*2.1. Concept Design*

We propose the design of ColorWatch, which is a wearable wrist-worn analog tactile device for people with visual impairments (PVI). The concept of ColorWatch design includes two disks that can be rotated independently: one marked square disk which is on top of and smaller in size than a round disk, which functions as an hour hand in analog watches while the marked round disk functions as a minutes hand. Both disks are marked at one position each, with markers pointing to the reference positions for time. These disks and marked pointers can be touched by PVIs to convey tactile information. In addition to conventional time checking, the function of ColorWatch extends to represent object colors by the tactile interface. An integrated color sensor or smartphone camera can be used to detect color information of a reference object, which can then be wirelessly communicated to the ColorWatch. Hybrid smartwatches available in the market already exhibit wireless communication and control capabilities along with traditional watch hands. The ColorWatch design proposed a square and a round disk instead of conventional arms to enable PVIs to interact with them without external protective glass and minimizing the risk of damage or heavy touch to conventional arms. The control circuitry in ColorWatch can then direct the watch disks to point to the corresponding position associated with the detected color and color tone. A maintained contact push toggle switch can be used to toggle between timepiece and ColorWatch mode. The ColorWatch tactile design is effective for drawing less attraction to PVI, and for not being disruptive to others in contrast to talking watches. The analog disk design of ColorWatch also makes it easy to read, less fragile, and less susceptible to damage in contrast to a traditional analog watch hands. Figure 2a displays the schematic configuration and perspective view of the ColorWatch design concept, with Figure 2b outlining an application scenario for the ColorWatch. More features can theoretically be added to the ColorWatch; such as smartphone call notifications, incoming call pick and drop, and alarms through haptic feedback. The push button and mechanical dial of the ColorWatch can also hypothetically function as a tactile input method for smartphone scrolling. In this setting, PVI can wirelessly navigate smartphone features through ColorWatch dials discrete rotation, select desired options through one or two buttons or ColorWatch, and get audio feedback through smartphone speakers. However, this study focuses on the automatic spatial color translation framework for the PVI.

(**a**)

**Figure 2.** Perspective view of ColorWatch design concept; (**a**) PVI use scenario of ColorWatch during shopping (**b**).

### *2.2. Proposed Color Selection and Tactile Representation Scheme*

The tactile association of color proposed in this study considers six distinct hues namely red (R), orange (O), yellow (Y), green (G), blue (B), and purple (P) from Goethe's color triangle. These hues are represented by the round disk of the prototype which dynamically points to the reference color. It can be seen from Figure 3 that complementary colors are arranged on opposite ends to each other, and mixing any two primary colors results in the secondary color between them. An emerged tactile dot of half-sphere on edge of the round disk resembling braille embossment is used as a pointer for tactile color marking. These tactile-color associations are further expanded by Munsell color systems's three dimensions of light (L), saturated (S), and dark (D) as a color tone of each monochromatic basic color or hue from Goethe's color triangle. The color tones are represented by the square disk of the ColorWatch design, where the emerged tactile dot at one corner points to the reference color tones, marked 90 degrees apart at 0, 90, and 180 degrees for L, S, and D, respectively. The remaining position at 270 degrees of square disk pointer is used to represent achromatic colors. When a reference to achromatic color is detected on the square disk, the round disk represents each of the achromatic colors given by White, Gainsboro, Light Gray, Dark Gray, Dim Gray, and Black (Table 1). The arrangement of these achromatic colors, and the six color-hues for monochromatic colors on round disk, depending on the color mode is provided in Table 2.

The analog clock dial design holds twelve marks separated by 30 degrees universally. These six markers for round disk and four markers for square disk can be incorporated on the analog clock design as the common factor of twelve markers. This association of perceptual colors and their tactile placement can be very convenient for learnability and ease of use of users and the user-centric design.

**Figure 3.** ColorWatch pattern for color hues and color tones. Blue and black text represents monochromatic and achromatic color modes, respectively.

**Table 1.** Colors tones or color mode according to the angle of the square disk.

**Table 2.** Round disk angle chroma-lightness levels for monochromatic and achromatic colors (0–180° and 270° on the square disk, respectively).


*2.1. Experimental Set up*

Cage experiments were carried out in the microbiology laboratory of the Department of Agricultural and Food Sciences, University of Bologna, in the period between October 2019 and June 2021. Newly emerged honey bees (*Apis mellifera ligustica* were obtained from multiple brood frames of emerging honey bees within the University of Bologna experimental apiary (San Lazzaro, Bologna, Italy, 210 m a.s.l.) in a continental climate. At least two independent laboratory cage tests were performed for each feed ingredient in order to validate results. The first set of assays, referred to as "First screening", was organized in order to study the effects of the feed ingredients on honey bee survival and parasite development. After this first screening, a second one, referred to as "Derived tests", was performed in order to confirm the obtained results or to test new hypotheses derived from the first one. Moreover, if the results showed a promising trend, even if not significant, the dosage of the active ingredient was increased, determining two different dosages for some of the ingredients [AA, NisA and GRA] marked as "low" (\_L) and "high" (\_H). Only para-coumaric acid and acetic acid were tested a third time using summer honey bees due to the contrasting results obtained in the two tests. All the tests were performed with the same protocol, having only differences in the season at which the newly emerged honey bees were obtaine. The ingredients assayed were chosen considering their known antimicrobial properties in both food and feed safety (organic acids and antibiotics), their immune stimulation properties (mainly plant extracts and microorganisms), but also basing the choice on traditional homemade remedies used by beekeepers (e.g., wine derivatives) that do not have a proper scientific basis. The selected compounds reported in Table 1 and are divided in four main groups: i. organic acids (acetic acid [AA], abscisic acid [ABA], p-coumaric acid [pCA]); ii. wine derivatives (ethanol [EtOH], sulphites [SUL], wine vinegar [WA]); iii. *Saccharomyces*and antibiotics (*Saccharomyces* sp. strain KIA1 [SC], a mixture of gramicidin A, B, C, and D [GRA], Nisine A [NisA]); iv. plant extracts (extract of *Opuntia ficusindica* [OPT], extract of brown alga *Padina pavonica* [PP], a mixture of manuka and tea tree oil [MT]). In all the tests, fumagillin [DCH] was used as positive control. Each assay had a dedicated control test, i.e., a group of infected bees not supplemented with any compounds in their diet [CTR]. Experimental cages had a dimension of 11 × 7 × 4 cm and were made using plastic, including a ventilation mesh. Three replicate cages, containing 50 newly emerged honey bees, were prepared for every dietary treatment and controls. Mortality in every replicate cage was registered on a daily basis, extracting the dead individuals after counting. Ten worker bees for each experimental condition were sacrificed at day 9 (experiment end) and the guts (midgut and rectum) were collected individually and stored at −20 °C until tissue analysis.

**Table 1.** Description of the different active ingredients tested in this work and its relative dose or concentration. a Dose recommended by the manufacturer. Final concentration of the ingredients are expressed as the amount of ingredient per mL of sugar syrup (1:1 *w*:*v*).


**4.1. Molecular imaging**

#### *Regenerative techniques – Stem cell technology and cellular tracking*

Advances in the biology of stem cells have evoked great interest in cell replacement therapies for the regeneration of heart tissue after myocardial infarction. Despite the initial controversial results from human trials [Rosenzweig 2006] due to the uncertain and unclear long-term fate, target-destination of the injected cells, their engraftment and viability, scientific interest and excitement remains high.

Employing high-resolution MRI in association with metabolism, iron-oxide labeled cells [Stuckey 2006] can be tracked and visualized thereby monitoring their migration patterns and ultimate engraftment fate in tissues of interest.


**4. Applications: From traditional to advanced materials**

After its first use in 1933 to deposit thoria particles on a platinum cathode for electron tube application, EPD was mainly utilized for traditional ceramic processing. Its industrial application was the deposition of clay or vitreous enamel coatings on metals, which after firing showed an evident improvement in the finishing properties of coatings with respect to conventional dipping or spraying processes.

In the last 20 years the interest shown by the academic and the industrial world regarding EPD has increased thanks to its wide range of applications, especially due to the insertion and diffusion of nanomaterials which allow to obtain structures with characteristics never conceived before.

A numbers of reviews reported extensively on the several applications of EPD as coatings and free standing objects, based on ceramics and metals (Sarkar & Nicholson, 1996; Van der Biest & Vandeperre, 1999; Boccaccini & Zhitomirsky, 2002; Boccaccini et al., 2003; Besra & Liu, 2007; Corni et al., 2008). Particularly successful is the use of EPD to produce porous, laminated and graded ceramic coatings (Hatton & Nicholson, 2001; Put et al, 2004; You et al, 2004) as well as fibres reinforced composites (Boccaccini et al., 1996,1997; Wang et al., 2000a; Freidrich et al., 2002; Kaya et al., 1999, 2000, 2001). Moreover, EPD has proven to be an effective method to texture superconductors structures, such as BSCCO and YBCO (Hang et al.,1995; Yau & Sorrell 1997; Grenci et al., 2006) and electrodes for solid oxide fuel cells (Zhitomirsky & Petric, 2000; Hosomi et al., 2007).

The aim of this review is to present more extensively those that are the current and most appealing applications for the most recent material science: biomaterials and nanomaterials.

Ceramic Coatings Obtained by Electrophoretic Deposition:

like nanosized HA crystal with the presence of body fluids.

bioactive material.

Fundamentals, Models, Post-Deposition Processes and Applications 59

components in EPD process. The presence of chitosan and alginate allowed to obtain coatings with improved strength with respect to the pure HA or Bioglass coatings.

Bioglass was successfully co-deposited with polyetheretherchetone (PEEK) by EPD (Boccaccini et al., 2006a) on Nitinol wires. PEEK is a semicrystalline thermoplastic polymer (Tm=340°C) with excellent performance also for biomedical applications. A suspension containing PEEK and Bioglass in ethanol was used for EPD co-deposition. Sintering was performed at 340°C for 20 min, just to melt the polymer and therefore to embed the ceramic particles. After sintering, the surface of coatings became smooth due to viscous flow of melted polymer. The PEEK/Bioglass coating deposited on Nitinol showed to be adherent to substrate also when it was bended. Moreover, the composite coating demonstrated to have two functions: to protect the NiTi substrate from corrosion when it was in contact with body fluids, and to improve the bonding of bone or soft tissue to an implant, being Bioglass a

Another example of application of composite coatings based on Bioglass concerns composites containing carbon nanotubes (Charlotte Schausten et al., 2010). The EPD parameters were optimised in order to obtain both co-deposition and sequential deposition of Bioglass particles and multi-walled CNTs on stainless steel substrates. Co-deposition produced homogenous and dense coatings with well-dispersed CNTs placed between the Bioglass particles. So, the network of CNTs acted as a reinforcement and contributed to the improvement of the mechanical stability of the coatings. The coatings obtained by sequential deposition formed a two-dimensional nanostructured mesh of CNTs on the Bioglass layer and produced a surface nanotopography, with a great potential in the formation of bone-

The combined use of Bioglass and CNTs is motivated also by recent results on differentiation of ostheoblast cells during their growth based on the substrate nanostructure. Moreover, as CNTs have a similar dimension to proteins, they demonstrated a high reactivity for interactions involved in the cell attachment mechanism. An interesting formation of CNTs/Bioglass composites by EPD was described by Boccaccini (Boccaccini et al., 2007) who referred to CNTs deposited on porous Bioglass-based scaffolds for bone tissue engineering. Concentrated CNTs suspensions (0.5-5 g/l) were used to create a deposit on interconnetted and macroporous structure of Bioglass, placed between two stainless steel electrodes. The final structure showed a scaffold with substantially unchanged porosity, with nanostructured pore walls. Moreover, the presence of CNTs conferred biosensing properties to the scaffold by adding an electrical conduction function, potentially useful for stimulation of cell growth and tissue regeneration by a physioelectrical signal transfer.

Alumina and ultrahigh molecular weight polyethylene (UHMWPE) are used as biomaterials for prostheses and joint replacement, but they do not bond with live bone. Coatings of bioactive ceramics can improve the osteoconductivity of these materials. Wollastonite (Yamaguchi et al., 2009) was used to form a composite bioactive material based on Alumina and UHMWPE. Wollastonite powder was prepared by calcination of silicon dioxide and calcium carbonate in an equimolar ratio. Substrates of porous alumina (10 µm average pore size) and porous UHMWPE (30 µm average pore size) were placed between two gold plates, acting as electrodes. After EPD, the subtractes were placed in simulated body fluid (SBF),

Moreover they did not obstruct the bioactive function of HA and Bioglass.


**1. Introduction**

266 Woven Fabrics

Sülar, V., Okur, A. (2008a). Objective Evaluation of Fabric Handle by Simple Measurement

Sülar, V., Okur, A. (2008b). Handle Evaluation of Men's Suitings Produced in Turkey, *Fibres & Textiles in Eastern Europe*, April/ June, Vol. 16, No. 2 (67), pp. 61-68 Thordike, G.H., Varley, L. (1961). Measurement of the Coefficient of Friction between Samples of the Same Cloth, *Journal of Textile Insitute*, Vol.52, pp. 255-271 Yazdi, A.A., Shahbazi , Z. (2006). Evaluation of the Bending Properties of Viscose/Polyester

Yazdi, A.A., Özçelik, G. (2007). The Effect of the Yarn Twist Directions on the Shearing

Yick**,** L. K., Cheng**,** K. P. S., & How**,** Y. L. (1995). Subjective and Objective Evaluation of Men`s

Wang, H., Mahar, T.J., Hall**,** R. (2011). Prediction of the Handle Characteristics of

 http://www.tandfonline.com/doi/abs/10.1080/00405000.2011.602230#preview Zeng, X.,Koehl, L. (2003). Representation of the Subjective Evaluation of the Fabric Hand

Woven Fabrics, *FIBRES & TEXTILES in Eastern Europe*, Vol. 14, No. 2 (56), pp. 50-54

Behavior of the Woven Fabrics, *3rd International Technical Textile Congress*, 1-2

Shirting, *International Journal of Clothing Science and Technology*, Vol. 7, No.4, pp. 17-29.

Lightweight Next-To-Skin Knitted Fabrics Using a Fabric Extraction Technique, *The*

Using Fuzzy Techniques, *Internatonal Journal of Intellgent Systems*, Vol. 18, pp. 355–

Methods, *Textile Research Journal*, Vol. 78: pp. 856-868

December

366 http://www.sdlatlas.com

*Journal of The Textile Institute*, web:

The textile industry is one of the most important and fastest developing industries in the world. An significant problem encountered by manufacturers is that of ensuring that the fabrics produced are of suitable quality and durability. Particular attention needs to be paid to the destructive action of microorganisms present in the environment.

In favourable conditions these can rapidly destroy material, rendering it entirely unusable and causing substantial economic losses.

In 1960, in the UK, annual losses due to biological degradation of cotton fibres were put at 110 000 tonnes of cotton, which at time was 1% of output (Howard & Mc Cord). According to estimates by Hueck-van der Plas (1971), the process of biodeterioration affected 2% of annual production of natural and artificial fibres (Zyska, 1977).

At the start of the 21st century annual world consumption of unwoven fabrics (for practical and technical uses) stood at 46 million tonnes, of which synthetics and cotton accounted for 49% and 42% respectively (with an upward trend in subsequent years), wool for 5%, and other fabrics 4% (linen, sisal, silk and others, with a downward trend) (Central Statistical Office Yearbooks – *Roczniki GUS*, Poland 2008). If 2% of the global value of fibre production is assumed, the problem of microbiological decomposition may affect 920 000 tonnes of fabric annually.

Not all losses can have a price attached to them: museum fabrics are particularly rapidly damaged by microorganisms, and the artistic and cultural value of these items cannot be recreated.

Microorganisms which attack textile products not only have a destructive effect, but also pose a significant danger to human health. Particularly dangerous are the pathogenic microorganisms present on fabrics which come into direct contact with the human body, such as on dressings and surgical masks; this may lead to skin infection, and even heart disorders and pneumonia.

It is a significant challenge for manufacturers to produce fabrics with antimicrobial properties – namely bioactive fabrics, containing biocides to provide protection against pathogenic microorganisms.

Microbial Degradation of Woven Fabrics and Protection Against Biodegradation 269

cellulose substances, including 25% lignin) (Basu & Ghose, 1962; Szostak-Kot, 2005). The rate also depends on many other factors: apart from environmental factors and the type of microorganisms, there is also an effect from thickness, type of weave, degree of crystallinity (amorphous cellulose is more easily degraded) and degree of orientation (namely the angle made by the fibrils with the long axis of the fibre – highly oriented fibres are less susceptible to biodeterioration) (Pedersen et al., 1992; Salerno-Kochan & Szostak-Kotowa, 2001; Szostak-

Artificial cellulose fibres include regenerated fibres (rayon) and cellulose acetate. Rayon usually has a lower degree of crystallinity, polymerization and ordering than cotton. It is also highly hygroscopic (its capacity to absorb water in normal conditions is 9.8–13%), which is a reason for its common use in making woven and knitted fabrics and as an additive to natural and synthetic fibre products. Its rate of microbiological decomposition is comparable to that of cotton. Cellulose acetate is produced by the acetylation of cellulose with acetic anhydride, as a result of which the product has a maximal degree of acetylation, and the fibre becomes more resistant to microbiological decomposition than cellulose (Buchanan et al., 1993, Buschle-Diller et al., 1994; Salerno-Kochan & Szostak-Kotowa, 2001;

**Wool** is characterized by high strength, thermal insulation properties and hygroscopicity (it can absorb 50% moisture without feeling wet). Chemically, wool is built from three types of keratins: low-sulphur, high-sulphur and high-tyrosine. Low-sulphur keratins primarily are linked with each other and to proteins of the matrix by numerous bonds – sulphide bridges, covalent bonds and hydrogen bonds, and in the presence of water also hydrophobic bonds. Due to the presence of these bonds and the network structure of wool, it is resistant to stretching and tearing and to environmental factors, including enzymatic degradation.

The biodeterioration of woollen fabrics involves microorganisms with mainly proteolytic and keratinolytic enzymes. So far 299 species of fungus with keratinolytic properties have been described, of which 107 are pathogenic to humans (Błyskal, 2009). Decomposition of a woollen fabric proceeds by way of deamination, sulphitolysis and proteolysis (Kunert, 1992, 2000). The first stage involves the splitting of disulphide bridges, which are the source of keratin's resistant strength. This is followed by the enzymatic decomposition of proteins by proteolytic enzymes (proteases) into oligopeptides, and these are then broken down by peptidases into amino acids, which are used in metabolic processes of oxidative deamination with the release of ammonia (Gochel et al., 1992; Kunert, 1989; Szostak-Kot, 2005). Characteristic symptoms of the microbiological decomposition of wool include the variously coloured stains on the fabric surface, a distinctive smell (in anaerobic conditions

During the technological process the woollen raw material is subjected to mechanical, chemical and photochemical action, which increases the susceptibility of the fibres to biodegradation. Many problems have been reported and described resulting from the development of microorganisms on woollen textiles, for example when carpets are in storage (Gochel et al., 1992; Hoare, 1968; Simpson, 1987). In favourable conditions of temperature (37°C) and humidity of the material (25–75%), the number of fungi may

increase to as much as 109 CFU/1g of wool over 20 days (Zyska, 2001).

Kot, 2005; Tyndal, 1992).

Szostak-Kot, 2005).

H2S is produced), and loss of stretching strength.

A separate issue is the protection of finished textile materials against biodegradation through proper storage, and possibly the use of an appropriate process of disinfection which can effectively eliminate microorganisms without affecting the material's strength properties.


**2. Application of a diffuse 3D model for the detection of rehabilitation exercises after hip surgery**

At the present time, it has been seen that intelligent systems embrace a large number of daily life tasks and activities of the society. The objective of these systems is to solve a variety of existing problems in society more efficiently and with accurate results. One of the characteristics of these systems is the interaction between the user and the computer [1], which allows the optimal handling of these systems intuitively.

The present work proposes the development of a virtual representation of the body structure of a patient who performs rehabilitation exercises. This digital representation is called avatar [2], which duplicates the movement of the human being that has been detected by a Kinect camera from Microsoft's Xbox One.

The captured movements are imitated by the avatar and executed in real time. Subsequently, if the patient performs an incorrect exercise, the system will show an alert with the part of the body where it is moving wrongly, with colors that help the patient's interaction. A detector subsystem applies the diffuse logic technique that identifies the execution of rehabilitation exercises; this allows the avatar to be a means of interaction between human and computer.

In the work presented by Ichim et al. [2], the development of three-dimensional facial avatars is detailed. The system detects facial expression from a template and a sequence of recorded images through an optimization that integrates the tracking of expression characteristics. This study helps the design of new applications of computer animation as well as online communication based on personalized avatars. In addition, demonstrations of several applications in real time that verify the process of avatars creation are presented.

In the work published by Pavone et al. [3], the application of immersive virtual reality and electroencephalography recording is presented to explore the avatar's error incorporation when it is viewed from a one-person perspective. The avatar activates the error monitoring system in a patient's brain and helps its development. The results show that immersive virtual reality can obtain optimal results with the application of an artificial agent. These tools improve the fine-tuning learning (motor skills), up to critical social functions (reading or anticipating the other people's intentions).

The study published by Belal et al. [4] presents the study of pulse oximetry. It is a technology used to monitor oxygen saturation in neonates and pediatric patients. The equipment that measures the pulse oximetry is not precise, whereby they generate false alarms. This study proposes the development of a knowledge-based system that uses fuzzy logic to classify plethysmogram pulses into two categories: valid and artifact. The model correctly classified 82% of the valid segments and 93% of the distorted segments.

The study developed by Guevara et al. [5] proposes a model of real-time movement detection of patients of rehabilitation from hip surgery. The model applies the fuzzy logic technique to identify correct and incorrect movements in the performance of rehabilitation exercises using the motion capture device called Kinect of Xbox One. It proposes an algorithm that works with a multivariable logic model. The diffuse model identifies movements of the patient during the performance of rehabilitation exercises. On the other hand, a 3D avatar is applied, which copies and graphically displays the real-time exercises performed by the patients.

#### **2.1 Data analysis**

The information used for the avatar development was obtained from the capture of body points by the Kinect camera of the Xbox One (**Figure 1**). In this study, we gained information of four patients who have gone through hip surgery. This

**75**

**Figure 3**.

**Figure 1.**

**2.2 Proposed model**

opening angle.

**2.3 Limb opening angle calculation**

*B(Xi, Yi)* and ending point C(Xj

as will be calculated.

*Technical Contributions to the Quality of Telerehabilitation Platforms: Case Study—ePHoRt…*

information was collected during 5 weeks of rehabilitation, with high-, medium-, and low-difficulty exercises. Patients performed a set of exercises correctly and

The detected points were 25, the same ones that can identify any movement in three dimensions. For this reason, the database contains 75 attributes. An information preprocessing has been carried out to identify the relevant information,

The attribute selection for the algorithm has been identified as 18 essential points of the skeleton detected by the Kinect Xbox One. The specific points are 0y, 6x, 6y, 10x, 10y, 12x, 12y, 13x, 13y, 14x, 14y, 15x, 15y, 16x, 16y, 17x, 17y, and 19x. These points determine the movement in a more detailed way, allowing depth and opening angle detection. The points selected for the front step exercise are those shown in **Figure 2** as well as in the lateral step exercise, as shown in

The proposed model uses the points identified in the previous section. With this information, we will calculate the speed and angle of the limb opening that have performed the rehabilitation exercises correctly. This information is vital to build the diffuse model and to determine the patient's correct posture while performing the exercise (arms, shoulders, and head), as well as the execution speed and the

To calculate the angle of the limbs, we identified starting points defined as

is defined as α, as shown in **Figure 4**. In the same way, the execution speed defined

, Yj). The value of the angle between points *B* and *C*

incorrectly, which enabled the avatar real movement.

eliminating repeated data as well as noise.

*Body points captured by Microsoft's Kinect [6].*

*DOI: http://dx.doi.org/10.5772/intechopen.83686*

*Technical Contributions to the Quality of Telerehabilitation Platforms: Case Study—ePHoRt… DOI: http://dx.doi.org/10.5772/intechopen.83686*

**Figure 1.** *Body points captured by Microsoft's Kinect [6].*

*Assistive and Rehabilitation Engineering*

**exercises after hip surgery**

**2. Application of a diffuse 3D model for the detection of rehabilitation**

At the present time, it has been seen that intelligent systems embrace a large number of daily life tasks and activities of the society. The objective of these systems is to solve a variety of existing problems in society more efficiently and with accurate results. One of the characteristics of these systems is the interaction between the user and the computer [1], which allows the optimal handling of these systems intuitively. The present work proposes the development of a virtual representation of the body structure of a patient who performs rehabilitation exercises. This digital representation is called avatar [2], which duplicates the movement of the human being

The captured movements are imitated by the avatar and executed in real time. Subsequently, if the patient performs an incorrect exercise, the system will show an alert with the part of the body where it is moving wrongly, with colors that help the patient's interaction. A detector subsystem applies the diffuse logic technique that identifies the execution of rehabilitation exercises; this allows the avatar to be a

In the work presented by Ichim et al. [2], the development of three-dimensional facial avatars is detailed. The system detects facial expression from a template and a sequence of recorded images through an optimization that integrates the tracking of expression characteristics. This study helps the design of new applications of computer animation as well as online communication based on personalized avatars. In addition, demonstrations of several applications in real time that verify the process

In the work published by Pavone et al. [3], the application of immersive virtual reality and electroencephalography recording is presented to explore the avatar's error incorporation when it is viewed from a one-person perspective. The avatar activates the error monitoring system in a patient's brain and helps its development. The results show that immersive virtual reality can obtain optimal results with the application of an artificial agent. These tools improve the fine-tuning learning (motor skills), up to critical social functions (reading or anticipating the other people's intentions).

The study published by Belal et al. [4] presents the study of pulse oximetry. It is a technology used to monitor oxygen saturation in neonates and pediatric patients. The equipment that measures the pulse oximetry is not precise, whereby they generate false alarms. This study proposes the development of a knowledge-based system that uses fuzzy logic to classify plethysmogram pulses into two categories: valid and artifact. The model correctly classified 82% of the valid segments and

The study developed by Guevara et al. [5] proposes a model of real-time movement detection of patients of rehabilitation from hip surgery. The model applies the fuzzy logic technique to identify correct and incorrect movements in the performance of rehabilitation exercises using the motion capture device called Kinect of Xbox One. It proposes an algorithm that works with a multivariable logic model. The diffuse model identifies movements of the patient during the performance of rehabilitation exercises. On the other hand, a 3D avatar is applied, which copies and

The information used for the avatar development was obtained from the capture

of body points by the Kinect camera of the Xbox One (**Figure 1**). In this study, we gained information of four patients who have gone through hip surgery. This

graphically displays the real-time exercises performed by the patients.

that has been detected by a Kinect camera from Microsoft's Xbox One.

means of interaction between human and computer.

of avatars creation are presented.

93% of the distorted segments.

**74**

**2.1 Data analysis**

information was collected during 5 weeks of rehabilitation, with high-, medium-, and low-difficulty exercises. Patients performed a set of exercises correctly and incorrectly, which enabled the avatar real movement.

The detected points were 25, the same ones that can identify any movement in three dimensions. For this reason, the database contains 75 attributes. An information preprocessing has been carried out to identify the relevant information, eliminating repeated data as well as noise.

The attribute selection for the algorithm has been identified as 18 essential points of the skeleton detected by the Kinect Xbox One. The specific points are 0y, 6x, 6y, 10x, 10y, 12x, 12y, 13x, 13y, 14x, 14y, 15x, 15y, 16x, 16y, 17x, 17y, and 19x. These points determine the movement in a more detailed way, allowing depth and opening angle detection. The points selected for the front step exercise are those shown in **Figure 2** as well as in the lateral step exercise, as shown in **Figure 3**.

### **2.2 Proposed model**

The proposed model uses the points identified in the previous section. With this information, we will calculate the speed and angle of the limb opening that have performed the rehabilitation exercises correctly. This information is vital to build the diffuse model and to determine the patient's correct posture while performing the exercise (arms, shoulders, and head), as well as the execution speed and the opening angle.

#### **2.3 Limb opening angle calculation**

To calculate the angle of the limbs, we identified starting points defined as *B(Xi, Yi)* and ending point C(Xj , Yj). The value of the angle between points *B* and *C* is defined as α, as shown in **Figure 4**. In the same way, the execution speed defined as will be calculated.

#### **Figure 2.**

*Selected points for front step exercise.*

#### **Figure 3.** *Selected points for lateral step exercise.*

To complete the movement modeling of the limbs, it has been based on **Table 1**, which details when the rehabilitation exercise is performed in a low, correct, or high way.

The diffuse model is based on **Table 1** variables, where the patient's correct movement is obtained while performing each of the rehabilitation exercises. Any exercise that is outside the range identified as "good" will be detected as "poorly executed exercise," where the system will give an alert that the variable is being performed incorrectly. The diffuse model is presented in **Figure 5**.

The following section describes the avatar design and development process in three dimensions using the Blender tool, based on the information captured from

**77**

**Figure 8**.

step (**Figure 6**).

**Figure 4.**

**Table 1.**

*Limb opening angle calculation.*

**2.4 Avatar development**

*Technical Contributions to the Quality of Telerehabilitation Platforms: Case Study—ePHoRt…*

several patients who performed physiotherapy exercises over a period of 4 weeks. The exercises performed in this data collection phase were lateral step and front

The following section describes how the patient's avatar was designed. This

The avatar design is fundamentally based on the skeleton in **Figure 1**, which describes all the points detected by the Kinect. This design was then loaded to Blender and the scale of the header image adjusted, as shown in **Figure 7**. To generate a three-dimensional avatar was necessary to generate two 3D windows (two windows for the avatar frontal and lateral view), as can be seen in

For the avatar design, the work has to be simultaneous with the modeling of two avatars, both doctor (male) and nurse (female). This development has been implemented with all the characteristics of clothing, ethnicity, and age of the employees

avatar will imitate the patient's movements during rehabilitation.

*Rules to determine correct or incorrect movement of rehabilitation exercises.*

*DOI: http://dx.doi.org/10.5772/intechopen.83686*

*Technical Contributions to the Quality of Telerehabilitation Platforms: Case Study—ePHoRt… DOI: http://dx.doi.org/10.5772/intechopen.83686*

**Figure 4.** *Limb opening angle calculation.*

*Assistive and Rehabilitation Engineering*

**76**

correct, or high way.

*Selected points for lateral step exercise.*

**Figure 3.**

**Figure 2.**

*Selected points for front step exercise.*

To complete the movement modeling of the limbs, it has been based on **Table 1**, which details when the rehabilitation exercise is performed in a low,

The diffuse model is based on **Table 1** variables, where the patient's correct movement is obtained while performing each of the rehabilitation exercises. Any exercise that is outside the range identified as "good" will be detected as "poorly executed exercise," where the system will give an alert that the variable is being

The following section describes the avatar design and development process in three dimensions using the Blender tool, based on the information captured from

performed incorrectly. The diffuse model is presented in **Figure 5**.

**Table 1.**

*Rules to determine correct or incorrect movement of rehabilitation exercises.*

several patients who performed physiotherapy exercises over a period of 4 weeks. The exercises performed in this data collection phase were lateral step and front step (**Figure 6**).

The following section describes how the patient's avatar was designed. This avatar will imitate the patient's movements during rehabilitation.

#### **2.4 Avatar development**

The avatar design is fundamentally based on the skeleton in **Figure 1**, which describes all the points detected by the Kinect. This design was then loaded to Blender and the scale of the header image adjusted, as shown in **Figure 7**.

To generate a three-dimensional avatar was necessary to generate two 3D windows (two windows for the avatar frontal and lateral view), as can be seen in **Figure 8**.

For the avatar design, the work has to be simultaneous with the modeling of two avatars, both doctor (male) and nurse (female). This development has been implemented with all the characteristics of clothing, ethnicity, and age of the employees

**Figure 5.** *Diffuse model for exercise detection in telerehabilitation [5].*

**Figure 6.** *Exercise images for lateral step and front step.*

that work in a health center, as shown in **Figure 9**. Part of the body of the avatar is designed with proportional measures as well as with skin and clothing textures in order to have a real shape and contour avatar.

Finally, we obtained two functional avatars that will imitate the patient's movements in three dimensions. These avatars will be able to move thanks to an interconnected system between the Kinect and a diffuse model of detection of speed, rhythm, and angles of movement of each of the 75 corporal points. This diffuse model is connected to the avatar through Python language and Java for online movement, which results in efficient response time.


**7. MPC-LQR for LPV Models**

*7.1. Attraction Sets and Terminal Set*

The inclusion of LMIs to ensure robust stability to the MPC paradigm often leads to a conservative performance of the control of the system. Therefore, to steer the system into a desired equilibrium state in the presence of disturbance or uncertainty, a series of terminal sets can be defined. In [32] a set of shrinking ellipsoids is determined using a decay rate, which can vary the speed of the system and the stability determined by similar stability conditions to the ones shown in Section 6, to steer the states to the equilibrium point. However, the determination of the decay rate and the constructions of the ellipsoids make this algorithm too slow for real-time applications and is rather implemented as an offline algorithm. In [33] a set of ellipsoidal sets are defined to predict the behavior of the system in the presence of bounded disturbances and uncertain bounded parameter changes. In [34] a path of ellipsoids is defined to predict the possible behavior of the scheduling parameter along the prediction horizon. In all three approaches, the goal of the ellipsoidal sets is that the states reach a terminal set or a terminal point, where a state-dependent stationary gain is applied to the system instead of the MPC law.

In this work, the future scheduling parameter is not known but predicted using the RLS algorithm presented in Section 3; therefore, the ellipsoids to build do not consider a variation on the scheduling parameter but rather the prediction error generated by the RLS algorithm. To generate the optimal desired trajectory to the setpoint, a path must be defined from every possible initial state to the terminal ellipsoidal set.

To steer the system into the desired terminal set, a term *JTS* is added to the cost function *J* presented in (17). *JTS* is defined as the following:

$$J\_{TS} = \left(\mathbf{x}(k + N\_p) - (\mathbf{x}\_{ds} + \mathbf{x}\_{dist})\right)^T \mathbf{L}\left(\mathbf{x}(k + N\_p) - (\mathbf{x}\_{ds} + \mathbf{x}\_{dist})\right) - E(\rho\_1) \tag{33}$$

where *E*(*ρ*1) = ∑*k*+*Np i*=*k* - *ρ*1(*i*) − *γ*(*i* − 1)*T***Θ**(*i* − 1) 2 represents the sum of the squared errors of the prediction of the future parameter values. **x**(*k* + *Np*) are the predicted states at the end of the prediction horizon, **x***ds* represents the desired state after *Np* steps, **x***dist* is the predicted effect of the disturbance on the states *Np* steps ahead and it was obtained by performing an open loop simulation of every possible disturbance from every initial set of states. Both **x***ds* and **x***dist* were computed offline and stored in a lookup table. **L** is a weighing matrix of appropriate dimensions. Therefore, (17) is redefined as:

$$f = \mathbf{X}^{T}\mathbf{Q}\_{\mathsf{c}}\mathbf{X} + \mathbf{U}^{T}\mathbf{R}\_{\mathsf{c}}\mathbf{U} + f\_{\mathsf{TS}}\tag{34}$$

However, the computation of every desired trajectory for every state needs to be computed offline and stored in a lookup table before the implementation of the MPC algorithm to increase execution speed.


**1. Introduction**

Antimicrobials are the substances or agents that kill, inhibit the growth and/or stop the spread of microorganisms. These are named based on the type of microorganism against which they act. Accordingly they are broadly of four different types [1]:

These are suffixed as ~cidal or ~ static antimicrobials depend on whether they kill or inhibit the growth of microorganisms respectively. For instance a bactericidal antibiotic is an antimicrobial that kills the microorganism, e.g., Vancomycin, Rifampin, Pencillins & Cephalosporins, Aminoglycosides (at high doses), Quinolones, Isoniazid, Metronidazole, Polymyxins and Bacitracin;

However, a bacteriostatic antibiotic is an antimicrobial that stops microorganisms from growing and stalls the process of reproduction, without killing them necessarily e.g. Tetracyclines, Clindamycin, Chloramphenicol, Macrolides, Sulfonamides and Timethoprim. The major difference to differentiate between ~cidal or ~ static antimicrobials is that in the former case, upon removal at the decline phase of an antimicrobial having ~cidal effect, the growth curve of target microorganism continues to decline and never resumes while in later case, since the growth of microorganism is stalled and plateaus at stationary phase, removal of such antimicrobials resumes the growth of target microorganisms from stationary to log phase [2]. Though we discussed of antimicrobials above as source agents that kill or inhibit the spread of microorganisms, yet antimicrobial is a broad term that also includes agents applied to non living surfaces e.g. disinfectants like bleach, non pharmaceuticals like essential oils [3, 4], antimicrobial pesticides and pesticide products [5], and ozone [6] among other antimicrobial properties of metal and metal alloys [7, 8]. However here in this chapter we will limit our discussion on antimicrobials in connection with Actinomycetota (formerly called Actinobacteria) - a class of gram positive microorganisms high in Guanine Cytosine (GC) base pair composition in their DNA and evolutionary viewed as rich source of antimicrobials and FDA approved antibiotics among all the microbial taxa [9, 10]. The name change of phylum Actinobacteria to Actinomycetota is very recent and an innumerable number of research articles communicated still retain the word as Actinobacteria and researchers also use the term Actinobacteria very frequently, so here for the sake of brevity, we will use Actinobacteria and Actinomycetota interchangeably.

Although both ~cidal and ~ static antimicrobials display vital possibility to stop the spread of pathogen causing diseases but the antimicrobial crisis to unlock the potential to counter the menace of antimicrobial drug resistance grows continuously. Resistant pathogenic microorganisms employ one or a combination of following anti-bacterial resistance mechanisms to evade killing by approved antimicrobials;

With every new antibiotic discovery, microorganisms opt for one or the other resistance mechanisms to evade killing by an antimicrobial and sometimes execute it successfully-thus add to the already burdened drug resistance pathogenic load [11]. Thoroughly screened and verified efforts need to be searched to subdue antimicrobial drug resistance patterns.

From the **Table 1**, it is clear that different classes of antimicrobials-having different chemical moieties are being produced by varying Actinobacterial strains, majority of which belong to the genus Streptomyces. These antimicrobials range from majorly characterised chemical classes like tetracyclines, β – Lactams, macrolides, aminoglycosides, lactones, alkaloids, glycopeptides to less known drug moieties like peptides-including simple peptides and lipopeptides, esters and nucleosides. Majority of the broadly classified antimicrobials are a product of nonribosomally synthesised bioactive chemicals by mega-enzyme complexes called NRPS Non-ribosomal peptide synthetases (NRPS) and polyketide synthetases (PKS) and hybrid NRPS-PKS complexes.


**Acknowledgements**

We thank Prof. Fabio Caporali, Mr.Nino Dubla, and Prof.Teodoro Miano for their helpful comments. We are grateful for financial support from the project of Beijing Innovation Consortium of Agriculture Research System BAIC01-2016, project No. GCTDZJ2014033007.


*3.4. Spike-Timing-Di*ff*erence Plasticity and Array Architecture*

Table 2 summarizes the bias conditions for the synaptic operations and the required energy consumption per the realizable synaptic event along with the calculated synaptic device density. In order to exactly calculate the energy consumption, the current is integrated with time and multiplied by voltage. In Table 2, the energy consumption was obtained in the case of maximum value to consider

the worst case. There are approximately 1015 synapses in the brain, about 1% of them are activated at the same time, and the frequency of neuron spike is about 10 Hz [31–33].  In other words, it is assumed that power of 11 W is consumed for the synaptic activities. The power consumption per biological synaptic event is derived to be 1.1 × 10−12 W. Considering that each synaptic event has a ~100 ms duration, the energy consumption per synaptic event is calculated to be about 10 fJ. For the inference operation, 20 ns of rising and falling times and 10 ns of pulse duration are schemed, and then, this time period is multiplied by the inference voltage of −0.1 V and the current depending on weight for calculation of the energy consumption. The energies required for respective synaptic operations are summarized in Table 2, and most of them are very close to those for the biological synapse. Potentiation operation increases the conductance of the synaptic device so that a relatively large energy consumption is required; however, the amount is still low. Owing to the low operation voltage and tunneling-based injection mechanism, maximum energy consumption of only 0.52 pJ is needed for a potentiation event. For a depression event, the trapped holes tunnel back to the channel, which necessitates a relatively high operation voltage on the gate 2. However, even in the worst case, the required energy consumption is much lower than that for a potentiation event. Although the energy consumption for individual potentiation or depression event can be higher than that for an inference operation, the energy for an inference event can be spanned over a large range depending on the conductance. With the help of low-power and high-speed operation capabilities, the proposed synaptic transistor requires only a femto-joule energy even after 40 potentiation pulses are applied. Assuming that a unit cell has a footprint of 158 nm by 150 nm, the density of synaptic device array is calculated to be 9.09 × 109 /cm2 . Here, the critical dimensions of the designed device and the metal pitches in one of the most recent memory technologies have been considered [38], where the wordline (WL) and bitline (BL) pitches are 48 and 54 nm, respectively. activated at the same time, and the frequency of neuron spike is about 10 Hz [31–33].  In other words, it is assumed that power of 11 W is consumed for the synaptic activities. The power consumption per biological synaptic event is derived to be 1.1×10−12 W. Considering that each synaptic event has a ~100 ms duration, the energy consumption per synaptic event is calculated to be about 10 fJ. For the inference operation, 20 ns of rising and falling times and 10 ns of pulse duration are schemed, and then, this time period is multiplied by the inference voltage of -0.1 V and the current depending on weight for calculation of the energy consumption. The energies required for respective synaptic operations are summarized in Table 2, and most of them are very close to those for the biological synapse. Potentiation operation increases the conductance of the synaptic device so that a relatively large energy consumption is required; however, the amount is still low. Owing to the low operation voltage and tunneling-based injection mechanism, maximum energy consumption of only 0.52 pJ is needed for a potentiation event. For a depression event, the trapped holes tunnel back to the channel, which necessitates a relatively high operation voltage on the gate 2. However, even in the worst case, the required energy consumption is much lower than that for a potentiation event. Although the energy consumption for individual potentiation or depression event can be higher than that for an inference operation, the energy for an inference event can be spanned over a large range depending on the conductance. With the help of low-power and high-speed operation capabilities, the proposed synaptic transistor requires only a femto-joule energy even after 40 potentiation pulses are applied. Assuming that a unit cell has a footprint of 158 nm by 150 nm, the density of synaptic device array is calculated to be 9.09 × 109 /cm2 . Here, the critical dimensions of the designed device and the metal pitches in one of the most recent memory technologies have been considered [38], where the wordline (WL) and bitline (BL) pitches are 48 and 54 nm, respectively.

*Electronics* **2019**, *8*, x FOR PEER REVIEW 9 of 12

characteristics under different interval time conditions for the same total number of potentiation pulses of 10. It is assured that a short enough time interval allows the synaptic device to enter the

Table 2 summarizes the bias conditions for the synaptic operations and the required energy consumption per the realizable synaptic event along with the calculated synaptic device density. In order to exactly calculate the energy consumption, the current is integrated with time and multiplied

consider the worst case. There are approximately 1015 synapses in the brain, about 1% of them are

LTP states and modulate the electrical conductivity for learning.

*3.4. Spike-Timing-Difference Plasticity and Array Architecture*

**Table 2.** Energy consumption per realizable synaptic event and the calculated synapse density. **Table 2.** Energy consumption per realizable synaptic event and the calculated synapse density**.**

Furthermore, the spike-timing-dependent plasticity (STDP) characteristics have been obtained by adjusting the pulse profile and time difference as demonstrated in Figure 7. The inset describes the potentiation and depression pulse schemes in the STDP simulations. The spiking pulse has 950 ns of rising time and 100 ns falling time, respectively, and the positive and negative voltage peak is 0.72 V in magnitude. The pre-neuron is connected with drain, and the post-neuron is with gate 1 and gate 2. When a pre-neuron spike comes earlier than a post-neuron one, the synaptic transistor is potentiated since the holes generated by tunneling operation from channel to drain are stored in the nitride charge-trap layer, which improves the conductance of the device. In the reversed order, the Furthermore, the spike-timing-dependent plasticity (STDP) characteristics have been obtained by adjusting the pulse profile and time difference as demonstrated in Figure 7. The inset describes the potentiation and depression pulse schemes in the STDP simulations. The spiking pulse has 950 ns of rising time and 100 ns falling time, respectively, and the positive and negative voltage peak is 0.72 V in magnitude. The pre-neuron is connected with drain, and the post-neuron is with gate 1 and gate 2. When a pre-neuron spike comes earlier than a post-neuron one, the synaptic transistor is potentiated since the holes generated by tunneling operation from channel to drain are stored in the nitride charge-trap layer, which improves the conductance of the device. In the reversed order, the device is depressed owing to ejection of the trapped holes out of the nitride layer. When the timing difference between pre- and post-neuron spikes is larger than 900 ns, the conductance of the device is not changed but left as the initial value, which indicates that two neurons are not so closely correlated, and there is neither potentiation nor depression. It is noticeable that the synaptic transistor has a large current difference for the different spike timing, which substantially reduces the complexity of the sensing circuits and enhances the system reliability. Figure 8 demonstrates a presumable array architecture with the designed synaptic transistor for a hardware-driven neuromorphic system.

neuromorphic system.

neuromorphic system.

nitride charge-trap layer, which improves the conductance of the device. In the reversed order, the device is depressed owing to ejection of the trapped holes out of the nitride layer. When the timing difference between pre- and post-neuron spikes is larger than 900 ns, the conductance of the device is not changed but left as the initial value, which indicates that two neurons are not so closely correlated, and there is neither potentiation nor depression. It is noticeable that the synaptic transistor has a large current difference for the different spike timing, which substantially reduces the complexity of the sensing circuits and enhances the system reliability. Figure 8 demonstrates a

nitride charge-trap layer, which improves the conductance of the device. In the reversed order, the device is depressed owing to ejection of the trapped holes out of the nitride layer. When the timing difference between pre- and post-neuron spikes is larger than 900 ns, the conductance of the device is not changed but left as the initial value, which indicates that two neurons are not so closely correlated, and there is neither potentiation nor depression. It is noticeable that the synaptic transistor has a large current difference for the different spike timing, which substantially reduces the complexity of the sensing circuits and enhances the system reliability. Figure 8 demonstrates a

*Electronics* **2019**, *8*, x FOR PEER REVIEW 10 of 12

**Figure 7.** Spike-timing-dependent plasticity characteristic of the proposed synaptic device. The inset describes the potentiation and depression pulse schemes. **Figure 7.** Spike-timing-dependent plasticity characteristic of the proposed synaptic device. The inset describes the potentiation and depression pulse schemes. **Figure 7.** Spike-timing-dependent plasticity characteristic of the proposed synaptic device. The inset describes the potentiation and depression pulse schemes.

**Figure 8.** Array architecture with the proposed four-terminal synaptic transistor towards a highdensity and high-reliability hardware-driven neuromorphic system. **Figure 8.** Array architecture with the proposed four-terminal synaptic transistor towards a highdensity and high-reliability hardware-driven neuromorphic system. **Figure 8.** Array architecture with the proposed four-terminal synaptic transistor towards a high-density and high-reliability hardware-driven neuromorphic system.

### **4. Conclusions 4. Conclusions**

**4. Conclusions** In this work, a synaptic transistor having SiGe quantum well and nitride charge-trap layer was schemed and characterized by a series of rigorous simulation works. The synaptic device has successfully demonstrated the synaptic operations including STP, LTP, and inference with high energy efficiency not exceeding a two femto-joules in the worst case. Further, spike-timingdependent plasticity was verified through a properly adjusted pulse scheme. A presumable array In this work, a synaptic transistor having SiGe quantum well and nitride charge-trap layer was schemed and characterized by a series of rigorous simulation works. The synaptic device has successfully demonstrated the synaptic operations including STP, LTP, and inference with high energy efficiency not exceeding a two femto-joules in the worst case. Further, spike-timingdependent plasticity was verified through a properly adjusted pulse scheme. A presumable array In this work, a synaptic transistor having SiGe quantum well and nitride charge-trap layer was schemed and characterized by a series of rigorous simulation works. The synaptic device has successfully demonstrated the synaptic operations including STP, LTP, and inference with high energy efficiency not exceeding a two femto-joules in the worst case. Further, spike-timing-dependent plasticity was verified through a properly adjusted pulse scheme. A presumable array architecture is also conceived with the four-terminal synaptic device, and its density was calculated to be 9.09 × 109 /cm2 based on the interconnect schemes in the 18-nm DRAM technology node.

**Author Contributions:** E.Y. and S.C. conceived the device structure and wrote the manuscript. E.Y. performed the device simulations and evaluated the device scalability and array density. S.C. approved the simulation results in confirmation of the biological analogies. B.-G.P. conceived and developed the various types of hardware-driven neuromorphic systems, initiated the overall research project, and confirmed the validities of the simulated synaptic operations towards the artificial spike neural network.

**Funding:** This work was supported by Nano·Material Technology Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT) (Grant No. NRF-2016M3A7B4910348) and by Mid-Career Researcher Program through NRF funded by the MSIT (Grant No. NRF-2017R1A2B2011570).

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