Two healthy volunteers and ten patients (six males and four females; 47.20 +- 20.47 years old) were recruited at the USL 5 Rehabilitation Centre at Fornacette (Pisa), Italy. Nine performed PS training, while seven performed both PS and FE movements. All patients received a medical indication of the following traditional rehabilitation physiotherapy of the forearm due to fracture(s) at the elbow or wrist joints and after at least a period of 7 to 10 days after the splint withdrawal. None presented fragments instability, severe pain sensation, kinaesthetic or tactile sensorial disorders in the upper limb, or cognitive impairment. The subjects were informed regarding the aspects of the study and signed their informed consent before the experimental sessions. The study was reviewed by the local ethics committee.
All patients underwent a battery of clinical assessments: (i) the ranges of motion with extendable goniometers and following standard procedures, (ii) the strength of the affected hand by the Jamar strength test, and (iii) the pain sensation using the VAS pain test (Visual Analogue Scale for the pain test). The musculoskeletal ability to perform activities of daily life applying the Italian version of the DASH Questionnaire (Disabilities of the Arm Shoulder and Hand Questionnaire) normalised to a scale from 0 to 100 where the zero score means no impairment and proper functionality, while 100 means severe impairment and limited functionality. The patients presented reduction of mobility at the limits of functional FE RoM (90.17 +- 23.08 , with 104.25 +- 28.89  of flexion below a functional range of 130  and 13.83 +- 18.48  of extension) and also at the limits of functional PS RoM (118.60 +- 11.07 , with 58.80 +- 20.89  of pronation and 59.80 +- 20.27  of supination), presented a small registered hand strength of 15.40 +- 16.09 kg, reported mild pain sensation of 4.3 +- 2.0, and self-perceived disability of 59.46 +- 10.79% according to the DASH score.  Table 2 shows the clinical characteristics of the patient population.
With the first aim of evaluating the functionality of the system, we recruited two healthy volunteers for testing the system before the evaluation in patients. We were particularly interested in studying the capability of the system for assigning incremental working profiles at moderate loads, under safe conditions at any moment and without overloading the patients.
We analysed their muscular activity to verify the effectiveness of the system in assigning different working loads in a training session under similar conditions, as for patients.
The subjects were invited to perform 45 minutes of training with the Bells game. Three motion velocities (low, medium, and high), under three haptic feedback modalities, were applied: zero force (ZF), assistance force (AF), and resistance force (RF) feedback. Two different force intensities were used for AF and RF, for a total of 15 working load combinations: 3 velocities x (2 AF + 2 RF + 1 ZF). The velocity levels for FE were 80 /s (low), 110 /s (medium), and 190 /s (high) (corresponding to movements within an RoM of 125  in time periods of 1.5 s, 0.9 s, and 0.65 s, resp.). The force feedback consisted of estimated mean values of 2.73 N (medium) and 5 N (high) for AF, while 1.8 N (medium) and 2.5 N (high) for RF. The ZF + medium velocity condition corresponded to natural movements during the calibration at the beginning of the session.
The muscular activation was monitored through surface electromyography (sEMG) by seven pairs of surface electrodes placed on two muscles of the subjects' upper limb: the biceps brachii (BB) and triceps brachii long head (TBL). SENIAM recommendations were followed for sensor positioning and the skin preparation (http://www.seniam.org). Ag/AgCl foam pregelled electrodes with a diameter of 24 mm were used with an interelectrode distance set to 20 mm for each bipolar derivation. The ground and the reference electrodes for all bipolar derivations were positioned at the elbow. All electrodes were connected to an amplifier (g.USBamp amplifier; http://www.gtec.at/) and digitally converted (1200 Hz sample frequency, 12-bit resolution). We preprocessed the envelopes of the activation signals for analysing isolated movements, as follows.
A band-pass filter was applied (5-500 Hz bandwidth), followed by high-pass filtering (cutoff frequency of 20 Hz), full-wave rectification, and low-pass filtering (1 Hz cutoff frequency). Then, the signals were divided into epochs using the maximum peak of the recorded FE elbow angle as a reference trigger and resampled using a cubic spline interpolation.  Figure 6 shows the average muscle profiles of a healthy volunteer under the different tested conditions.
To verify the suitability of the system to be used as an aided method for orthopaedic physiotherapy of the forearm, we carried out a second experiment with patients. The tests were done to confirm the capability of the system for providing controlled and moderate motion tasks with patients, after the preliminary evaluation with two healthy volunteers. To this purpose, first, we analysed the kinesiologic patient's performance and the relationship of the variable difficulty training levels with the current patient clinical conditions according to the standard clinical outcomes (JAMAR, VAS, and DASH tests). We were also interested in two other issues: (i) the possibility of introducing a new predictive metric of performance as a critical tool for guiding the recovery by the therapist and (ii) assessing the system and verifying its acceptance by patients.
The tests lasted 30 minutes of exercising divided into three parts, with two pauses of 2 minutes for resting, for a total of 45 minutes per session, including the initial calibration phase. For practicality, for FE movements, all tested the Bells game because it did not require the external support of the arm.
Before starting the session, the patient was assisted to sit down in the correct posture. Next, we evaluated the current motion capability (RoM, velocity, and force) of the patient and then calibrated the starting difficulty level of the game. The difficulty was progressively adjusted by the hand during the session, always within safe tolerances. In other words, with the aim of preventing any manual error by the therapist, the system constrained the game parameters to ranges that matched from half to the full current capacity of the patient according to the calibration. In particular, for FE, completion task time ttask was constrained up to 2tbase, maximum force intensity up to half of the tolerated force intensity (through the impedance gain Kp up to 1/2KpEX or 1/2KpFLEX), and RoMwork up to 1.2 RoMpatient. For PS, RoMwork was constrained up to 1.2 RoMpatient. Then, patients were invited to perform and were kindly instructed to concentrate and to express if they felt pain or discomfort during the exercising.
With the aim of aiding the therapist to manually individualise the physiotherapy by systematically incrementing the training demand levels, we implemented a model of the performance of the patients. For this purpose, a principal component analysis (PCA) was applied to the observed kinesiology information of patients. The model resulted in the linear combination of a performed range of motion, velocity, and tolerated exerted resistive force by the system (RoMperformed, Velocityperformed, and Forceperformed) for FE, while RoMperformed and Velocityperformed for PS. Then, for providing a prior estimation of performance, predictive regression models of normalised outcomes of RoM*performed and Velocity*performed for FE and PS and Force*performed for FE were developed, all regarding game input parameters, as follows:where xi is the ith input parameter among the p significant input variables (significant main factors) for the corresponding outcome, xj and xk correspond to significant interacting factors, and bn are constant values. Significant main factors and interactions over outcomes (RoMperformed, Velocityperformed, and Forceperformed) were identified through a series of multifactorial ANOVAs (MANOVAs). The MANOVA series followed a design of 3 target sequences x 3 levels of ttask x 3 levels of RoMwork x 3 levels of Forcework for FE movements, while 2 sequences x 3 RoMwork x 3 balls' number x 3 balls' speed x 3 balls' frequency for PS movements.
Finally, optimisation of the regression models was carried out over the training data set of 7 patients for PS and six patients for FE, while we used the data of 2 patients for PS and one patient for FE for model comparison and validation.
We applied an ad hoc designed questionnaire with eight items, all rated on a 7-point Likert scale (where 1 was the minimum, 7 the maximum, and 4 the neutral scores), for qualifying diverse perceived aspects regarding the confidence and acceptability of the system (Table 3). Six items assessed the usability and acceptance of the system: (1) How much the patients perceived it enjoyable (enjoy)? (2) How much difficult it was (difficult)? (3) How much exhausting they felt (fatigue)? (4) How much attention they paid (attention)? (5) How much physical pain patients felt in the affected limb during the exercises (pain)? (6) How much annoyed they felt during the exercises (annoyance)? Two extra items evaluated the embodiment sensation during the sessions, regarding two sensations: (1) the sense of ownership, which means how much they perceived that the virtual avatar was their own limb, and (2) the sense of agency that indicates how much they recognised that the movements and actions of the virtual avatar were caused by their own actions.