Continuous Motion Intention Prediction Using sEMG for Upper-Limb Rehabilitation: A Systematic Review of Model-Based and Model-Free Approaches.

Upper limb functional impairments persisting after stroke significantly affect patients' quality of life. Precise adjustment of robotic assistance levels based on patients' motion intentions using sEMG signals is crucial for active rehabilitation. This paper systematically reviews studies on continuous prediction of upper limb single joints and multi-joint combinations motion intention using Model-Based (MB) and Model-Free (MF) approaches over the past decade, based on 186 relevant studies screened from six major electronic databases. The findings indicate ongoing challenges in terms of subject composition, algorithm robustness and generalization, and algorithm feasibility for practical applications. Moreover, it suggests integrating the strengths of both MB and MF approaches to improve existing algorithms. Therefore, future research should further explore personalized MB-MF combination methods incorporating deep learning, attention mechanisms, muscle synergy features, motor unit features, and closed-loop feedback to achieve precise, real-time, and long-duration prediction of multi-joint complex movements, while further refining the transfer learning strategy for rapid algorithm deployment across days and subjects. Overall, this review summarizes the current research status, significant findings, and challenges, aiming to inspire future research on predicting upper limb motion intentions based on sEMG.

Biomechanical Effects of Using a Passive Exoskeleton for the Upper Limb in Industrial Manufacturing Activities: A Pilot Study.

This study investigates the biomechanical impact of a passive Arm-Support Exoskeleton (ASE) on workers in wool textile processing. Eight workers, equipped with surface electrodes for electromyography (EMG) recording, performed three industrial tasks, with and without the exoskeleton. All tasks were performed in an upright stance involving repetitive upper limbs actions and overhead work, each presenting different physical demands in terms of cycle duration, load handling and percentage of cycle time with shoulder flexion over 80°. The use of ASE consistently lowered muscle activity in the anterior and medial deltoid compared to the free condition (reduction in signal Root Mean Square (RMS) -21.6% and -13.6%, respectively), while no difference was found for the Erector Spinae Longissimus (ESL) muscle. All workers reported complete satisfaction with the ASE effectiveness as rated on Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST), and 62% of the subjects rated the usability score as very high (>80 System Usability Scale (SUS)). The reduction in shoulder flexor muscle activity during the performance of industrial tasks is not correlated to the level of ergonomic risk involved. This preliminary study affirms the potential adoption of ASE as support for repetitive activities in wool textile processing, emphasizing its efficacy in reducing shoulder muscle activity. Positive worker acceptance and intention to use ASE supports its broader adoption as a preventive tool in the occupational sector.

Virtual Reality Self Co-Embodiment: An Alternative to Mirror Therapy for Post-Stroke Upper Limb Rehabilitation.

We present Virtual Reality Self Co-embodiment, a new method for post-stroke upper limb rehabilitation. It is inspired by mirror therapy, where the patient's healthy arm is involved in recovering the affected arm's motion. By tracking the user's head, wrists, and fingers' positions, our new approach allows the handicapped arm to control a digital avatar in order to pursue a reaching task. We apply the concept of virtual co-embodiment to use the information from the unaffected arm and complete the affected limb's impaired motion, which is our added unique feature. This requires users to mechanically involve the incapacitated area as much as possible, prioritizing actual movement rather than the sole imagination of it. As a result, subjects will see a seemingly normally functional virtual arm primarily controlled by their handicapped extremity, but with the constant support of their healthy limb's motion. Our experiment compares the task execution performance and embodiment perceived when interacting with both mirror therapy and our proposed technique. We found that our approach's provided sense of ownership is mildly impacted by users' motion planning response times, which mirror therapy does not exhibit. We also observed that mirror therapy's sense of ownership is moderately affected by the subject's proficiency while executing the assigned task, which our new method did not display. The results indicate that our proposed method provides similar embodiment and rehabilitation capabilities to those perceived from existing mirror therapy. This experiment was performed in healthy individuals to have an unbiased comparison of how mirror therapy's and VRSelfCo's task performance and degree of virtual embodiment compare, but future work explores the possibility of applying this new approach to actual post-stroke patients.

An Optimized Stimulation Control System for Upper Limb Exoskeleton Robot-Assisted Rehabilitation Using a Fuzzy Logic-Based Pain Detection Approach.

The utilization of robotic systems in upper limb rehabilitation has shown promising results in aiding individuals with motor impairments. This research introduces an innovative approach to enhance the efficiency and adaptability of upper limb exoskeleton robot-assisted rehabilitation through the development of an optimized stimulation control system (OSCS). The proposed OSCS integrates a fuzzy logic-based pain detection approach designed to accurately assess and respond to the patient's pain threshold during rehabilitation sessions. By employing fuzzy logic algorithms, the system dynamically adjusts the stimulation levels and control parameters of the exoskeleton, ensuring personalized and optimized rehabilitation protocols. This research conducts comprehensive evaluations, including simulation studies and clinical trials, to validate the OSCS's efficacy in improving rehabilitation outcomes while prioritizing patient comfort and safety. The findings demonstrate the potential of the OSCS to revolutionize upper limb exoskeleton-assisted rehabilitation by offering a customizable and adaptive framework tailored to individual patient needs, thereby advancing the field of robotic-assisted rehabilitation.

Detection of Rehabilitation Training Effect of Upper Limb Movement Disorder Based on MPL-CNN.

Stroke represents a medical emergency and can lead to the development of movement disorders such as abnormal muscle tone, limited range of motion, or abnormalities in coordination and balance. In order to help stroke patients recover as soon as possible, rehabilitation training methods employ various movement modes such as ordinary movements and joint reactions to induce active reactions in the limbs and gradually restore normal functions. Rehabilitation effect evaluation can help physicians understand the rehabilitation needs of different patients, determine effective treatment methods and strategies, and improve treatment efficiency. In order to achieve real-time and accuracy of action detection, this article uses Mediapipe's action detection algorithm and proposes a model based on MPL-CNN. Mediapipe can be used to identify key point features of the patient's upper limbs and simultaneously identify key point features of the hand. In order to detect the effect of rehabilitation training for upper limb movement disorders, LSTM and CNN are combined to form a new LSTM-CNN model, which is used to identify the action features of upper limb rehabilitation training extracted by Medipipe. The MPL-CNN model can effectively identify the accuracy of rehabilitation movements during upper limb rehabilitation training for stroke patients. In order to ensure the scientific validity and unified standards of rehabilitation training movements, this article employs the postures in the Fugl-Meyer Upper Limb Rehabilitation Training Functional Assessment Form (FMA) and establishes an FMA upper limb rehabilitation data set for experimental verification. Experimental results show that in each stage of the Fugl-Meyer upper limb rehabilitation training evaluation effect detection, the MPL-CNN-based method's recognition accuracy of upper limb rehabilitation training actions reached 95%. At the same time, the average accuracy rate of various upper limb rehabilitation training actions reaches 97.54%. This shows that the model is highly robust across different action categories and proves that the MPL-CNN model is an effective and feasible solution. This method based on MPL-CNN can provide a high-precision detection method for the evaluation of rehabilitation effects of upper limb movement disorders after stroke, helping clinicians in evaluating the patient's rehabilitation progress and adjusting the rehabilitation plan based on the evaluation results. This will help improve the personalization and precision of rehabilitation treatment and promote patient recovery.

Assessment and indicators of kinematic behavior and perceived fatigability.

OBJECTIVE: The objective of this study was to investigate the relationship between upper limb kinetics and perceived fatigability in elderly individuals during an upper limb position sustained isometric task. METHODS: A total of 31 elderly participants, 16 men (72.94±4.49 years) and 15 women (72.27±6.05 years), performed a upper limb position sustained isometric task. Upper-limb acceleration was measured using an inertial measurement unit. Perceived fatigability was measured using the Borg CR10 scale. RESULTS: Higher mean acceleration in the x-axis throughout the activity was associated with higher final perceived fatigability scores. Moderate correlations were observed between perceived fatigability variation and mean acceleration cutoffs in all axes during the second half of the activity. In women, significant correlations were found between all perceived fatigability cutoffs and mean acceleration in the y- and x-axes. However, in men, the relationships between perceived fatigability variation and mean acceleration were more extensive and stronger. CONCLUSION: The acceleration pattern of the upper limb is linked to perceived fatigability scores and variation, with differences between sexes. Monitoring upper limb acceleration using a single inertial measurement unit can be a useful and straightforward method for identifying individuals who may be at risk of experiencing high perceived fatigability or task failure.

Multi Degree of Freedom Hybrid FES and Robotic Control of the Upper Limb.

Individuals who have suffered a spinal cord injury often require assistance to complete daily activities, and for individuals with tetraplegia, recovery of upper-limb function is among their top priorities. Hybrid functional electrical stimulation (FES) and exoskeleton systems have emerged as a potential solution to provide upper limb movement assistance. These systems leverage the user's own muscles via FES and provide additional movement support via an assistive exoskeleton. To date, these systems have focused on single joint movements, limiting their utility for the complex movements necessary for independence. In this paper, we extend our prior work on model predictive control (MPC) of hybrid FES-exo systems and present a multi degree of freedom (DOF) hybrid controller that uses the controller's cost function to achieve desired behavior. In studies with neurologically intact individuals, the hybrid controller is compared to an exoskeleton acting alone for movement assistance scenarios incorporating multiple degrees-of-freedom of the limb to explore the potential for exoskeleton power consumption reduction and impacts on tracking accuracy. Additionally, each scenario is explored in simulation using the models required to generate the MPC formulation. The two DOF hybrid controller implementation saw reductions in power consumption and satisfactory trajectory tracking in both the physical and simulated systems. In the four DOF implementation, the experimental results showed minor improvements for some joints of the upper limb. In simulation, we observed comparable performance as in the two DOF implementation.

Simulation of a control method for active kinesiotherapy with an upper extremity rehabilitation exoskeleton without force sensor.

Exoskeleton-aided active rehabilitation is a process that requires sensing and acting upon the motion intentions of the user. Typically, force sensors are used for this. However, they increase the weight and cost of these wearable devices. This paper presents the methodology for detecting users' intentions only with encoders integrated with the drives. It is unique compared to other algorithms, as enables active kinesiotherapy while adding no sensory systems. The method is based on comparing the measured motion with the one computed with the idealised model of the multibody system. The investigation assesses the method's performance and its robustness to model and measurement inaccuracies, as well as patients' unintended motions. Moreover, the PID parameters are selected to provide the optimal regulation based on the dynamics requirements. The research proves the presented concept of the control approach. For all the tests with the final settings, the system reacts to a change in the user's intention below one second and minimises the changes in proportion between the system's acceleration and the generated user's joint torque. The results are comparable to those obtained by EMG-based systems and significantly better than low-cost force sensors.

Evaluation of antigravitational support levels provided by a passive upper-limb occupational exoskeleton in repetitive arm movements.

Upper-limb occupational exoskeletons to support the workers' upper arms are typically designed to provide antigravitational support. Although typical work activities require workers to perform static and dynamic actions, the majority of the studies in literature investigated the effects of upper-limb occupational exoskeletons in static and quasi-static activities, while only a few works focused on dynamic tasks. This article presents a systematic evaluation of the effects of different levels of antigravitational support (from about 60% to 100% of the arm gravitational load) provided by a passive upper-limb occupational exoskeleton on muscles' activity during repetitive arm movements. The effect of the exoskeleton on muscle activity was evaluated by the comparison of muscle activations with and without the exoskeleton. The average muscle activation was computed considering shoulder full flexion-extension cycles, and sub-movements, namely the arm-lifting (i.e., flexion) and arm-lowering (i.e., extension) movements. Results showed a quasi-linear correlation between antigravitational support and muscle activity reductions, both when considering the full flexion-extension cycle and in the arm-lifting movement (reductions were up to 64 and 61% compared to not wearing the exoskeleton, respectively). When considering the arm-lowering movement, providing antigravitational support close to or higher than 100% of the arm gravitational load led to increased muscle activations of the extensors (up to 127%), suggesting that such an amount of antigravitational support may be not effective for a complete biomechanical load reduction on the shoulder district in dynamic tasks.

Acute Effects of Strength and Skill Training on the Cortical and Spinal Circuits of Contralateral Limb.

Unilateral strength and skill training increase strength and performance in the contralateral untrained limb, a phenomenon known as cross-education. Recent evidence suggests that similar neural mechanisms might be responsible for the increase in strength and skill observed in the untrained hand after unimanual training. The aims of this study were to: investigate whether a single session of unimanual strength and skill (force-tracking) training increased strength and skill in the opposite hand; measure ipsilateral (untrained) brain (via transcranial magnetic stimulation, TMS) and spinal (via the monosynaptic reflex) changes in excitability occurring after training; measure ipsilateral (untrained) pathway-specific changes in neural excitability (via TMS-conditioning of the monosynaptic reflex) occurring after training. Participants (N = 13) completed a session of unimanual strength (ballistic isometric wrist flexions) and skill (force-tracking wrist flexions) training on two separate days. Strength increased after training in the untrained hand (p = 0.025) but not in the trained hand (p = 0.611). Force-tracking performance increased in both the trained (p = 0.007) and untrained (p = 0.010) hand. Corticospinal excitability increased after force-tracking and strength training (p = 0.027), while spinal excitability was not affected (p = 0.214). TMS-conditioned monosynaptic reflex increased after force-tracking (p = 0.001) but not strength training (p = 0.689), suggesting a possible role of polysynaptic pathways in the increase of cortical excitability observed after training. The results suggest that cross-education of strength and skill at the acute stage is supported by increased excitability of the untrained motor cortex.New & Noteworthy: A single session of isometric wrist flexion strength and skill straining increased strength and skill in the untrained limb. The excitability of the untrained motor cortex increased after strength and skill training. TMS-conditioned H-reflexes increased after skill but not strength training in the untrained hand, indicating that polysynaptic pathways in the increase of cortical excitability observed after skill training.

Design and analysis of a compatible exoskeleton rehabilitation robot system based on upper limb movement mechanism.

Rehabilitation robots are used to promote structural and functional recovery of the nervous system with repetitive, task-oriented training and have been gradually applied to clinical rehabilitation training. This paper proposes an upper limb exoskeleton rehabilitation robot system that could realize shoulder-elbow-wrist joint rehabilitation training. Firstly, a motion equivalent model was established based on the upper limb movement mechanism, the robot mechanism configuration was designed, and the optimization algorithm and spatial mechanism theory were used to optimize and analyze the structural parameters and human-machine compatibility of the robot, which will guide the design of the robot's model. Then, the robot kinematics were solved, and its maximum motion range, dexterity distribution, and daily motion trajectory were simulated. Finally, a system prototype was built to test the maximum range of robot-assisted human upper limb training by laser tracker, while the pressure of human-machine interaction during training was captured and analyzed by flexible sensors. The results show that the proposed rehabilitation robot could nearly completely cover the range of motion of upper limb joints and meet the needs of trajectory training, and the linear velocity dexterity and angular velocity dexterity in the motion space are maximum 0.55 and 0.89, and the human-machine interaction pressures during the training process are all less than 10 kPa. Besides, this paper also conducted a system evaluation based on the fuzzy comprehensive evaluation model, and the evaluation result was 0.39, with an excellent evaluation grade, it indirectly indicates that the robot's overall performance was good.

Reducing Motor Variability Enhances Myoelectric Control Robustness Across Untrained Limb Positions.

The limb position effect is a multi-faceted problem, associated with decreased upper-limb prosthesis control acuity following a change in arm position. Factors contributing to this problem can arise from distinct environmental or physiological sources. Despite their differences in origin, the effect of each factor manifests similarly as increased input data variability. This variability can cause incorrect decoding of user intent. Previous research has attempted to address this by better capturing input data variability with data abundance. In this paper, we take an alternative approach and investigate the effect of reducing trial-to-trial variability by improving the consistency of muscle activity through user training. Ten participants underwent 4 days of myoelectric training with either concurrent or delayed feedback in a single arm position. At the end of training participants experienced a zero-feedback retention test in multiple limb positions. In doing so, we tested how well the skill learned in a single limb position generalized to untrained positions. We found that delayed feedback training led to more consistent muscle activity across both the trained and untrained limb positions. Analysis of patterns of activations in the delayed feedback group suggest a structured change in muscle activity occurs across arm positions. Our results demonstrate that myoelectric user-training can lead to the retention of motor skills that bring about more robust decoding across untrained limb positions. This work highlights the importance of reducing motor variability with practice, prior to examining the underlying structure of muscle changes associated with limb position.

A Self-Aligning Upper-Limb Exoskeleton Preserving Natural Shoulder Movements: Kinematic Compatibility Analysis.

NESM- γ is an upper-limb exoskeleton to train motor functions of post-stroke patients. Based on the kinesiology of the upper limb, the NESM- γ includes a four degrees-of-freedom (DOF) active kinematic chain for the shoulder and elbow, along with a passive chain for self-aligning robotic joint axes with the glenohumeral (GH) joint's center of rotation. The passive chain accounts for scapulohumeral rhythm and trunk rotations. To assess self-aligning performance, we analyzed the kinematic and electromyographic data of the shoulder in eight healthy subjects performing reaching tasks under three experimental conditions: moving without the exoskeleton (baseline), moving while wearing the exoskeleton with the passive DOFs properly functioning, i.e., unlocked (human-in-the-loop(HIL)-unlocked), and with the passive DOFs locked (HIL-locked). Comparison of baseline and HIL-unlocked conditions showed nearly unchanged anatomical movement patterns, with a root-mean-square error of shoulder angle lower than 5 deg and median deviations of the GH center of rotation below 20 mm. Peak muscle activations showed no significant differences. In contrast, the HIL-locked condition deviated significantly from the baseline, as observed by the trunk and GH trajectory deviations up to 50 mm, accompanied by increased peak muscle activations in the Deltoid and Upper Trapezius muscles. These findings highlight the need for kinematic solutions in shoulder exoskeletons that can accommodate the movements of the entire shoulder complex and trunk to achieve kinematic compatibility.

Adaptive Learning based Upper-Limb Rehabilitation Training System with Collaborative Robot.

Rehabilitation training for patients with motor disabilities usually requires specialized devices in rehabilitation centers. Home-based multi-purpose training would significantly increase treatment accessibility and reduce medical costs. While it is unlikely to equip a set of rehabilitation robots at home, we investigate the feasibility to use the general-purpose collaborative robot for rehabilitation therapies. In this work, we developed a new system for multi-purpose upper-limb rehabilitation training using a generic robot arm with human motor feedback and preference. We integrated surface electromyography, force/torque sensors, RGB-D cameras, and robot controllers with the Robot Operating System to enable sensing, communication, and control of the system. Imitation learning methods were adopted to imitate expert-provided training trajectories which could adapt to subject capabilities to facilitate in-home training. Our rehabilitation system is able to perform gross motor function and fine motor skill training with a gripper-based end-effector. We simulated system control in Gazebo and training effects (muscle activation level) in Open-Sim and evaluated its real performance with human subjects. For all the subjects enrolled, our system achieved better training outcomes compared to specialist-assisted rehabilitation under the same conditions. Our work demonstrates the potential of utilizing collaborative robots for in-home motor rehabilitation training.Clinical relevance-The collaborative robot system is capable of providing safe and effective training comparable to specialized rehabilitation robots, enabling possibilities of convenient rehabilitation training at home.

Analysis of Motor Control and Learning in Human-Robot Interaction during Game Guided Movements.

Robotic devices can be used in upper limb rehabilitation in order to help the total or partial functional recovery. Robots can perform repetitive activities for a long period of time, which may be beneficial for rehabilitation processes. In this context, this study uses a bi-manual robotic device to investigate motor learning and control for the upper limbs among different game guided tasks, and inspect the user's grip force exerted in response to perturbations. The robotic device resembles a bicycle handlebar, instrumented with load cells to measure torques and grip forces. It is equipped with a DC motor to apply external torques to the guiding system. A game was developed containing in-game and physical perturbations to the natural movement of the handlebar. Tests were carried out with 16 healthy subjects that were instructed to move the handlebar guiding a character displayed on the screen with the objective of collecting tokens to get the higher score in the game. During the trials, corresponding data from the game and the load cells were collected and used to infer the learning process, the mean error in the trajectory and the variations in the force applied to the handles of the handlebar. Analyses showed that there was learning in the first repetitions, and the learning was retained further. The higher values of the grip force occurred when there was a physical perturbation to the handlebar's natural movement. The larger errors in the trajectories occurred immediately after the perturbations ended. In conclusion, there was a performance improvement, probably related to learning. The increase of the mean error at the transitions of the perturbations indicates the need for adaptation to the new conditions of the task.

Redundancy Resolution in Trimanual vs. Bimanual Tracking Tasks.

Supernumerary limbs promise to allow users to perform complex tasks that would otherwise require the actions of teams. However, how the user's capability for multimanual coordination compares to bimanual coordination, and how the motor system decides to configure its limb contributions given task redundancy is unclear. We conducted bimanual and trimanual (with the foot as a third-hand controller) virtual reality visuomotor tracking experiments to study how 32 healthy participants changed their limb coordination in response to uninstructed cursor mapping changes. This used a shared cursor mapped to the average limbs' position for different limb combinations. The results show that most participants correctly identified the different mappings during bimanual tracking, and accordingly minimized task-irrelevant motion. Instead during trimanual coordination, participants consistently moved all three limbs concurrently, showing weaker ipsilateral hand-foot coordination. These findings show how redundancy resolution and the resulting coordination patterns differ between similar bimanual and trimanual tasks. Further research is needed to consider the effect of learning on coordination behaviour.

Hybrid Rehabilitation System with Motion Estimation Based on EMG Signals.

Patients with upper limb paralysis undergo various types of rehabilitation to reconstruct upper limb functions necessary for their return to daily life and social activities. Therefore, it is necessary to develop an effective rehabilitation support system using robotic technologies. In this study, we propose an EMG-driven hybrid rehabilitation system based on the estimation of intended motion using a probabilistic neural network. In the proposed system, the developed robot and functional electrical stimulation are controlled by estimating the patient's intention, which enables the intuitive learning of the appropriate control abilities of joint motions and muscle contraction patterns. In the experiments, hybrid and visual feedback training were conducted for pointing movements of the wrist joint of the non-dominant hand. The results confirmed that the proposed method provides effective training and has great potential for use in rehabilitation.

Decoding Upper-Limb Movement Intention Through Adaptive Dynamic Movement Primitives: A Proof-of-Concept Study with a Shoulder-Elbow Exoskeleton.

This work presents an intention decoding algorithm that can be used to control a 4 degrees-of-freedom shoulder-elbow exoskeleton in reaching tasks. The algorithm was designed to assist the movement of users with upper-limb impairments who can initiate the movement by themselves. It relies on the observation of the initial part of the user's movement through joint angle measures and aims to estimate in real-time the phase of the movement and predict the goal position of the hand in the reaching task. The algorithm is based on adaptive Dynamic Movement Primitives and Gaussian Mixture Models. The performance of the algorithm was verified in robot-assisted planar reaching movements performed by one healthy subject wearing the exoskeleton. Tests included movements of different amplitudes and orientations. Results showed that the algorithm could predict the hand's final position with an error lower than 5 cm after 0.25 s from the movement onset, and that the final position reached during the tests was on average less than 4 cm far from the target position. Finally, the effects of the assistance were observed in a reduction of the activation of the Biceps Brachii and of the time to execute the reaching tasks.

Test procedures and positive diagnostic criteria of the upper limb tension tests differ: a systematic review of the DiTA database.

BACKGROUND: The validity of the ULTT is unclear, due to heterogeneity of test procedures and variability in the definition of a positive test OBJECTIVE: To evaluate test procedures and positive diagnostic criteria for the upper limb tension test (ULTT) in diagnostic test accuracy studies. METHODS: A systematic review of diagnostic accuracy studies was performed. We conducted a search of the DiTA (Diagnostic Test Accuracy) database and selected primary studies evaluating the diagnostic accuracy of the ULTT. We assessed risk of bias, performed data extraction on study characteristics, test procedures, and positive diagnostic criteria, and performed a descriptive analysis. RESULTS: We included nine studies (681 participants), four diagnosing people with cervical radiculopathy (CR), four diagnosing people with carpal tunnel syndrome (CTS), and one included both CR and CTS. The risk of bias varied between 2 and 6 out of 6 positive items. Eight studies reported on the ULTT1 (median nerve). Overall, all studies clearly described their test procedures and positive diagnostic criteria although the order of movements and the diagnostic criteria between studies varied. We suggest a more standardised test procedure for the ULTT1 to consist of: 1) stabilising the shoulder in abduction, 2) extending the wrist/fingers, 3) supinating the forearm, 4) externally rotating the shoulder, 5) extending the elbow, and finally 6) performed structural differentiation by side bending (lateral flexion) of the neck. This proposed test procedure should reproduce the symptoms and enables the clinician to evaluate whether symptoms increase/decrease when stressing or relaxing the nerves. CONCLUSION: Based on our findings we proposed a more standardised test procedure for the ULTT1 with accompanying positive diagnostic criteria to facilitate homogeneity in future diagnostic accuracy studies of the ULTT.

Changes in Electromyographic Activity of the Dominant Arm Muscles during Forehand Stroke Phases in Wheelchair Tennis.

The aim of this study was to determine the muscle activations of the dominant arm during the forehand stroke of wheelchair tennis. Five players participated in the present study (age: 32.6 ± 9.9 years; body mass: 63.8 ± 3.12 kg; height: 164.4 ± 1.7 cm). The electrical muscle activity of six dominant arm muscles was recorded using an sEMG system. A significant effect of the muscle's activity was observed, and it was shown that the muscle activation was significantly higher in the execution phase compared to the preparation phase in the anterior deltoid and biceps brachii (34.98 ± 10.23% and 29.13 ± 8.27%, p < 0.001); the posterior deltoid, triceps brachii, flexor carpi radialis, and extensor carpi radialis were higher in the follow-through phase than in the execution phase (16.43 ± 11.72%, 16.96 ± 12.19%, 36.23 ± 21.47% and 19.13 ± 12.55%, p < 0.01). In conclusion, it was determined that the muscle activations of the dominant arm muscles demonstrate variances throughout the phases of the forehand stroke. Furthermore, the application of electromyographic analysis to the primary arm muscles has been beneficial in understanding the muscular activity of the shoulder, elbow, and wrist throughout the various phases of the forehand stroke in wheelchair tennis.