Apecs-AI Posture Evaluation and Correction System®. New Body Technologies SAS, Grenoble, France). This application demonstrated good reproducibility with trunk inclination, although axillae alignment was unreliable in all the planes. This evaluation is cheap, easy to adopt (the application indicates the anatomical points on which to place the markers), and feasible; consequently, it could be an alternative to more expensive devices.

Software recording with 3D systems sometimes requires the use of technology to analyze data. In the life sciences, there is an ever-increasing interest in machine learning [20]. This technology is based on deep learning and has multiple field applications; one that could be of interest for movement analysis is the identification of objects in images [21]. Machine learning tools are useful for analyzing 3D movement kinematics and they can help distinguish healthy from pathological behaviors [10]. Deep learning could be adapted to analyze behaviors with standardized methods proposed in the literature [22]. In one of the studies included in this Special Issue, a machine learning approach was adopted in the evaluation of climbing holding time [23]. The concept of the study could also be adopted in other studies using 3D data.

All the above aspects should be related with their practical applications. Using 3D analysis is not only useful for researchers but also for kinesiologists. Three-dimensional evaluation and analysis could be useful in a studio, in a sports setting, or in a rehabilitation setting, but could also be performed remotely. Indeed, new technologies, if integrated with proper applications and supported by a good internet connection, could allow for the monitoring of treatment, as was demonstrated in another study included in this Special Issue [18]. As a review suggests [24], everything proposed above could be moved to the metaverse, a place where these new technologies and evaluation techniques can be adopted to reach people everywhere and at every time.

A practical application proposed in another study is the evaluation of hand-standing from a posturographic point of view [25]. It is not a natural human position, but different sports and disciplines require this specific and not-so-often-studied posture. Consequently, the study provides feedback for future research on this topic. Future research could also consider the evaluation of the human posture by integrating the above-presented tests with other techniques such as a termocamera [14] or in dual-task conditions [26]. In this way, it is possible to increase the quality and accuracy of the evaluation.

This Special Issue seeks to provide an overview of instruments, research ideas, and also future applications of 3D analysis technology. In the near future, it will be interesting to make some of the above-presented instruments the gold standard or valid research tools that could complement much more expensive and complex instruments. Furthermore, researchers should start to think about adopting new markerless technologies or techniques to make research as objective, precise, and cheap as possible.

In conclusion, this editorial aimed to present an overview of the Special Issue "3D Analysis of Human Movement, Sport, and Health Promotion" and provide feedback for future studies on the same or similar topics.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

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## *Article* **Postural Evaluation in Young Healthy Adults through a Digital and Reproducible Method**

**Bruno Trovato 1, Federico Roggio 1,2, Martina Sortino 1, Marta Zanghì 1, Luca Petrigna 1,\*, Rosario Giuffrida 3 and Giuseppe Musumeci 1,4,5**

**Abstract:** Different tools for the assessment of posture exist, from the simplest and cheap plumb line to complex, expensive, 3D-marker-based systems. The aim of this study is to present digital postural normative data of young adults collected through a mobile app to expand the possibilities of digital postural evaluation. A sample of 100 healthy volunteers, 50 males and 50 females, was analyzed with the mobile app Apecs-AI Posture Evaluation and Correction System® (Apecs). The Student's *t*-test evaluated differences between gender to highlight if the digital posture evaluation may differ between groups. A significant difference was present in the anterior coronal plane for axillary alignment (*p* = 0.04), trunk inclination (*p* = 0.03), and knee alignment (*p* = 0.01). Head inclination (*p* = 0.04), tibia shift (*p* = 0.01), and foot angle (*p* < 0.001) presented significant differences in the sagittal plane, while there were no significant differences in the posterior coronal plane. The intraclass correlation coefficient (ICC) was considered to evaluate reproducibility. Thirteen parameters out of twenty-two provided an ICC > 0.90, three provided an ICC > 0.60, and six variables did not meet the cut-off criteria. The results highlight that digital posture analysis of healthy individuals may present slight differences related to gender. Additionally, the mobile app showed good reproducibility according to ICC. Digital postural assessment with Apecs could represent a quick method for preventing screening in the general population. Therefore, clinicians should consider this app's worth as an auxiliary posture evaluation tool.

**Keywords:** posture; reproducibility; mobile app; movement; kinesiology

#### **1. Introduction**

Posture is defined as the position acquired by the human body in various situations, opposed to the force of gravity and adapting to different environments [1]. Moreover, posture is essential for maintaining postural balance both in static and dynamic conditions. Remaining in a non-ergonomic position for an extended period can predispose people to manifest musculoskeletal pain [2]; thus, assuming good postures is considered necessary for general health at both a musculoskeletal and psychological level [3]. Nowadays, the evaluation of human posture is performed consistently in healthcare clinics and fitness centers, considering that postural misalignments can cause individuals to manifest headaches, lower back pain, neck pain, neurological pathologies, and a reduction in overall psychological well-being [4]. Currently, the literature does not provide any gold standard procedure for postural assessment. The types of exams employed can vary from a visual evaluation

**Citation:** Trovato, B.; Roggio, F.; Sortino, M.; Zanghì, M.; Petrigna, L.; Giuffrida, R.; Musumeci, G. Postural Evaluation in Young Healthy Adults through a Digital and Reproducible Method. *J. Funct. Morphol. Kinesiol.* **2022**, *7*, 98. https://doi.org/ 10.3390/jfmk7040098

Academic Editor: Vítor P. Lopes

Received: 12 October 2022 Accepted: 27 October 2022 Published: 28 October 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

5

with goniometers and plumb lines to motion capture systems, such as Vicon, for dynamic evaluation and 3D camera infrared systems, such as rasterstereography, for static evaluation [5]. Regarding the feasibility of using a markerless system to assess human posture, rasterstereography is a system that generates a 3D model of the spine by calculating specific deformities and analyzing the convexity and concavity of the spine [6]. It is commonly used to investigate the presence of scoliosis and is considered reliable for the assessment of parameters such as pelvic obliquity, thoracic kyphosis, and lumbar lordosis angles [7,8]. However, this system has a high cost, and it is difficult to implement in postural screening for the general population. Other valid tools such as inertial measurement units (e.g., accelerometers, magneto inertial units) are also employed in the field of postural evaluation for the assessment of the thoracic kyphosis and the lumbar lordosis angles [9] and also for gait and balance assessment [10].

All the available methods for evaluating posture present some biases or disadvantages. The visual evaluation with a plumb line is cheap, but it requires specialized personnel, is prone to bias, and lacks scientific validation [11]. The use of goniometers is feasible for the measurement of the range of motion and angles of different joints with good reliability [12]; it has a low cost and is easy to perform, although it presents some methodological issues when assessing postural deviations [13], and it is only considered useful for one postural variable examination at the time [5]. Marker-based advanced technologies that can provide highly accurate data on joint angles and translations are potentially available for clinicians; however, these evaluation systems are too expensive for the average clinic, and often they are employed for research purposes only [14].

In this heterogeneous scenario regarding the available postural evaluation tools, the advancement in image-based technologies will come in handy for clinicians and researchers who want to find a postural assessment system with good reproducibility and an affordable cost. Tablet and phone apps for postural evaluation can fill this gap, with different postural apps demonstrating promising results in the evaluation of the frontal plane [15], standing posture [13], angulation variables [14], and head shift in sagittal and frontal planes [4]; however, the literature is insufficient to confirm the quality of these methods. Considering that the complete visual evaluation of body posture with goniometers and a plumb line can be long and not free from biases, and taking into account the high costs of 3D systems, the use of a mobile app could represent a quick, safe, and accurate method for researchers and clinicians to quantitatively evaluate general posture. Moreover, laboratory tests are often more expensive than field-based ones [16], and adopting a mobile, affordable tool for postural assessment could benefit the primary prevention of musculoskeletal disorders of the spine. The aim of this study is to present normative data about digital posture evaluation collected through a mobile app Apecs and, moreover, to evaluate the reproducibility.

#### **2. Materials and Methods**

#### *2.1. Participants*

We recruited and evaluated a sample of 100 healthy volunteers, 50 males and 50 females, with a mean age of 23.4 (standard deviation (SD) ± 6.2) years. Prior to testing, all participants were informed about the study procedure, risks, and benefits and provided written, informed consent to participate in the study and for us to use their data. The study followed the Helsinki Declaration principles and was approved by the University of Catania (protocol no.: CRAM-017-2020, 16 March 2020).

Exclusion criteria comprised: past or current major musculoskeletal injuries, spine pathology, and neurological pathologies. All the participants selected after the oral interview underwent a static postural evaluation provided by expert clinician (experience of 7 years) to confirm their eligibility for the study.

#### *2.2. Study Design*

The evaluation took 30 min per participant at the University Laboratories and consisted of evaluating their health status and history of previous conditions that could meet the

exclusion criteria. After the screening process, participants were always asked to attend the laboratory at the same time (between 10:00 a.m. and 12:00 p.m.). The postural evaluation was performed by three different operators with similar experience in postural analysis (3 to 4 years of experience). The mobile app Apecs-AI Posture Evaluation and Correction System® (New Body Technologies SAS, Grenoble, France) (Apecs app) was used to acquire the images of the participants in standing position. The participants were asked to dress in minimal clothing, shorts for men and shorts and bras for women, to minimize biases relating to wrong landmark positioning during the postural analysis; for the same reason, markers were placed by expert clinicians on the body of the participants in correspondence to the app's predetermined landmarks. Four pictures were captured, one for the anterior coronal plane, one for the posterior coronal plane, and two for the sagittal plane (left and right). Participants were instructed to place their feet at the same width as the shoulders (Figure 1).

**Figure 1.** Landmarks positioning.

To avoid any wrong camera leveling during the image acquisition, the app's interface shows a target that becomes green when the camera is leveled. After the picture is acquired, the app immediately steers the user to crop the image at the individual's head and feet to minimize inconsistency in the proportion of different images. The Apecs app uses standardized digital landmarks and anatomical angles from one to four pictures, depending on the number of variables of interest to the investigation. The app calculates 24 postural variables from the predetermined anatomical markers in the three planes of the space examined. Figure 2 shows the points evaluated in the anterior coronal plane (a), the sagittal plane (b), and the posterior coronal plane (c).

**Figure 2.** Evaluation of the anterior coronal plane (**A**); of the sagittal plane (**B**); of the posterior coronal plane (**C**).

After the cropping phase, the app drives the user to position the digital markers, fostering this process with examples of the proper positioning with images. Table 1 shows all the anatomical landmarks taken into consideration by the app for calculating the postural variables.

**Table 1.** Anatomic landmarks and postural variables studied with Apecs.

#### *2.3. Statistical Analysis*

Data analysis comprised descriptive statistics to present the mean and standard deviation of the whole sample divided by gender. Inferential statistics comprised the Shapiro–Wilk test to assess the data distribution; the Student's *t*-test was used to compare means between the male and female groups; statistical significance was set at *p* ≤ 0.05. Cohen's effect size (d) was applied to identify meaningful differences between the groups. Based on Cohen's criteria, d = 0.80 (absolute value) was considered a large effect size, and d = 0.50 (absolute value) was considered a medium effect size. Post hoc power calculations were performed with G\*Power v.3.1. Three qualified examiners were selected to perform the positioning of the markers and the postural analysis in the two different parts of the day to assess the reproducibility of the app. The two-way mixed effect for absolute agreement was the model for calculating the intraclass correlation coefficient (ICC) for inter-rater agreement. The cut-off values for reproducibility based on a 95% confidence interval of the ICC estimate were <0.5 (poor), between 0.5 and 0.75 (moderate), between 0.75 and 0.9 (good), and >0.9 (excellent) [17]. All the statistical analyses were performed with R Project for Statistical Computing (Vienna, Austria).

#### **3. Results**

Anthropometric measurements were taken for each subject and grouped by gender, with a mean male height of 175 (SD ± 5.6) cm, a mean female height of 164.6 (SD ± 6.5) cm, and a mean male weight of 75.5 (SD ± 8.8) kg and a mean female weight of 58.13 (SD ± 7.41) kg.

The post hoc power calculation analysis with G\*Power 3.1 returned a statistical power of 0.696 for our sample. The analysis of the digital anatomical landmarks collected with the Apecs app and the ICC values are presented in Table 2. The Student's *t*-test statistically indicated differences in the postural evaluation performed by the mobile app Apecs between males and females for specific variables. The postural variables with significant differences between male and female groups in the anterior coronal plane were axillary alignment (*p* = 0.04), trunk inclination (*p* = 0.03), and knee alignment (*p* = 0.01). The female group presented more body inclination to the right than men, more trunk inclination, and a wider knee angle in the anterior coronal plane. The male group showed the worst results for the axillary alignment, which resulted in greater deviation from the ideal alignment than that of the female group. In the sagittal plane, statistically significant differences were found for head inclination (*p* = 0.04), tibia shift (*p* = 0.01), and foot angle (*p* < 0.001). The head of the female group was more significantly shifted from the ideal alignment compared to that of the male group and also showed a more accentuated anterior tibial shift. Instead, the male group presented a wider foot angle than the female group. No statistically significant differences were found between groups for the evaluation of the posterior coronal plane. According to Cohen's d, there was a small effect size only for ribcage tilt (d = −0.35) in the anterior coronal plane, for head alignment in the sagittal plane (d = −0.38), and a large effect size for knee angle in the anterior coronal plane (d = −0.89), tibia shift in the sagittal plane (d = −0.95), and foot angle in the sagittal plane (d = 1.6).

Figures 3–5 show the box plots for gender differences in the three space planes.

**Figure 3.** Box plots of the differences between male and female groups in the anterior coronal plane with indication of significance. Figure (**A**) is for body alignment; figure (**B**) is for head alignment, figure (**C**) is of acromion alignment, figure (**D**) is for axillae alignment, figure (**E**) is for trunk inclination, figure (**F**) is for ribcage tilt, figure (**G**) is for antero superior iliac spine inclination, figure (**H**) is for knee angle. \*: *p* < 0.05; \*\*\*: *p* < 0.001.

**Figure 4.** Box plots of the differences between male and female groups in the posterior coronal plane. Figure (**A**) is for body alignment; figure (**B**) is for head alignment, figure (**C**) is of shoulder alignment, figure (**D**) is for axillae alignment, figure (**E**) is for scapulae alignment, figure (**F**) is for trunk inclination, figure (**G**) is for postero superior iliac spine inclination, figure (**H**) is for knee angle, figure (**I**) is for foot angle.

**Figure 5.** Box plots of the postural differences between male and female groups in the sagittal plane with indication of significance. Figure (**A**) is for body alignment; figure (**B**) is for head alignment, figure (**C**) is of acromion alignment, figure (**D**) is pelvic tilt, figure (**E**) is for tibia shift, figure (**F**) is for fibula alignment, figure (**G**) is for foot angle. \*: *p* < 0.05; \*\*: *p* < 0.01; \*\*\*: *p* < 0.001.

**Table 2.** Description of group means and ICC of the postural variables analyzed.

ASIS: anterior superior iliac spines; PSIS: postero superior iliac spines. \* *p*-value < 0.05; \*\* *p*-value < 0.01; \*\*\* *p*-value < 0.001.

The ICC showed promising results for inter-rater reproducibility, with values > 0.90 for thirteen out of the twenty-two postural variables examined and >0.60 for the other three variables; only six variables did not meet the cut-off criteria required to be considered reliable. Table 2 shows the ICC for the postural variables evaluated.

#### **4. Discussion**

This study aimed to present normative data about the digital posture evaluation of healthy young adults performed by the mobile app Apecs and to evaluate its reproducibility. The first finding was that the app is sensible to postural variation, considering that it was capable of detecting postural differences between males and females. The second finding of the study was that this mobile app presents a good inter-rater reproducibility for all the postural variables examined except for head alignment, trunk inclination and axillae alignment in the anterior and posterior coronal plane, and acromion alignment in the sagittal plane.

The Apecs app has already been used for research purposes to evaluate postural behaviors related to specific ergonomic studies' work [12] and to evaluate body segment angles in subjects with adolescent idiopathic scoliosis [18]. However, the studies mentioned above had small samples; the first used the app only to compare their sample's posture at rest and during working activity, and the second only evaluated angles in the frontal and sagittal plane. Hence, to the best of our knowledge, this is the first study that employs the mobile app Apecs to evaluate global posture, providing normative data and assessing its reproducibility as a posture evaluation tool.

The sample in this study was composed of 100 participants equally distributed between males and females, and the Apecs mobile app was capable of detecting postural differences when present. It emerged from the postural analysis of the anterior coronal

plane that females presented a wider knee angle; this could be due to the overall increased knee laxity and reduced stiffness in females compared to males [19]. In a previous study by Raine et al. [20], no sex differences were found for head inclination on the sagittal plane; conversely, we found that the head inclination was more accentuated in the female group compared to the male group. However, Raine et al.'s study dates from 1997, and they considered an older sample size. These observations may be the cause of the differences compared to our study. Iacob et al. [21] analyzed the posture of a sample of people with malocclusion through the PostureScreen® mobile app, comparing it with a healthy sample. We found a difference between our postural data gathered with Apecs and those reported by Iacob et al. for the same variable analyzed. These authors found, on the frontal plane, a head alignment in their sample of 3.86◦ ± 2.45, a shoulder alignment of 1 ± 0.97, and a hip deviation of 1.42 ± 1.28, while, for the same variable, we reported a head alignment of 2.7 ± 1.5, a shoulder alignment of 1.5 ± 1.2, and postero superior spine inclination of 1.9◦ ± 1.4. The differences in the postural evaluation between the two apps might be due to the differences in the samples considering that the control group of young healthy young adults investigated by Iacob et al. was composed of only 14 people, and they were almost exclusively females.

We found a statistically significant difference in the sagittal plane for foot angle, with the male group presenting higher values; this finding could be related to the generally bigger size of the foot anthropometrics of males [22]. In the anterior and posterior coronal planes, we did not find any statistically significant difference between gender for foot posture parameters, in line with previous studies [23,24].

The reproducibility analysis of Apecs showed excellent results for all the variables examined on the sagittal plane except for the acromion alignment. The marker placed on the acromion was not clearly visible during the positioning of the digital marker in this plane of space, making it difficult to evaluate with consistency among raters. The same issue occurred in the posterior coronal plane for the trunk inclination, where the app asks raters to identify "the most intended point of the trunk", which was not easy to replicate for the raters. Interestingly, the two less reliable measures in the anterior coronal plane were the axillae alignment and the trunk inclination, indicating that this mobile app should be carefully considered when a precise measure of these variables is needed. Accordingly, with what was stated by Szucs et al. [14] when evaluating the PostureScreen® mobile app, we suggest that the quality of the evaluation is higher when markers are placed on the subject and are clearly visible during the positioning of the digital markers; however, neither the Apecs manufacturer nor the PostureScreen mobile one specifies this in their instruction for postural analysis.

The current study presents some limitations. First, we considered a sample composed exclusively of young adults, so we could not assess whether the Apecs app is a feasible tool to employ in the postural evaluation of pediatric and elderly populations. Second, all the individuals in the sample were healthy, thus, these results should be carefully interpreted when examining individuals with pathologies that influence the musculoskeletal system. Third, we did not compare measures collected with Apecs with those collected by postural gold standard instruments to assess the validity of the app. Further studies should investigate the validity of Apecs as a reliable postural assessment tool, comparing it with rasterstereography or marker-based systems. However, these normative data may help those involved in the analysis of postural alterations as a comparative standard with a healthy sample. Finally, the digital landmark positioning accomplished with the app may be challenging for less experienced users and might change the evaluation results.

#### **5. Conclusions**

The mobile postural app Apecs demonstrated good reproducibility for most of the postural variables analyzed and could detect postural differences between males and females when present. The app was easy to use for all the raters, from the more experienced to the less experienced ones, indicating that Apecs could be a cheap and feasible good

alternative to more expensive postural assessment devices for researchers and clinicians. However, trunk inclination and axillae alignment were unreliable in all the planes of space where they were evaluated, and head alignment was reliable only in the sagittal plane. Clinicians should be aware of this issue when using Apecs and carefully predetermine the landmark positioning and digital identification during the analysis to minimize the possibilities of errors for the postural variables not clearly described by the Apecs manufacturer. In conclusion, the Apecs app could be a potentially useful tool for clinicians and researchers to implement in the preventive care of postural disorders given its ease of use and cheap costs.

**Author Contributions:** Conceptualization, B.T. and F.R.; Methodology, B.T., F.R., and L.P.; Statistical Analysis, F.R., B.T., and R.G.; Investigation, G.M.; Resources, G.M.; Data Curation, M.S. and M.Z.; Writing—Original Draft Preparation, B.T., F.R., and L.P.; Writing—Review and Editing, R.G. and G.M.; Visualization, M.S. and M.Z. Supervision, G.M.; Funding Acquisition, G.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the University Research Project Grant PIACERI Found— NATURE-OA—2020–2022, Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, Italy.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the scientific committee of the University of Catania (protocol no.: CRAM-017-2020, 16 March 2020).

**Informed Consent Statement:** All subjects gave their informed consent for inclusion before they participated in the study.

**Data Availability Statement:** Data are available upon appropriate request.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **Relation between Photogrammetry and Spinal Mouse for Sagittal Imbalance Assessment in Adolescents with Thoracic Kyphosis**

**Guido Belli 1, Stefania Toselli 1, Mario Mauro 1,\*, Pasqualino Maietta Latessa 1 and Luca Russo 2**

**Abstract:** The evaluation of postural alignment in childhood and adolescence is fundamental for sports, health, and daily life activities. Spinal Mouse (SM) and photogrammetry (PG) are two of the most debated tools in postural evaluation because choosing the proper instrument is also important to avoid false or misleading data. This research aims to find out the best linear regression models that could relate the analytic kyphosis measurements of the SM with one or more PG parameters of body posture in adolescents with kyphotic posture. Thirty-four adolescents with structural and non-structural kyphosis were analyzed (13.1 ± 1.8 years; 1.59 ± 0.13 m; 47.0 ± 12.2 kg) using SM and PG on the sagittal plane in a standing and forward-bending position, allowing us to measure body vertical inclination, trunk flexion, and sacral inclination and hip position during bending. The stepwise backward procedure was assessed to estimate the variability of the grade of inclination of the spine and thoracic spine curvature with fixed upper and lower limits, evaluated with SM during flexion. In both models, the PG angle between the horizontal line and a line connecting the sacral endplate–C7 spinous process and the PG hip position were the best regressors (*adjusted-R*2 SM bend = 0.804, *p* < 0.001; *adjusted-R*2 SM fixed bending = 0.488, *p* < 0.001). Several Spinal Mouse and photogrammetry parameters showed significant correlations, especially when the Spinal Mouse measurements were taken when the adolescents were in the forward-bending position. Physicians and kinesiologists may consider photogrammetry as a good method for spinal curve prediction.

**Keywords:** kyphosis; spinal mouse; photogrammetry; kinesiology; postural evaluation

#### **1. Introduction**

Postural alignment in childhood and adolescence can be considered one of the most important sources of worry for parents, with particular attention being paid to the spine. Altered postural alignments can be classified as structural and non-structural misalignments, even if the postural appearance of these disturbances may be similar [1]. Structural misalignments indicate the presence of morphological abnormalities within the bones and soft tissues. Conversely, non-structural misalignments do not show any bone disorder but evidence a non-anatomic spine alignment with a moderate-to-good degree of selfcorrection [2]. Both structural and non-structural misalignments can affect the sagittal balance of the spine [3–5].

With specific regard to the sagittal plane, several classifications have been previously reported [2,6–9]. Within these classifications, kyphotic posture is frequently and easily recognized by parents. The thoracic spine in children and adolescents can be defined in a normal range as being between 20–40◦ degrees [1], and hyperkyphosis diagnosis is considered beyond 45◦ [10,11]. Nevertheless, other authors suggest that the average values of thoracic kyphosis are 42.0◦ ± 10.6◦ and 45.8◦ ± 10.4◦ from a cohort of 167 children of 8.1 ± 2.0 years and 479 adolescents of 13.6 ± 1.9 years, respectively [12].

**Citation:** Belli, G.; Toselli, S.; Mauro, M.; Maietta Latessa, P.; Russo, L. Relation between Photogrammetry and Spinal Mouse for Sagittal Imbalance Assessment in Adolescents with Thoracic Kyphosis. *J. Funct. Morphol. Kinesiol.* **2023**, *8*, 68. https://doi.org/10.3390/jfmk8020068

Academic Editor: Luca Petrigna

Received: 31 March 2023 Revised: 13 May 2023 Accepted: 17 May 2023 Published: 19 May 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Measuring procedures in posture can be widely utilized, such as with posturography, to analyze the effect of specific interferences on postural control [13–15]; or they can be analytical and descriptive, such as with photogrammetric analysis of the spine, with a focus on sagittal balance assessment using non-radiographic methods as an example [16]. In the last 15 years, the main three non-radiographic methods for spine evaluation were rasterstereography, skin-surface mouse, and photogrammetry [17–20]. Rasterstereography is mainly represented by two kinds of measuring methods: (1) the first one uses the analysis of the light projected on the subject's skin; it is reliable and represents the most widespread solution for the application of rasterstereography [21–23]; (2) the second one uses an infrared and time-of-flight 3D RGB camera, and it seems to be reliable as well [24]. The skinsurface mouse is mainly represented by Spinal Mouse® (IDIAG, Fehraltorf, Switzerland), a valid and reliable tool for spine assessment, in particular for kyphotic posture [25,26], that can be rolled along the profile of the spine measuring the vertebral shape and angulation [16,27–29]. Finally, photogrammetry, in particular 2D modality, is one of the most used and cheapest tools for kinematic and geometrical analysis of motion and even posture. It can be performed using different software, and many of them are valid and reliable [30–32]. All these non-radiographic methods evidence some advantages but show several limits for spine evaluation. Researchers, but even more so professionals, should always balance the cost/effectiveness ratio as well as the ease and accuracy of the measurement. Rasterstereography usually offers a wide range of postural parameters; it is very fast to use but represents a high-cost tool. Spinal Mouse has a lower cost, but the price range is not accessible for all; the accuracy is high, as is the software analysis, but this is only focused on the spine [25,27]. Finally, photogrammetry is the cheaper one, as well as the less "smart". Depending on software features and user skills, photogrammetry can be more or less "user friendly"; at the same time, it also allows the user to obtain measures of the whole body, not only of the spine [32].

Within this scenario, it could be very interesting for professionals to use photogrammetry, the easiest and cheaper way, as a global screening tool to detect in advance the signs of a spine misalignment, with particular regard to the kyphosis curvature. Considering the whole body as a kinetic chain [33], and that photogrammetry could easily measure the alignment of the whole body with good validity and reliability [32], a relation could be hypothesized between thoracic spine behavior and one or more photogrammetric measurements of body posture. Although radiographic and photogrammetric procedures have been previously investigated in order to quantify thoracic kyphosis and lumbar lordosis [34,35], the comparison between Spinal Mouse® evaluation and photogrammetry is lacking. Since Spinal Mouse® can be used in several body positions (upright standing, forward trunk bending, seated side-bending, for example), additional information could be obtained from this device. Therefore, this study aims to find out a model of regression that could relate global and analytic measurements of the Spinal Mouse® on the sagittal plane with one or more photogrammetric parameters of body posture in adolescents with kyphotic posture.

#### **2. Materials and Methods**

#### *2.1. Design and Participants*

This is a cross-sectional study design. Participants were recruited from Fisiokinè Medical Centre (Scandiano, Reggio Emilia, Italy). The criteria of selection included a diagnosis of increased thoracic kyphosis (postural or structural hyperkyphosis), no history of musculoskeletal or neurological pain in the last 3 months, no prior surgical intervention for spine disorders, and aged between 10 to 16 years old. No gender restrictions were defined. All participants were informed and gave voluntary consent to participate in the study. Parents' consent was requested, since participants were younger than 18 years old. The privacy criteria were met. The study was approved by the Bioethics Committee of the University of Bologna and was conducted in accordance with the guidelines of the Declaration of Helsinki; the project identification code was n.2.18.

During the recruitment phase, each participant completed the anamnesis investigation. All specific medical reports were collected and analyzed to meet the selection criteria. The enrolment phase lasted 6 months, from June to December 2022.

#### *2.2. Measurements Instruments*

#### 2.2.1. Spine Analysis

To evaluate spinal curves and trunk alignment, the SpinalMouse® (IDIAG M360®, Mülistrasse 18, CH-8320 Fehraltorf, Switzerland) device was used. It is a non-invasive computer-assisted medical device that quantifies the curvature and mobility of the spinal column in the frontal and sagittal planes by gliding manually along the spine [28,36]. Data are sampled every 1.3 mm while the mouse is rolled from vertebra C7 to S3, giving a sampling frequency of approximately 150 Hz. Results are wirelessly transferred to a computer, where the IDIAG software displays vertebral positions, joint angles, and spinal measurements. A recent study reported a high correlation between Cobb angle evaluated with X-ray and intra (ICC = 0.872) or inter-observer (ICC = 0.962) SpinalMouse® measurements on the frontal plane [37]. In addition, this device evidenced excellent intrarater reliability for the analysis of sagittal thoracic and lumbar curvature and mobility in hyperkyphosis [25]. In the present study, the SpinalMouse® measurements were performed by a trained specialist with more than five years of experience. Data were collected in a quiet and well-lit environment with a comfortable temperature [38,39]. The evaluation was settled in the morning to avoid positional differences in the spine due to fatigue and/or daily stress factors. After undressing the upper body, the C7–S3 vertebral spinal processes were determined and marked with a dermographic pen by the specialist while the patient was standing up in the anatomical position. Measurements were performed in 3 different trunk positions during standing: neutral, maximal flexion, and extension (sagittal plane evaluation). In the neutral position, the participant was asked to maintain a relaxed position, looking and facing horizontally toward the wall, with the feet shoulder-width apart and with straight knees and arms by the side. In maximal flexion, the subject was asked to flex the trunk with extended legs as far as possible, aiming to touch the ground with fingertips. In maximal extension, the participant was asked to cross their arms in front of the chest and extend the trunk as far as possible, without extension of the cervical spine. SpinalMouse® was then moved downwards along the spinal criteria points, in each position. Participants did not perform a warm-up before the examination. Some specific measures were extracted and analyzed from all raw data available. The eight variables were: the inclination of the spine in standing (SM stand); the inclination of the spine during flexion (SM bend); thoracic spine curvature with fixed upper and lower limits (first and last thoracic vertebra) in standing (SM fixed stand) and during flexion (SM fixed bend); thoracic spine curvature with physiological upper and lower limits (defined by Spinal Mouse software) in standing (SM phys. stand) and during flexion (SM phys. bend); and spine length in standing position (SM Rachid stand) and during flexion (SM Rachid bend). Figure 1 shows some of all Spinal Mouse possible measurements displayed using IDIAG M360 software and used in the present study.

#### 2.2.2. Photogrammetric Postural Analysis

Postural evaluation using photogrammetry has been previously demonstrated to be a reliable method in young people with postural misalignments [40,41]. Recently, photogrammetric measurements of thoracic kyphosis showed excellent test–retest reliability (ICC = 0.97; SEM = 1.67; MDC = 4.62) in adolescents with hyperkyphosis and evidenced a strong correlation between the values obtained with this technique and radiography methods [42]. In the present study, 2 digital photographs (standing right-side and standing with trunk flexion) were recorded using a portable device (Tablet Huawei® Mediapad, Huawei Base, Bantian, Longgang District, Shenzhen, China) to analyze the sagittal plane. The device was set on a tripod, three meters away from the line marking the position of the participant. The height of the tripod was adjusted so the middle of the objective lens was

100 cm above the ground [43]. Each participant was initially positioned in front of the camera with a postural grid (ATS®, Largo Cairoli 10, 52100 Arezzo, Italy) on the back, then made to turn their body to the left to show the right side perpendicular to the lens, with feet placed in a fixed position over a specific area (standing right-side position —Figure 2A). Successively, participants flexed the trunk and remained in the forwardbending position (standing trunk flexion position—Figure 2B–D). The APECS-AI Posture Evaluation and Correction System® (New Body Technology SAS, 12 Rue Pierre Semard, Incubagem 38000 Grenoble, France) was used to evaluate absolute and relative angles in the sagittal plane [29,32]. Specifically, the following angles were investigated: body vertical inclination (absolute angle between the vertical line and a line connecting the lateral malleolus–tragus of the ear: PG mall–tragus); trunk flexion (absolute angle between the horizontal line and a line connecting sacral endplate—C7 spinous process, PG trunk bend); sacral inclination during bending (absolute angle between horizontal line and a tangent line to the sacral dorsum, PG sacrum bend); hip position during bending (absolute angle between the vertical line and a line connecting the lateral malleolus–greater trochanter, PG hip bend). To better detect previous anatomic landmarks during photographic analysis, an adhesive tape was applied to the skin [43].

**Figure 1.** Example of Spinal Mouse report—thoracic and lumbar curvature (**left side**); body inclination (**right side**).

Figure 2 shows the four angles analyzed with the APECS application.

#### *2.3. Statistical Procedure*

The descriptive statistics were reported as the mean, standard deviation (std), minimum (min), and maximum (max) values for each variable. The variables' distribution was verified with the Shapiro–Wilk test. The Pearson product–moment (r) was calculated to measure the degree of correlation between the variables. To perform the best regression model, the stepwise backward procedure was assessed with a significant level for entry or removal to or from the model equal to 0.10. The model's heteroskedasticity was checked using the Breusch–Pagan/Cook–Weisberg test. The multicollinearity was checked using the variance inflation factor (VIF), and a value lower than 5 was considered acceptable (moderate correlation) [44]. The Cook's distance plot was performed to look for the outlier presence, with a threshold settled at n/4. If one or more outliers affected the model, they were removed, and a new model was performed. The adjusted R2 was calculated to report the goodness-of-fit for the proposed model. Additionally, the F value, the root MSE, the regression coefficient (β), the standard error, the student's *t*-test value, and the 95% confidence interval were reported. The significance level was settled at ≤0.05. Finally, the Bland–Altman plot, the pairwise correlation, and the concordance correlation coefficient (CCC) were computed to compute the degree of agreement between the Spinal Mouse and photogrammetry [45].

#### **3. Results**

Table 1 shows the descriptive statistics for all the variables. No missing value was met for all variables (n = 34). Similar values were found between fixed and physiological Spinal Mouse evaluation, in both standing (45.94 ± 8.24 and 48.29 ± 9.14) and bending (63.71 ± 10.23 and 63.41 ± 9.45) positions. The highest grade was found in the inclination of the spine during flexion (122◦), whereas the smallest value was the grade of the inclination of the spine in a standing position (−6◦).

**Table 1.** Descriptive statistics.

Note: n, number of observations; std, standard deviation; min, minimum value observed; max, maximum value observed; PG, photogrammetry; mall, malleolus; bend, bending; SM, Spinal Mouse; stand, standing; phys., physiological kyphosis.

Table 2 shows the variables' correlation matrix. Generally, high Pearson correlation coefficients between Spinal Mouse and photogrammetry measurements were found in the bending position (*p* < 0.05). In particular, a wide positive correlation appeared among the inclination of the spine during trunk flexion and trunk flexion, calculated as the absolute angle between the horizontal line and a line connecting the sacral endplate–C7 spinous process (r = 0.839, *p* < 0.001). Differently, the grade of the inclination of the spine during flexion decreased with the increasing of the absolute angle between a horizontal line and a tangent line to the sacral dorsum (r = −0.732, *p* < 0.001). Additionally, the thoracic spine curvature with fixed upper and lower limits in the bending position showed high correlations with the trunk flexion and the sacral inclination detected using photogrammetry (*p* < 0.001).

**Table 2.** Variables' correlation matrix.

**Table 2.** *Cont.*

Note: PG, photogrammetry; mall, malleolus; bend, bending; SM, Spinal Mouse; stand, standing; phys., physiological kyphosis; \* *p*-value ≤ 0.05.

#### *Linear Regression Models*

Table 3 shows the result of the stepwise procedure. Two outliers were removed from the first model, and the two photogrammetry measurements in bending, such as the angle between the horizontal line and a line connecting the sacral endplate–C7 spinous process and the hip position, explained 80.4% of the variability of the spine inclination during trunk flexion measured with the Spinal Mouse on 32 adolescents. The Breusch-Pagan/Cook-Weisberg test accepts the null hypothesis of heteroskedasticity absence (*χ*2 (1) *=* 0.77, *p* = 0.711). The mean VIF was 1.19.

**Table 3.** Best linear regression model for bending Spinal Mouse estimation.

Note: SS, squared sums; df, degrees of freedom; MS, squared means; n, number of observations; *F*, Snedecor– Fisher's test; *p*, *p*-value; *R*2, the goodness-of-fit; Adj., adjusted; MSE, mean of squares error; *β*, regression coefficient; *t*, Student's test; CI, confidence interval.

Figure 3 shows the scatterplots with the errors of bending SM and each regressor, respectively.

Figure 4 shows the Bland–Altman graph (A) and scatterplot with Spinal Mouse and the new model (B). The concordance correlation coefficient was 0.995 and Pearson's r = 0.904 (mean = 90.125 ± 12.067).

The new equation to estimate the Spinal Mouse degree in bending is

*SM bend* = (0.86413 · *PG hip bend*) + (1.0557 · *PG trunk bend*) − 12.749

Table 4 shows the result of the stepwise procedure on the thoracic spine curvature with fixed upper and lower limits, in the bending position. Three outliers were removed from the first model, and the two photogrammetry measurements in bending explained 48.79% of the Spinal Mouse fixed kyphosis variability in 31 adolescents. The Breusch– Pagan/Cook–Weisberg test accepts the null hypothesis of heteroskedasticity absence (*χ*2 (1) *=* 1.80, *p* = 0.179). The mean VIF was 1.32.

**Figure 3.** Errors' scatterplots with SM and PG model regressors. Note: β, regressor coefficient; se, standard error; t, Student's *t*-test.

**Figure 4.** Bland–Altman plot (**A**) and scatterplot (**B**) with gold standard and new estimated model. Note: CCC, concordance correlation coefficient; σ, standard deviation; r, Pearson correlation coefficient; CI, confidence interval.

**Table 4.** Best linear regression model for Spinal Mouse fixed kyphosis estimation.

Note: SS, squared sums; df, degrees of freedom; MS, squared means; n, number of observations; *F*, Snedecor– Fisher's test; *p*, *p*-value; *R*2, goodness-of-fit; Adj., adjusted; MSE, mean of squares error; *β*, regression coefficient; *t*, student's test; CI, confidence interval.

Figure 5 shows the scatterplots with the errors of SM fixed kyphosis measured in bending position and each regressor, respectively.

**Figure 5.** Errors' scatterplots with SM fixed kyphosis and PG model regressors. Note: β, regressor coefficient; se, standard error; t, Student's *t*-test.

Figure 6 shows the Bland–Altman graph (A) and scatterplot with Spinal Mouse fixed kyphosis and the new model (B). The concordance correlation coefficient was 0.686 and Pearson's *r* = 0.723.

**Figure 6.** Bland–Altman plot (**A**) and scatterplot (**B**) with fixed Spinal Mouse in bending position and the new estimated model. Note: CCC, concordance correlation coefficient; σ, standard deviation; r, Pearson correlation coefficient; CI, confidence interval.

The new equation to estimate the Spinal Mouse fixed kyphosis degree in the bending position is

*SM fixed bending =* (−2.122705 · *PG hip bend*) *+* (−0.678946 · *PG trunk bend*) *+* 144.2784

#### **4. Discussion**

The present study aimed to correlate photogrammetry and Spinal Mouse® during the postural evaluation of adolescents with a diagnosis of structural or non-structural hyperkyphosis. Current findings evidence a positive correlation between some measurements of standing trunk flexion performed with both devices and highlight how photogrammetry

could explain 80.4% of Spinal Mouse variability during forward bending. To the best of our knowledge, this is the first study that compared SM and PG.

In recent years, several authors analyzed the reliability and validity of non-radiographic methods during sagittal balance assessment in different populations. Since an adequate anterior–posterior balance condition is fundamental to maintaining an upright, efficient, and painless posture, the evaluation of the sagittal profile has gained much relevance in spinal pathology [46]. In this direction, Cohen et al. [16] reported that plumbline, surface topography, infrared motion analysis, and SM show moderate-to-high validity and reliability. In their systematic review of 14 articles, authors suggested that these methods can be a non-invasive approach to monitor global sagittal balance, even if specific limitations are present and spinopelvic parameters represent the "gold standard" (sacral vertical axis, pelvic tilt, and sacral slope, as an example). Furthermore, Barret et al. [26] evidenced that SM, the Debrunner kyphometer, and the Flexicurve index have the strongest levels of reliability among 15 non-radiographic methods to assess thoracic kyphosis. Starting from this consideration and previous research [25,47,48], SM was included in our study. Roghani et al. evaluated SM reliability on a sample of women with and without hyperkyphosis (aged between 60–80 years), with a focus on thoracic and lumbar curvature, pelvic position, trunk inclination, and spine mobility. The results evidenced a high intra-rater reliability for all measurements in both groups (ICC: 0.89–0.99), with standard error of the means (SEMs) ranging from 1.02◦ to 2.06◦ and from 1.15◦ to 2.22◦ in the hyperkyphosis and normal group, respectively. In addition, the minimal detectable change (MDC) ranged from 2.85◦ to 5.73◦ in the hyperkyphosis group and from 3.20◦ to 6.17◦ in the normal group. The authors concluded that SM is a useful, easy, and low-risk device to assess spinal curvature and mobility. Demir et al. evaluated SM test–retest reliability in 28 female adolescents (aged between 15–18 years) during upright standing on the frontal and sagittal planes. Their results evidenced good reliability for thoracic and lumbar curvature on the sagittal plane and confirmed the use of these tools for "in-field" screening and clinical assessment. Muyor and collaborators analyzed the Sit-and-Reach Test and Toe-Touch test (same as the forward bending test) using SM to define the criterion validity of both tests during hamstring flexibility assessment. The study involved 141 athletes from different sports (tennis players, kayakers, canoeists, cyclists), all aged between 15–17 years. Research findings suggested that pelvic tilt and lumbar motion have a greater impact on test scores than hamstring flexibility (measured with a passive straight leg test). In the present study, only some SM measurements were investigated. Specifically, fixed and physiologic thoracic curvature, body inclination, and spine length in upright and bending positions were chosen. The reason is mainly related to: (1) the sample features (adolescents with postural or structural hyperkyphosis); (2) to compare these parameters with some specific photogrammetric variables; (3) to attempt to find a few quick and easy-to-detect photogrammetric landmarks [31,49]. Mean values for SM thoracic curvature in a standing position were 45.9◦ and 48.2◦ for fixed and physiological kyphosis, respectively. These values are slightly above the reported range for normal curvature (20–40◦) and evidence of slight hyperkyphosis. Similar values have been reported in different sports players performing in flexed positions (kayak, canoa, tennis) and that were aged between 15–17 [50], as well as for adolescents aged between 12–15 [51]. Anyway, it must be considered that higher values have been found for structural spine misalignment diagnosis (range of 50–62◦) compared to non-structural (range of 38–50◦).

For photogrammetric analysis, the application APECS-AI Posture Evaluation and Correction System® has been used. This tool is an easy and low-cost program that allows one to assess body posture in different positions. Recently, Trovato et al. [32] evaluated a sample of 50 males and 50 females (mean age 23.4 years) to investigate gender differences in anterior coronal, posterior coronal, and sagittal planes. Their results evidenced good reproducibility for most of the 24 variables analyzed and reported some gender-related features. In the present study, only four sagittal parameters were investigated to assess the anterior–posterior balance in upright and bending positions. This selection has been

defined for the abovementioned reasons. In particular, trunk inclination in both positions and pelvic motion during forward bending have been correlated with thoracic curvature. As regards body alignment, the results evidenced a mean value of 2.7◦ and 91.7◦ during standing or bending positions, respectively. Sagittal vertical inclination (upright posture) is similar to the reference value of 2.6◦ highlighted by Trovato et al. in their sample and superior to the reference value of 1.73◦ defined by Krawky et al. [31]. The difference could be related to the photogrammetry techniques reported in both studies [43,52]. Results did not show a correlation between PG and SM in relation to this parameter (2.6◦ vs. 1.6◦, respectively). Since the body vertical alignment using PG was calculated by using the absolute angle between the vertical line and a line connecting the lateral malleolus–tragus of the ear, while SM evaluated it from the C7–S3 connection and vertical line, this result could be expected. Conversely, a significant positive correlation was found between the two devices during the bending position. In this postural assessment, PG and SM used a similar technique (absolute angle between the horizontal line and a line connecting the sacral endplate–C7 spinous process for PG or absolute angle between the vertical line and a line connecting the S3–C7 spinous process for SM). The landmarks for pelvic parameters during forward bending were defined as reported by Carregaro et al. [53]. Since adolescents with hyperkyphosis show a low level of flexibility across the muscular posterior chain, sacral inclination and hip position were calculated to investigate pelvic displacement in the sagittal plane [6,33,48]. PG Sacrum inclination evidenced a significant correlation with SM trunk inclination during bending, and linear regression reported that trunk bending added to hip bending explained 80.4% of SM variability in relation to this parameter (first model). Furthermore, the same PG variables explained 48.7% of SM variability concerning thoracic curvature during bending. These results highlight how the photogrammetric analysis of the pelvic region is deeply connected with spine inclination in this kind of subject.

Since the present study aims to correlate quick and easy-to-detect PG measurements with Spinal Mouse®, the abovementioned variable was chosen. Previous researchers analyzed different pelvic parameters using photogrammetry (pelvic horizontal alignment and hip angle, for example), especially in the upright position [31,49]; however, there is a lack of research on the bending posture [53]. Specifically, the focus has been more addressed on frontal plane analysis than on the sagittal plane [54]. Finally, SM and PG have recently been investigated in body perception in adolescents with idiopathic scoliosis [29].

#### *Limitations*

The sample size, participants' ages, morpho-structural characteristics, differences in spine misalignment, and level of physical activity represent limits in our work. Furthermore, Spinal Mouse® and photogrammetry could be affected from measurement errors. Although the reliability and validity of both methods have been previously described, the occurrence of possible evaluation errors must be considered (markers positioning and angles investigation using photogrammetry or skin surface contact during Spinal Mouse® analysis, for example). Future investigations are needed investigating the role of Spinal Mouse® and photogrammetry during postural evaluation in adolescents with structural and non-structural hyperkyphosis and in relation to specific phases of treatment.

#### **5. Conclusions**

The present study suggests that photogrammetry can be considered an easy, inexpensive, and rapid tool for postural screening in adolescents with both structural and non-structural hyperkyphosis. Photogrammetry can be a useful alternative in the absence of other specific instruments, although it should be noted that photogrammetry is more suitable for screening rather than diagnosis. Photogrammetry is significantly correlated with the SM parameters when the analysis is taken during spine forward-bending. Specifically, the pelvic motion measured with photogrammetry can predict over 80% of the SM spine inclination. Differently, these instruments exhibited low correlations in standing positions. In conclusion, Kinesiologists and professionals involved in postural assessment

are encouraged to use photogrammetry in bending as a first-line assessment tool to evaluate the sagittal spinal profile of adolescents.

**Author Contributions:** Conceptualization, G.B. and L.R.; methodology, G.B., L.R. and M.M.; software, P.M.L.; validation, G.B., L.R. and M.M.; formal analysis, M.M. and S.T.; investigation, G.B.; resources, P.M.L. and S.T.; data curation, G.B., L.R. and M.M.; writing—original draft preparation, G.B., L.R. and M.M.; writing—review and editing, G.B. and L.R.; visualization, S.T.; supervision, P.M.L.; project administration, G.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of University of Bologna (n. 2.18).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

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## *Article* **Effects of Feedback-Supported Online Training during the Coronavirus Lockdown on Posture in Children and Adolescents**

**Oliver Ludwig 1,\*, Carlo Dindorf 1, Torsten Schuh 2, Thomas Haab 3, Johannes Marchetti 1,3 and Michael Fröhlich 1**

	- **\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** (1) Background. The coronavirus pandemic had a serious impact on the everyday life of children and young people with sometimes drastic effects on daily physical activity time that could have led to posture imbalances. The aim of the study was to examine whether a six-week, feedbacksupported online training programme could improve posture parameters in young soccer players. (2) Methods. Data of 170 adolescent soccer players (age 15.6 ± 1.6 years) were analyzed. A total of 86 soccer players of a youth academy participated in an online training program that included eight exercises twice per week for 45 min (Zoom group). The participants' exercise execution could be monitored and corrected via smartphone or laptop camera. Before and after the training intervention, participants' posture was assessed using photographic analysis. The changes of relevant posture parameters (perpendicular positions of ear, shoulder and hips, pelvic tilt, trunk tilt and sacral angle) were statistically tested by robust mixed ANOVA using trimmed means. Postural parameters were also assessed post hoc at 8-week intervals in a control group of 84 participants of the same age. (3) Results. We found a statistically significant interaction (*p* < 0.05) between time and group for trunk tilt, head and shoulder protrusion and for hip anteversion in the Zoom group. No changes were found for these parameters in the control group. For pelvic tilt no significant changes were found. (4) Conclusions. Feedback-based online training with two 45 min sessions per week can improve postural parameters in adolescent soccer players over a period of six weeks.

**Keywords:** posture training; feedback; COVID-19; neck-shoulder-region; shoulder protraction; upper crossed syndrome; posture weakness; physical inactivity; sedentary behavior; soccer

#### **1. Introduction**

Postural disorders are widespread in childhood and adolescence and are reported with a prevalence of 25–60% [1–3].  Current studies have shown that this can lead to pain at an older age. For example, Dolphens et al. demonstrated in 1196 children and adolescents that increased forward head tilt was associated with lifetime prevalence of neck pain [5]. Kim et al. in turn were able to demonstrate, that a protracted head could lower respiratory functions in young adults [6]. An important cause for the occurrence of postural weaknesses is apparently muscular imbalances that lead to the displacement of individual body parts [7,8]. A sedentary everyday life seems to promote such imbalances, and the intensive use of smartphones also apparently leads to postural adaptations, especially forward displacement of the shoulder and head [9,10].

In 2020, the coronavirus pandemic had a serious impact on the everyday life of children and young people through measures such as lockdowns and temporary curfews. In Germany, as in many other countries around the world, young people who were normally

**Citation:** Ludwig, O.; Dindorf, C.; Schuh, T.; Haab, T.; Marchetti, J.; Fröhlich, M. Effects of Feedback-Supported Online Training during the Coronavirus Lockdown on Posture in Children and Adolescents. *J. Funct. Morphol. Kinesiol.* **2022**, *7*, 88. https://doi.org/10.3390/jfmk7040088

Academic Editor: Peter Hofmann

Received: 26 September 2022 Accepted: 13 October 2022 Published: 14 October 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

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active in sports were cut off from outdoor exercise and sports activities in clubs for several months. While physical activity time thus decreased significantly, time in front of the computer increased—as a leisure activity, but also because school lessons were largely held online. This promoted physical inactivity among many adolescents in Germany and worldwide for weeks, with sometimes drastic effects on daily physical activity time. For example, Schmidt et al. showed that in Germany, among 14–17-year-old boys, physical activity decreased by an average of 21 min per day during Corona, while time spent in front of the screen relaxing increased by 79 min per day [11]. A survey of over 6400 children and adolescents in France by Chambonniere et al. also showed that 57% of teenagers significantly decreased their physical activity during Corona, which was particularly evident in adolescents who were previously more active in sports [12]. Guan and colleagues found the same trend in Canadian adolescents, namely, in addition to a decrease in physical activity time, a 66% increase in time spent watching television and a 35% increase in time spent playing video games [13].

It is well known that there is a strong association between health outcomes and physical activity behavior. Guan et al. therefore concluded that the health of children and adolescents may have been compromised due to a lack of physical activity during the Corona pandemic [13].

Negative effects of sitting on altered muscular activity and misalignments of the head and neck have been demonstrated. For example, Caneiro et al. found the typical postural deficiencies in the form of increased neck flexion and increased anterior translation of the head as a result of a slump sitting position, which led to an unfavorable increase in the activity of the postural muscles in the neck region [14], while Ertekin and Günaydin demonstrated a change in muscle activity and stiffness of the trapezius muscle associated with protracted shoulders [15].

Many of these muscularly induced misalignments are associated with neck pain. For example, Ruivo et al. observed protracted head in 68% of the subjects and protracted shoulders in 58% of the subjects in studies of 275 adolescents, and forward head posture was significantly associated with neck pain [16].

According to current scientific knowledge, an important starting point in the prevention of shoulder and neck pain is the strengthening of the stabilizing musculature [17]. Targeted sports activities can contribute to this.

One approach during the pandemic time, which was physically and psychologically stressful for children and adolescents, was sports activities carried out online in groups. This is where the present study comes in. For adolescent soccer players at a DFB (German Football Association) youth academy, who normally trained together three to four times a week on the sports field, posture-specific sports training was offered online twice a week via the Zoom® platform during the lockdown phase. The typical postural weaknesses of this target group were known from previous own studies [8], so the training programme was adapted accordingly. As the online meetings took place live via smartphone or laptop cameras, the exercises could be individually corrected by trainers in real time for each participant.

Although some studies discuss the general use of digital tools and online training or effectiveness regarding improvements in overall activity levels during the coronavirus pandemic, there is insufficient research on the effectiveness of online training on body posture. Tjønndal was able to show that the use of online tools during the corona pandemic was quite uncoordinated and that synchronized (live-streamed) training was offered rather rarely [18]. On the other hand, when Parker et al. surveyed 963 adolescents, they found that the willingness to use digital platforms to support and guide physical activity was present in 26.5% of the surveyed adolescents [19]. These are initially good conditions, especially since 95–96% of 13–18-year-olds in Germany had their own smartphone at the end of 2021 [20].

However, there is very little research on the use and effectiveness of synchronized (live streamed) online training, particularly for posture correction and especially when participants received live feedback. Given the potential and benefits in situations where face-to-face training cannot take place, there is a clear need for research. Therefore, the aim of the study was to examine whether a six-week, feedback-supported online training programme could improve posture parameters in children and adolescents.

#### **2. Materials and Methods**

The online training intervention took place during the second "hard" coronavirus lockdown in Germany, which came into effect on 16 December 2020 and lasted for six weeks.

#### *2.1. Subjects*

A total of 96 adolescents from the U14 (age 13–14 years) to U19 (age 17–19 years) youth teams of the DFB youth academy of the SV 07 Elversberg soccer club (Germany) participated in the training intervention (Zoom group). Participation was voluntary and was advertised via the club. The data of 86 participants of the Zoom group were used for final analysis (anthropometric data in Table 1); data of ten subjects had to be removed because regular participation was not possible (due to poor internet connection or illness) or the follow-up appointment was missed.

**Table 1.** Anthropometric data of the subjects.

Since, for ethical reasons, we could not deprive young soccer players of the club of participating in online training during the coronavirus lockdown, no non-training control group could run in parallel. We therefore selected an age-matched control group of 84 adolescent soccer players post hoc, who were examined twice at intervals of eight weeks and only took part in regular soccer training or had a training break in between.

All participants or their legal representatives were fully informed beforehand and gave their written informed consent to participate in the postural analyses and to take part in the video conferences. The study was conducted in accordance with the Declaration of Helsinki and approved by the local University Ethics Committee (ref. nr. 6-18).

#### *2.2. Posture Analysis*

Before the start of the study, a posture analysis was carried out on all participants on the premises of the association. Due to the contact restrictions, an exemption was obtained from the responsible municipal regulatory authority. In view of the current infection situation, appropriate corona precaution measures were followed strictly.

During the analysis, the subjects were first weighed in their underwear, and their height was determined (SECA stadiometer). The following anatomical landmarks were marked with marker dots or marker balls (diameter 12 mm): malleolus lateralis, greater trochanter, acromion, spinous process of the 7th cervical vertebra (C7), spinous process of the 1st sacral vertebra (S1), anterior superior iliac spine (ASIS), and posterior superior iliac spine (PSIS). The subjects then placed themselves in front of a measuring wall and assumed a relaxed posture (arms hanging loosely, looking straight ahead, breathing normally). A posture photo was taken using a camera (Logitech webcam, Full HD) mounted on a tripod at hip height. The inclination of the sacrum was then determined in degrees by placing an electronic inclinometer (Neoteck NTK033) on the proximal part of the sacrum.

Using analysis software (Dartfish ProSuite 6, Dartfish, Fribourg, Switzerland), the following posture parameters were determined (Figure 1): horizontal distances of the ear, shoulder (acromion), and hip (major trochanter) perpendicularly through the lateral malleolus as a percentage of body height; pelvic tilt (angle between the connecting the

PSIS–ASIS line to the horizontal); and trunk forward tilt (angle between the connecting the S1–C7 line to the vertical).

**Figure 1.** Analyzed posture parameters; ASIS = anterior superior iliac spine, PSIS = posterior superior iliac spine, C7 = 7th cervical vertebrae, S1 = 1st sacral vertebrae.

Posture assessment using analysis of angles and distances from posture photographs is a scientifically well-studied, reliable and valid procedure [21,22].

#### *2.3. Intervention*

To implement the intervention, a temporary film studio was set up in the club's athletics hall, from which the training exercises were broadcast live twice a week via the Zoom® (Zoom Video Communications Inc., San José, CA, USA) communications platform. One trainer performed the exercises at the designated pace, while a second trainer commented on the execution of the exercises and announced the number of repetitions and rest times. The participants had previously been asked to point their smartphone or laptop camera so that they were clearly visible in the front or side profile. Two other trainers switched from participant to participant via video during the exercise session and controlled and, where necessary, verbally corrected the execution of the exercise until the participant executed it correctly (Figure 2). The participants were divided into a total of three subgroups of 30–35 adolescents, who took part in the online training at different times to ensure sufficient monitoring by the trainers. The first two sessions were necessary to learn how to perform the exercises correctly.

From the postural examinations (pre-test), it was known that there were deficits especially in the head and shoulder area (protracted shoulder girdle, head protrusion), as well as in the pelvic area (Table 2). Therefore, the exercises were chosen to meet the following criteria:

**Figure 2.** Exemplary online view that the participants (**a**) and the correcting trainers (**b**) had during the exercise sessions. In the photo on the right, the background has been changed for data protection reasons. The persons depicted have given their written consent to the publication of the photos.

**Table 2.** Prevalence of postural deviations in the studied population (absolute N/prevalence).

To improve the position of the shoulder and head, particular emphasis was placed on strengthening the rhomboid, latissimus dorsi, rectus capitis, longus colli, longus capitis, and obliquus capitis muscles [23]. To correct the pelvic position in the sense of reducing the pelvic tilt, the rectus abdominis, gluteus maximus, and ischiocrural muscle groups were strengthened [24]. The exercises performed are described in Table 3.

**Table 3.** Description of the exercises and the targeted muscle groups.

**Table 3.** *Cont*.

The exercise sessions were performed twice a week in the afternoon, three days apart, and lasted about 45 min each. At the beginning, the participants completed an approximately five-minute warm-up programme consisting of running on the spot, jumping jacks, knee bends, and light stretching exercises for the trunk and leg muscles. This was followed by the eight exercises with 20 repetitions each (Table 3). This sequence was repeated a total of three times with short drinking breaks. The training was concluded with five minutes of stretching exercises for the trunk and legs and a check of the load intensity.

The exercises were demonstrated by a trainer in real time and, thus, the number of repetitions, load, and rest times were specified. An adjustment to the individual performance level of the participants was made through the choice of weights (e.g., water bottles of different sizes), the height of the obstacles (for the "swimmer" exercise), and the tension of the resistance band (e.g., for rowing exercises). In the first week of training, the correct

execution of the movement was trained and the weights were adjusted so that the number of repetitions could be carried out. After each training session, the participants were asked to rate the training load on a ten-point Likert scale via chat. The target range was set at 6–8; if the target was exceeded or not reached, the resistance and weights were varied individually in consultation with the participants. After seven training sessions, either the weights or the number of repetitions (now 30) was increased. This was maintained until the 12th training session.

#### *2.4. Statistics*

Outliers at the time of the pre-tests were checked again in the posture photos. As these were not measurement errors but actual extreme values in the range of the posture parameters, they were not removed.

Due to presence of outliers, as well as partial inhomogeneity of the covariance according to Box's test (*p* < 0.01), assumptions could not be met for the calculation of a commonly used mixed ANOVA. Therefore, a robust mixed ANOVA using trimmed means was applied for statistical analysis of the interaction effects of the groups and measuring points in time using the R package WRS2 [25]. Further post hoc statistical analysis was performed using IBS SPSS Statistics (version 16, SPSS Inc., Chicago, IL, USA). Visualizations were performed using the Python library "Seaborn" [26].

#### **3. Results**

Table 4 shows the development of the posture parameters in the training and control groups, while Figure 3 shows the distribution and development of the parameters over time.

#### *3.1. Interaction Effects*

There was a statistically significant interaction between time and group for head protrusion (F(1, 93.75) = 51.92, *p* < 0.001, partial η2 = 0.36), for shoulder protrusion (F(1, 93.85) = 23.62, *p* < 0.001, partial η2 = 0.20), and for hip anteversion (F(1, 100.99) = 7.07, *p* = 0.009, partial η2 = 0.07).

We found a statistically significant interaction between time and group for trunk tilt (F(1, 96.03) = 40.65, *p* < 0.001, partial η2 = 0.30).

For pelvic tilt, we found no statistically significant interaction between time and group (F(1, 99.43) = 1.93, *p* = 0.168). Further, no main effects for time (F(1, 92.49) = 0.15, *p* = 0.695) or group (F(1, 99.43) = 0.48, *p* = 0.492) could be found.

There was no statistically significant interaction between time and group for sacral angle (F(1, 100.99) = 2.44, *p* < 0.001). There were, however, main effects for time (F(1, 97.96) = 28.64, *p* < 0.001, partial η2 = 0.23) and group (F(1, 100.99) = 48.94, *p* < 0.001, partial η2 = 0.33).

#### *3.2. Main Effects of "Between-Subject Factors" (Group)*

The control and training groups did not differ significantly at the pre-test on the variables head protrusion, shoulder protrusion, hip anteversion, and pelvic tilt (*p* > 0.05), but there were differences in trunk tilt and sacral angle (*p* < 0.05). At the post-test, the training and control groups differed significantly (*p* < 0.05) in all the variables except pelvic tilt (*p* > 0.05).

#### *3.3. Main Effects of "Within-Subject Factors" (Time)*

For the training group, there was a significant change between the pre- and post-tests for all parameters (*p* < 0.05), except for pelvic tilt. For the control group, there was no difference between the measurement times (*p* > 0.05), except for the variables sacral angle and trunk tilt (*p* < 0.05).

**Table 4.** Development of the posture parameters over time (mean ± standard deviation).

% BH = percentage of body height.

**Figure 3.** Violin plots of the development of the posture parameters of the training group (ZOOM) and the control group (CON). The horizontal lines mark the median, \* = significant difference (*p* < 0.05).

#### **4. Discussion**

The coronavirus pandemic brought drastic changes to the everyday lives of many people, especially during the phases of lockdown, with contact restrictions and massive reductions in social and sporting life. Children and adolescents were particularly affected [11]. The subjects of our study were young soccer players in the junior performance sector who previously trained three to four times a week for 90 min or more with an additional game at the weekend. During the phases of the second hard lockdown, which lasted from mid-December 2020 to May 2021 in Germany, club life was largely switched off. Training sessions conducted at home and accompanied online were therefore the only guided sporting activity for many young people and, at the same time, one of the few opportunities to maintain social contacts within the team.

The present study was able to show that significant improvements in posture could be brought about by the six-week online training programme. To substantiate the study results, the changes in posture parameters during the six weeks of training were compared post hoc with the posture development of a roughly identically composed group of young competitive soccer players in regular sporting activity after the coronavirus lockdown phase. Although a control group running at the same time would have been scientifically optimal, it could not be realised at the time the study was conducted for ethical reasons, as we did not want to deny any young person participation in the exercise programme during the lockdown. The absence of systematic differences between both groups, and, therefore, the potential suitability, is also indicated by the mostly non-significant differences for the pre-test condition.

The reduction in the perpendicular distances of the ear, the shoulder, and the hip show that an improvement in posture in the sense of a less forward-leaning position could be achieved, presumably through the training-related strengthening of the dorsal muscle chain. Figure 4 shows a typical example of the change in a participant's habitual posture over the course of the study. It is known that deviations of the head and trunk from the perpendicular can be associated with pain in the neck and back [27]. The violin plots in Figure 4 provide information about the distribution of these parameters and show that there was no normal distribution in the pre-tests, but rather a skewed distribution in the direction of the perpendicular. Minimum perpendicular distances are considered biomechanically optimal.

As a measure against protracted head, the longus colli, obliquus capitis, and longus capitis muscles were strengthened via Exercises 1 and 8 (Table 3). For retraction of the shoulders, it was additionally and synergistically important to strengthen the rhomboid, latissimus dorsi, and trapezius muscles, which were activated in Exercises 1, 2, and 5. This is consistent with the findings of Ruivo et al. [28], who were able to improve head and shoulder position in adolescents through a 16-week strength and stretching programme, and also with the work of Sheikhhoseini et al. [29], who were able to demonstrate the effect of appropriate interventions on head position.

Even though the training group and the control group differed in the parameter trunk tilt at the time of the pre-test, an improvement was observed in the training group in the post-test, but with even a deterioration in the control group. To reduce trunk tilt, the dorsal muscle chain (especially the gluteus maximus, erector spinae, and biceps femoris muscles) had to be strengthened (Exercises 5, 6, 7 in Table 3). The work of Dolphens et al. [5,30] showed that a forward-leaning posture in adolescence is an important predictor of back pain in the following years.

In the area of pelvic alignment, we could not find any significant improvements in the intervention group. A lifting of the anterior pelvic edge (reduction in the pelvic tilt and decrease in the sacral angle) would be associated with a reduction in lumbar lordosis after a new muscular balance between the inserting muscle groups has been established [7]. Strengthening the muscles that straighten the pelvis (especially the rectus abdominis, gluteus maximus, and hamstrings) would have been responsible for this. The training programme specifically included exercises for this purpose (1, 3, 4, 6, 7; Table 3). The fact

that the training intervention did not bring about any improvement in this area could be related to the fact that a change in the pelvic position in the resting posture can presumably be brought about less through an increase in the strength of the muscles involved and more through an improvement in the proprioceptive perception of the pelvic position [24,31]. However, proprioceptive exercises were not part of the training programme. Furthermore, it cannot be ruled out that the training stimuli on the muscle groups mentioned were too low.

**Figure 4.** Typical example of the change in a participant's habitual posture (**a**: pre-test; **b**: post-test).

The control group did not show any improvement in the posture parameters (except for the sacral angle, which also decreased in the training group), so we assume that the online training was causally responsible for the improvement in the training group. This seems relevant to us insofar as the positive effects of targeted strength training on posture, which have already been proven in other studies [24,32–34], could also be achieved via online feedback training.

We see a significant aspect that contributed to the success and motivation of the participants in the feedback we were able to give in real time via video. It has been shown that in this way, frequent mistakes could be corrected, which otherwise would probably have led to a lower training success. At the same time, this kind of contact was an important psychological factor for many young people, as they reported afterwards. Praise and motivational announcements helped many participants to persevere through the strenuous training sessions and to maintain their bond with the team during the coronavirus period. From a scientific point of view, the lockdown situation naturally also had the advantage that (apart from individual sport at home) there were few outside influences in sporting terms, i.e., there was almost a "laboratory situation".

We see online feedback as a great opportunity for internet training, which is clearly superior to traditional training videos that are available in large numbers via social media and platforms such as YouTube® but offer no feedback option [18].

Our study has several limitations. As already mentioned, the intervention and control groups could not run in parallel. Nevertheless, the control group was composed as homogeneously as possible to the training group, even though they underwent regular sports training. However, since posture-relevant exercises were not part of their soccer training, we can exclude strong influencing effects here. It must also be emphasised that, apart from the load control, the training programme could not be individually adapted. Participants without postural deficits also performed the same exercises, so that a smaller effect of the intervention could be assumed here, which, in the end, rather led to an underestimation of the training effect. Nevertheless, training the postural muscles is important and makes sense in these cases as well, since many of the trained muscle groups also play a major role in movement stabilisation in soccer. In the selection of exercises, the choice of tools was limited to those available to the participants at home (water bottles as a substitute for dumbbells, exercise balls, resistance bands, broomsticks). Even though the adolescents had the specification not to do any additional training at home, this was not a factor that could be realistically controlled, but would not diminish the basic statement.

Our study was limited to performance-oriented youth soccer players. Nevertheless, we assume that the approach of feedback-supported training could also be successful for other youth target groups.

#### **5. Conclusions**

In the context of our study, it has been shown that it is possible to provide individual exercise supervision and correction for participants during online posture training. Feedback-based online training with two 45 min sessions per week can improve postural parameters in adolescent soccer players over a period of six weeks.

**Author Contributions:** Conceptualization, O.L., T.H., J.M. and T.S.; methodology, O.L.; software, C.D., T.H.; formal analysis, J.M., C.D. and O.L.; investigation, O.L., T.S. and J.M.; writing—original draft preparation, O.L., M.F. and C.D.; writing—review and editing, O.L., C.D. and M.F.; visualization, C.D and O.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee (ref. nr. 6-18).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the subjects to publish this paper.

**Data Availability Statement:** The data is available for qualified requests.

**Acknowledgments:** The authors would like to thank Lena Reiter and Sebastian Eberle for conducting the exercises, Jonas Dully for his help in preparing the study and Diana Mergen for her assistance in analysing the posture photos.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **The Impact of Nordic Walking Pole Length on Gait Kinematic Parameters**

**Luca Russo 1,\*, Guido Belli 2, Andrea Di Blasio 3, Elena Lupu 4, Alin Larion 5, Francesco Fischetti 6, Eleonora Montagnani 7, Pierfrancesco Di Biase Arrivabene 8 and Marco De Angelis 8**

**Abstract:** Nordic walking (NW) is a popular physical activity used to manage chronic diseases and maintain overall health and fitness status. This study aimed to compare NW to ordinary walking (W) with regard to pole length and to identify kinematic differences associated with different poles' length (55%, 65% and 75% of the subject's height, respectively). Twelve male volunteers (21.1 ± 0.7 years; 1.74 ± 0.05 m; 68.9 ± 6.1 kg) were tested in four conditions (W, NW55, NW65 and NW75) at three different speeds (4-5-6 km∗h−1). Each subject performed a total of twelve tests in a random order. Three-dimensional kinematics of upper and lower body were measured for both W and NW, while oxygen consumption levels (VO2) and rating of perceived exertion (RPE) were measured only for NW trials with different poles' length. NW showed a higher step length, lower elbow motion and higher trunk motion (*p* < 0.05) compared to W. Additionally, NW65 did not show any kinematic or RPE differences compared to NW55 and NW75. Only NW75 showed a higher elbow joint (*p* < 0.05) and lower pole (*p* < 0.05) range of motion compared to NW55 and a higher VO2 (*p* < 0.05) compared to NW55 and NW65 at 6 km∗h−1. In conclusion, the use of the poles affects the motion of the upper and lower body during gait. Poles with shorter or longer length do not produce particular changes in NW kinematics. However, increasing the length of the pole can be a smart variation in NW to increase exercise metabolic demand without significantly affecting the kinematics and the RPE.

**Keywords:** Nordic walking; walking; 3D kinematics; biomechanics; gait analysis

#### **1. Introduction**

Walking with poles in an urban or natural environment is commonly known as Nordic walking (NW), defined as an outdoor non-competitive fitness activity in which the practitioners perform brisk walking with specially designed poles, similar to those for cross country skiing, engaging also the upper body [1–3]. NW is widely and successfully applied in the management of several not-transmissible chronic diseases, such as diabetes, cancer, hypertension, obesity [4–9] or in case of joints diseases [10,11] or for general health maintaining purpose [12,13].

Over an approximate period of 25 years, NW has received great attention by researchers. The main attractive feature of NW, as a fitness activity, is the suggestion from the literature about a higher request in terms of energy expenditure with respect to ordinary walking (W). The average rate of oxygen uptake (VO2) is reported to be significantly higher

**Citation:** Russo, L.; Belli, G.; Di Blasio, A.; Lupu, E.; Larion, A.; Fischetti, F.; Montagnani, E.; Di Biase Arrivabene, P.; De Angelis, M. The Impact of Nordic Walking Pole Length on Gait Kinematic Parameters. *J. Funct. Morphol. Kinesiol.* **2023**, *8*, 50. https://doi.org/10.3390/jfmk8020050

Academic Editor: Luca Petrigna

Received: 30 March 2023 Revised: 17 April 2023 Accepted: 23 April 2023 Published: 26 April 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

in NW with respect to W at the same speed [3,14–21], without any increase in the rate of perceived exertion [14,17,19–21]. These results reinforce the practice of NW as an activity for weight loss and maintaining an optimal health status.

From a biomechanical point of view, NW is often compared to W with the aim to understand if the use of the poles could affect the joint load. For this reason, the lower limbs are mainly investigated [22], in particular the knee joint, obtaining, however, controversial results [2,23–26] due to the different tested samples in which not always the knee joint load was reduced in NW with respect to W. The upper body is mainly studied in terms of muscular activation patterns [27]. Some studies suggest that NW can lead to increased shoulder mobility and reduced tenderness in the shoulder girdle [28], as well as decreased neck and shoulder pain [29]. In general, NW increases the walking distance and speed, as well as the stride length, decreasing the cadence [30]. Moreover, NW increases the muscle activation and the strength of upper limbs, as well as the upper and lower range of motion and the ground reaction force [30].

According to the actual literature state of art, NW is deeply investigated but less attention is given to the main element that differentiates NW from W: the pole. In NW, the poles are investigated most of all for the force transmission profile [31,32] and it is well-known that properly pushing the pole on the ground allows to increase the NW metabolic benefits. Not by chance, there is a difference in the applied force on the ground between NW instructors and recreational individuals [32]. Despite that, at present, few information is available about the poles' length and how this parameter can affect the body kinematics. Usually, the NW poles are set approximately at 2/3 of the subject's height (height of the subject in centimeters∗0.68) [23,32,33], but it is common to use them based on comfort perception. For this reason, it is important to understand the number of kinematic modifications that different pole lengths could induce. From a metabolic perspective, some results are available about both different weight and length of the poles. About weight, no differences were measured comparing NW with heavier (adding 0.5; 1 and 1.5 kg to the pole) or standard poles on metabolic data, therefore there is no suggestion to use heavier poles to increase the metabolic demand [34]. About length, poles lengths which are self-selected caused greater energy expenditure than shorter poles only in uphill walking but not on level walking [3]. No information is present about using longer poles and no information is available about the kinematics of NW with different poles' length. Moreover, the increased metabolic demand of NW compared to W is well-known, but less is known about the relationships between kinematics and VO2 consumption during NW exercise.

It is reasonable to hypothesize that modifying the length of NW poles could affect gait kinematics, as well as perceived fatigue and metabolic demand during exercise. Modifying the poles' length could lead to using the upper limbs in a different way to properly manage the pole, and this modification could affect the motion of the spine and lower limbs. Thus, this study aimed to (1) characterize the kinematics of NW compared to regular walking, with a focus on upper body motion and (2) examine the effects of different pole lengths on kinematics, metabolic demand and perceived fatigue during NW exercise. The primary practical goal of this research is to provide evidence-based recommendations for practitioners and instructors involved in NW training.

#### **2. Materials and Methods**

#### *2.1. Design and Participants*

This is a cross-sectional study design with a random crossover approach. Participants were recruited as part of the undergraduate program of Sport Science at the University of L'Aquila. The participation was on a voluntary base and the specific criteria of selection included: no history of musculoskeletal or neurological pain in the last 6 months and to be physically active. Participants never practiced NW. This was required as we wanted to resemble as close as possible the activity of recreational and novice NW practitioners; expert participants would have displayed different walking techniques and styles, biasing the results. Due to the inexperience of the participants, they attended three preliminary

weeks of supervised training with a NW instructor, to avoid a learning effect during the study as Figard-Fabre et al. found [21]. The instructor taught the basic technique (diagonal technique) according to the INWA guidelines [35]. Diagonal technique can be briefly described as technique that seeks a position of the trunk inclined forward, with long strides and active use of the arms without any limitation of flexion or extension [36]. Practices were performed using a treadmill, at the same time of the day, 3 sessions/week, 1 h/session.

A total amount of 20 male participants were recruited but only 12 completed the experiment (mean ± SD: 21.1 ± 0.7 years; 1.74 ± 0.05 m; 68.9 ± 6.1 kg; 22.7 ± 1.6 BMI; 12.8 ± 2.7% body fat). A power analysis of the sample was conducted, and 12 subjects were sufficient to satisfy a power at 80% and an error probability at 5%. During the recruiting phase and prior to the training phase, all participants were informed and gave voluntary consent to participate in the study, and privacy criteria were meet. The study was approved by the Ovidius University of Constanta Nr. 141 din 21 February 2023 in accordance with the Declaration of Helsinki.

#### *2.2. Instrumentation*

The NW pole used was customized with a telescopic pole (Skitrab, Bormio, Italy; 210 g of mass each) connected with a grip and a tip specific for NW (Swix, Lillehammer, Norway). The choice to use a telescopic pole allowed to modify the length but not the weight of the pole for each trial.

Kinematic data were collected using a 4 infrared 3-dimensional camera SMART integrated System working at a sample rate of 60 Hz (BTS Bioengineering, Garbagnate Milanese, Italy.

Metabolic data were collected using a portable metabolimeter K4b2 (Cosmed, Roma, Italy), calibrated before each test session.

All the tests were performed on a Cosmed T170 treadmill (Cosmed, Roma, Italy), adapted by taking out frontal and lateral handlebars to allow participants to perform the typical NW gesture without hitting the structure. The treadmill was calibrated according to the literature [37] before the beginning of the experimental procedures.

The Figure 1 resumes the used instrumentation.

**Figure 1.** Schematic representation of the experimental setting. 1—Nordic walking pole. 2—3D kinematic integrated system; 2a—Infrared camera; 2b—Reflective marker; 2c—Workstation. 3—Metabolimeter. 4—Treadmill and workstation for treadmill management.

#### *2.3. Procedure and Data Collection*

Testing procedures were carried out in a Sport Performance Laboratory at a mean temperature of 19 ◦C and a mean relative humidity of 51%, and each subject was tested at the same time of the day, avoiding any circadian effect [38–40]. The first day of the training period, all participants were tested for anthropometric measures aiming to find out the three different poles' length: classical, reduced and increased length 65%, 55% and 75% of the participant's height, respectively. The supervised training period was performed with classical length poles (65% of subject's height) as well as longer and shorter poles in a random order. The last day of training, each individual received a personalized random sequence of the test conditions.

Each participant performed a total amount of 12 tests. The experimental procedure had 4 conditions, each condition was tested during a single day and each test day was separated by 7 days or rest. The test conditions were: ordinary walking (W) and NW with poles at different lengths (65%, 55%, 75% of the subject's height defined as NW65, NW55, NW75). The length of the pole was measured from the insertion of the lace in the handle to the tip final extremity (Figure 2). Each condition was tested at 3 different fixed speeds 4-5-6 km∗h−1 [41] and no slope was applied to the treadmill. Conditions were randomly assigned while speeds were always administered from the slowest to the faster one. Each trial lasted 10 min and a resting period of 20 min was observed between each trial test. Table 1 resumes a real example of randomized sequence for one single participant. During tests, kinematic data, rating of perceived exertion (RPE) and oxygen consumption (VO2) were collected.

**Figure 2.** Landmarks for measurement of NW pole's length, from left to right: insertion of the lace in the handle and tip final extremity.

**Table 1.** Real tests sequence of a participant. The sequence of the conditions was randomly assigned while the speeds were always administered from the slowest to the faster one (4-5-6 km∗h−1). Each trial, represented as an "X", lasted 10 min and a resting period of 20 min was observed between each trial test.

W—Walking. NW55—Nordic walking with pole length adjusted at 55% of subject's height. NW65—Nordic walking with pole length adjusted at 65% of subject's height. NW75—Nordic walking with pole length adjusted at 75% of subject's height.

#### 2.3.1. Kinematic Data

Kinematic analysis was conducted using a model of 18 body reflective markers (Figure 3), positioned on the most used body landmarks according to other studies about NW or motion analysis [2,23,25,26,42–47].

**Figure 3.** Position of the reflective markers. (**A**)—Kinematic used model for the automatic recognition of the body landmarks. (**B**)—Detailed description of the position for each reflective marker on body landmarks.

The last two minutes of each trial were taken into account for the kinematic analysis, aiming to reduce the stride variability [48]. Smoothing procedures and missing frames were managed through the SMART Analyzer software (BTS Bioengineering, Garbagnate Milanese—Italy). Once the raw kinematic data were processed, a ratio between the step length and the elbow horizontal displacement was also calculated (SL/EHD ratio), with the aim to understand if the use of the poles addressed some changes in the upper limbs motion in NW with respect to W. All the kinematic data were measured on the right side of each subject in order to standardize the process. Table 2 resumes and describes the kinematic parameters acquired for each test.

**Table 2.** Detailed description of each parameter measured with kinematic analysis.

Measures for elbows, feet and poles were taken all on the right side for the entire sample. Note: all the data are expressed as an average value of all gait cycles.

#### 2.3.2. Fatigue and Metabolic Data

VO2 was measured using a wearable metabolimeter during the whole duration of each test and the last seven minutes were taken into account for the metabolic analysis. The evaluation of the average oxygen consumption of each NW trial was used to look for correlations between kinematics and metabolic demand in NW exercise. Due to the wellknown metabolic difference between NW and W [3,14–21], VO2 consumption during W was not considered in this study. Anyway, the metabolimeter was worn as well even during W trials in order to avoid perceived comfort difference with respect to NW. Immediately after each trial, the participants indicated their rating of perceived exertion using the category rating-10 (CR-10) scale modified by Foster et al. [49].

#### *2.4. Statistical Analysis*

All data were tested with the Shapiro–Wilk's test for normality. As data were normally distributed, parametric inferences were used for the analysis. Kinematic differences between NW65 and W were tested using the Student paired *t*-test, while to measure kinematics differences in NW with different poles' height, an ANOVA design for repeated measures with Sidak correction was used. Finally, the Pearson correlation coefficient was used to look for a correlation between kinematic and metabolic data. The significant level was set at *p* = 0.05 and the data were analyzed using SPSS (SPSS Inc., Chicago, IL, USA).

#### **3. Results**

#### *3.1. Kinematic Differecences between NW65 and W*

According to statistical analysis, kinematic data in NW65 showed significant differences with respect to W, for all the three tested speeds. Most of the significant differences involved the upper body segments (Table 3).

**Table 3.** Differences between NW65 and W for kinematics.

W—walking. NW65—Nordic walking with pole length adjusted at 65% of subject's height. SL/EHD ratio—ratio between the step length and the elbow horizontal displacement. \* significant difference between NW and W.

The use of the poles significantly increased both the C7 and the S1 vertical displacement for all speeds; even the elbow horizontal displacement and the elbow advancing speed resulted significantly lower in NW compared to W, while the step length was higher in NW in comparison with W for all tested speeds.

#### *3.2. Kinematic Differecences between NW with Different Poles' Length*

A limited number of significant differences were found for kinematics between NW with different poles' length (Figure 4). For all the three tested speeds, no differences were measured between NW65 and NW75, while only one significant difference was measured at 6 km∗h−1 between NW55 and NW65 for the pole Δ slope (31.7 ± 2.6◦ and 28.0 ± 3.2◦, respectively, *p* = 0.013). Significant differences were measured between the shorter and the longer poles' length, NW55 and NW75, particularly on the elbow and poles kinematics. At 4 km∗h−1, three significant differences were measured between NW55 and NW75: (1) pole

minimum slope (14.5 ± 6.6◦ and 25.7 ± 10.7◦, respectively, *p* = 0.013); (2) pole maximum slope (41.8 ± 4.4◦ and 49.5 ± 4.0◦, respectively, *p* = 0.028); (3) pole Δ slope (27.3 ± 3.2◦ and 23.4 ± 2.5◦, respectively, *p* = 0.010). At 5 km∗h−1, four significant differences were measured between NW55 and NW75: (1) elbow Δ angle (30.7 ± 6.5◦ and 41.9 ± 13.3◦, respectively, *p* = 0.027); (2) pole minimum slope (13.5 ± 5.5◦ and 27.4 ± 9.0◦, respectively, *p* = 0.000); (3) pole maximum slope (42.9 ± 4.0◦ and 51.1 ± 7.1◦, respectively, *p* = 0.001); (4) pole Δ slope (29.4 ± 2.7◦ and 24.7 ± 2.8◦, respectively, *p* = 0.003). Finally, at 6 km∗h−1, four significant differences were measured between NW55 and NW75: (1) elbow Δ angle (31.7 ± 7.1◦ and 42.8 ± 12.0◦, respectively, *p* = 0.031); (2) pole minimum slope (13.7 ± 6.4◦ and 27.7 ± 7.0◦, respectively, *p* = 0.000); (3) pole maximum slope (45.5 ± 4.3◦ and 54.2 ± 5.3◦, respectively, *p* = 0.002); (4) pole Δ slope (31.7 ± 2.6◦ and 26.5 ± 3.0◦, respectively, *p* = 0.000). The results for all the data measured can be read in Appendix A.

**Figure 4.** Kinematic differences between NW using different poles' length. NW55—Nordic walking with pole length adjusted at 55% of subject's height. NW65—Nordic walking with pole length adjusted at 65% of subject's height. NW75—Nordic walking with pole length adjusted at 75% of subject's height. \* significant difference.

#### *3.3. Correlations between Metabolic Data and Kinematics in NW*

No differences were measured in RPE for NW with different poles' lengths at the same speed; while two significant differences were measured at 6 km∗h−1 between NW55 and NW75, as well as between NW65 and NW75 for VO2 (21.7 ± 1.7 mL∗kg−1∗min−1 and 24.1 ± 2.2 mL∗kg−1∗min−1, respectively, *p* = 0.002 and 22.2 ± 2.9 mL∗kg−1∗min−1 and 24.1 ± 2.2 mL∗kg−1∗min−1, respectively, *p* = 0.030) (Figure 5).

**Figure 5.** Fatigue perception and oxygen consumption differences between NW using different poles' length. RPE—Rating of perceived exertion. VO2—Oxygen consumption. NW55—Nordic walking with pole length adjusted at 55% of subject's height. NW65—Nordic walking with pole length adjusted at 65% of subject's height. NW75—Nordic walking with pole length adjusted at 75% of subject's height. \* significant difference.

Significant correlations were measured between metabolic data and kinematics in NW. In NW65 at 6 km∗h−1, the S1 vertical displacement significantly correlated with VO2 (r = 0.59 *p* = 0.043). In NW75 at 4, 5 and 6 km∗h−1, significant correlations were found between the spine forward slope and the VO2 (r = 0.71 *p* = 0.010; r = 0.69 *p* = 0.014; r = 0.71 *p* = 0.010, respectively, for each tested speed). In NW75, another two correlations were measured: one at 4 km∗h−1 between poles Δ slope and VO2 (r = 0.63 *p* = 0.027) and another one at 6 km∗h−1 between elbow Δ angle and VO2 (r = 0.61 *p* = 0.036). No significant correlations were found at any speed for NW55.

#### **4. Discussion**

This study aimed to characterize the kinematics of NW compared to W and to examine the effects of different pole lengths on kinematics, metabolic demand and perceived fatigue during NW. The study of the effect of different poles' length on gait kinematics is the main novelty of the investigation. Additionally, exploring the relationship between NW kinematics and exercise VO2 consumption could provide a new perspective on NW training and practice.

The main attention in NW from a biomechanical point of view is usually focused on lower limbs [22]. Conversely, the most interesting aspect of this investigation is the use of a 3D kinematic model for the study of the upper body segments. Finally, by utilizing a treadmill, we were able to maintain a constant speed throughout the tests, resulting in a more accurate comparison of the impact of various pole lengths on both kinematic and metabolic data.

#### *4.1. Kinematic Differecences between NW65 and W*

Significant differences in kinematics were found for all the tested speeds between NW65 and W. The use of the poles during walking seems to affect the gait kinematics both for the upper and lower body. The measured differences are significant but relatively small. This point can be considered delusive, but it should be considered that the NW is a physical activity that is performed for a long time during the training session, therefore it is logical to mind that even small differences can affect the final energy expenditure of the exercise.

The poles affect the vertical displacement of the two segments of the spine, C7 and S1, increasing the muscular work against gravity. In fact, in NW65, a moderate positive but significant correlation is present between the vertical displacement of S1 and the VO2. The use of the poles in NW not only allows a higher use of the upper limbs musculature [50] but engages all the trunk muscles [51–53], reflecting a higher vertical displacement of the whole spine.

With respect to the upper limb motion, particular attention was paid to the elbow. A significant difference for the angle displacement of the elbow was measured between NW and W only for the slower speed, 4 km∗h−1, in fact NW showed a higher angle displacement with respect to W. This difference disappeared when the gait speed increases, higher speeds showed a similar elbow angle. On the other hand, significant differences were observed between NW and W at all tested speeds, both in terms of elbow horizontal displacement and elbow advancing speed. In both cases, the NW values were smaller with respect to W, this can be addressed by the presence of the poles. It is reasonable to hypothesize that the pole's presence can affect the motion of the upper limbs both on the coordinative and on the kinematics profile, due to the necessity to push the pole against the ground [32]. It is well-known that the pole's weight does not affect the oxygen consumption, but only the muscle activation [34]; thus, the motion of the elbow is mainly affected by the pole's usage but not by its weight. The result of the present study cannot confirm at all this hypothesis but the presence of the positive significant correlation for NW75 between the elbow angle displacement and the VO2 can suggest that more research in this area is needed to clear this aspect.

For the lower body kinematics, NW showed a significantly higher step length with respect to W and this aspect could explain the advantages of NW for special populations, such as diabetic people [54,55]. To increase the step length results in engaging the ankle and hip motion much more, therefore this information can be relevant in all cases where higher ankle and hip motion is required: such as sedentary or pathological individuals [10,11,56]. The results of this research, about step length and step frequency, are consistent with previous studies [19,25] but with different absolute values. Willson et al. [25] observed an increase in step length up to 20 cm, whereas the difference observed in the present research is smaller (approximately 3 cm). However, it is important to note that there are methodological differences between the two experimental protocols as other researchers used self-selected and faster walking speeds compared to the present study. Therefore, it is

reasonable that the difference in step length could depend on the absolute different speed used for the tests.

Finally, as a direct consequence of the effect of the poles on the elbow motion and step length, even the SL/EHD ratio is significantly different between NW and W. The SL/EHD ratio is the mathematical ratio between the step length and the elbow horizontal displacement. It could be considered as a coordinative aspect of the gait. For all tested speeds, NW showed higher values of this ratio compared to W, because NW led to higher step length but smaller elbow horizontal displacement. This information confirms that the use of the poles can modify the gait spatiotemporal parameters.

#### *4.2. Characterization of NW with Different Poles' Length*

The second aim of this research was to examine the effects of different pole lengths on kinematics, metabolic demand and perceived fatigue during NW. Usually, the suggested length of the poles is set approximately at 2/3 of the subject's height [23,32,33]; thus, in this research, the poles were set at 55%, 65% and 75% of the subject's height. It would have been plausible to hypothesize that the use of shorter or longer poles could have influenced the spine inclination or the upper limb motion with respect to the classical length, but no statistical kinematic differences were measured between NW65 and NW55 or NW75 for all the tested speeds. No statistical differences were measured even for exercise RPE, suggesting that the length of the poles does not affect the perceived fatigue at any speed.

The use of different poles' length determined a limited number of significant differences both on the kinematic and metabolic profile: all the differences were related to the NW75 condition. In fact, NW75 showed a higher elbow angular displacement and a lower change of poles' slope with respect to the ground compared to NW55. The significant difference was present for all tested speeds. It is rationale to assume that the higher elbow angular displacement and the position of the pole constantly inclined with respect to the ground enable the participants to optimize the use of the pole during the pushing phase. The latter interpretation can be read in light of the significant increase of VO2 consumption at 6 km∗h−1 measured in NW75 compared to NW55 and NW65. These results are consistent with literature that suggests keeping the pole inclined for pushing optimization [21]. Therefore, the use of a longer pole can be beneficial for NW practitioners due to the increased metabolic demand without any effect on kinematics and exercise RPE compared to classical length. On the other hand, no reasons seem to be present for suggesting to reduce the length of the pole (NW55) in level walking, whereas it seems useful on uphill walking [3].

The absence of substantial significant kinematic differences between the different pole length conditions may seem odd, but it is important to consider that the sample for this research was deliberately chosen to have no previous experience. Although the participants underwent a training period before the tests, they were not as skilled as regular practitioners. Therefore, it is plausible to assume that the absence of specific NW coordination and technique allowed the participants to respond in a similar way to the different pole lengths. This perspective can be viewed positively when working with novice subjects, but this data cannot be applied to skilled practitioners without specific research.

Based on the research findings, NW instructors can opt for a different pole length compared to the traditional one when instructing novices. This is because it is widely known that the level of comfort does not vary between poles with different lengths [3]. Furthermore, novice practitioners may be advised by NW instructors to use a longer pole length (75% of the subject's height) if their objective is to increase metabolic demand during exercise without altering the kinematics of the movement and the exercise RPE. This recommendation may be particularly useful in the management of metabolic clinical conditions, such as overweight and obesity [55,57,58]. This practical application can be considered the main novelty of this research.

#### *4.3. Limitations*

The findings of this study are applicable solely to young male novice NW practitioners. It would be highly interesting to replicate the same experimental protocol using participants of different genders and ages. Additionally, this research did not provide any insights into the subject's adaptation or learning process during the training period, nor did it examine the comfort levels associated with the use of a specific pole during extended training sessions. Therefore, this study may be viewed as a preliminary exploration of the topic, and further research is warranted to enhance the practical information available to NW instructors.

#### **5. Conclusions**