Search Results (156)

Upper extremity amputations significantly impact an individual’s physical capabilities, psychosocial well-being, and overall quality of life. The level at which an amputation is performed influences residual limb function, prosthetic compatibility, and long-term patient satisfaction. While surgical guidelines traditionally emphasize maximal limb preservation, prosthetists often advocate for amputation sites that optimize prosthetic fit and function, highlighting the need for a collaborative approach. This review examines the discrepancies between surgical and prosthetic recommendations for optimal amputation levels, from digit amputations to shoulder disarticulations, and explores their implications for prosthetic design, functionality, and patient outcomes. Various prosthetic options, including passive functional, body-powered, myoelectric, and hybrid devices, offer distinct advantages and limitations based on the level of amputation. Prosthetists emphasize the importance of residual limb length, not only for mechanical efficiency but also for achieving symmetry with the contralateral limb, minimizing discomfort, and enhancing control. Additionally, emerging technologies such as targeted muscle reinnervation (TMR) and advanced myoelectric prostheses are reshaping rehabilitation strategies, further underscoring the need for precise amputation planning. By integrating insights from both surgical and prosthetic perspectives, this review highlights the necessity of a multidisciplinary approach involving surgeons, prosthetists, rehabilitation specialists, and patients in the decision-making process. A greater emphasis on preoperative planning and interprofessional collaboration can improve prosthetic outcomes, reduce device rejection rates, and ultimately enhance the functional independence and well-being of individuals with upper extremity amputations. Full article

The development of wearable robotic exoskeletons has seen rapid progress in recent years, driven by the growing need for technologies that support motor rehabilitation, assist individuals with physical impairments, and enhance human capabilities in both clinical and everyday contexts. Within this field, elbow exoskeletons have emerged as a key focus due to the joint’s essential role in upper limb functionality and its frequent impairment following neurological injuries such as stroke. With increasing research activity, there is a strong interest in evaluating these systems not only from a technical perspective but also in terms of user comfort, adaptability, and clinical relevance. This review investigates recent advancements in elbow exoskeleton technology, evaluating their effectiveness and identifying key design challenges and limitations. Devices are categorized based on three main criteria: mechanical structure (rigid, soft, or hybrid), actuation method, and sensing technologies. Additionally, the review classifies systems by their supported range of motion, flexion–extension, supination–pronation, or both. Through a systematic analysis of these features, the paper highlights current design trends, common trade-offs, and research gaps, aiming to guide the development of more practical, effective, and accessible elbow exoskeletons. Full article

Manual wheelchair users are at high risk of upper limb overuse injuries due to repetitive propulsion mechanics. To address this, we developed a novel detachable push–pull dual-propulsion device that enables both forward and backward propulsion, aiming to reduce shoulder strain and promote balanced muscle engagement. This study presents a protocol to evaluate the device’s biomechanical impact and ergonomic effects, focusing on objective, quantitative analysis using a repeated-measures within-subject design. Thirty participants with spinal cord injury will perform standardized propulsion trials under two conditions: push and pull. Motion capture and surface electromyography (EMG) will assess upper limb kinematics and muscle activation. Each propulsion mode will be repeated over a 10-m track, and maximum voluntary contraction (MVC) data will be collected for EMG normalization. The protocol aims to provide objective evidence on the propulsion efficiency, muscle distribution, and ergonomic safety of the device. Findings will inform future assistive technology development and rehabilitation guidelines for manual wheelchair users. Full article

Accessible tools for post-stroke motor rehabilitation are critically needed to promote recovery beyond clinical settings. This pilot study evaluated the impact of a posture correction intervention using the Postural SmartVest, a wearable device that delivers multisensory feedback via a smartphone app. Forty individuals with post-stroke hemiparesis participated in a single supervised session, during which each patient completed the same four-phase functional protocol: multidirectional walking, free walking toward a refrigerator, an upper-limb reaching and object-handling task, and walking back to the starting point. Under the supervision of their therapists, each patient performed the full protocol twice—first without feedback and then with feedback—which allowed within-subject comparisons across multiple metrics, including upright posture duration, number and frequency of posture-related events, and temporal distribution. Additional analyses explored associations with demographic and clinical variables and identified predictors through regression models. Wilcoxon signed-rank and Mann–Whitney U tests showed significant improvements with feedback, including an increase in upright posture time ($p<0.001$), an increase in the frequency of upright posture events ($p<0.001$), and a decrease in the total task time ($p=0.038$). No significant subgroup differences were found for age, sex, lateralization, or stroke chronicity. Regression models did not identify significant predictors of improvement. Full article

Upper-limb impairments after stroke significantly affect patients’ quality of life and require effective rehabilitation strategies. Rehabilitation devices play a vital role in enhancing motor recovery. This study evaluated the efficacy of the Arm Booster, a bilateral arm-training device, in improving upper-limb impairment in patients with chronic stroke. Eighteen participants were randomly assigned to two groups: a device group (n = 9), using the Arm Booster; and a conventional physiotherapy group (n = 9). Both groups performed six bilateral upper-limb exercises (32 repetitions each) three times per week for eight weeks. Participants were further classified into mild spasticity (n = 5) and moderate-to-severe spasticity (n = 4) subgroups. The primary outcome was motor impairment, assessed using the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE). Secondary outcomes included spasticity, measured by the Modified Ashworth Scale (MAS), and daily functional use of the arm, assessed with the Motor Activity Log (MAL). Both groups showed significant improvements in FMA-UE scores and overall arm movement. The conventional group demonstrated additional gains in hand and wrist function and coordination. Notably, in the moderate-to-severe spasticity subgroup, the device group exhibited improvements in upper-limb movement and a trend toward reduced spasticity. These findings suggest that the Arm Booster may support motor recovery, encourage the use of the affected arm, improve movement control, and provide an efficient means for patients to exercise more frequently on their own. Full article

Rotator cuff tears are common in individuals over 40, and physical therapy is often prescribed post-surgery. However, access can be limited by cost, convenience, and insurance coverage. CuffLink is a telehealth rehabilitation system that integrates the Strengthening and Stabilization System mechanical exerciser with the interACTION mobile health platform. The system includes a triple-axis accelerometer (LSM6DSOX + LIS3MDL FeatherWing), a rotary encoder, a VL530X time-of-flight sensor, and two wearable BioMech Health IMUs to capture upper-limb motion. CuffLink is designed to facilitate controlled, home-based exercise while enabling clinicians to remotely monitor joint function. Concurrent validity and test–retest reliability were used to assess device accuracy and repeatability. The results showed moderate to good validity for shoulder rotation (ICC = 0.81), device rotation (ICC = 0.94), and linear tracking (from zero: ICC = 0.75 and RMSE = 2.41; from start: ICC = 0.88 and RMSE = 2.02) and good reliability (e.g., RMSEs as low as 1.66 cm), with greater consistency in linear tracking compared to angular measures. Shoulder rotation and abduction exhibited higher variability in both validity and reliability measures. Future improvements will focus on manufacturability, signal stability, and force sensing. CuffLink supports accessible, data-driven rehabilitation and holds promise for advancing digital health in orthopedic recovery. Full article

A prototype device was developed as a simple yet effective tool for the rehabilitation of individuals with upper limb paresis resulting from stroke. The primary objective of the design process was to create a portable rehabilitation device that could be remotely controlled by a therapist via a Bluetooth protocol. The device enables the execution of upper limb rehabilitation exercises and integrates essential modules for assessment, reporting, and user feedback (biofeedback). It comprises a base and three movable arms, each fitted with a container at its distal end. The central arm, positioned at the midpoint of the device’s housing, holds a storage container from which specific objects are retrieved by the user. This arm features an adjustable reach. The remaining two arms are equipped with task-specific containers mounted at their ends. The conceptual framework is based on the execution of various tasks displayed on a screen. The user retrieves objects from the central storage unit and places them into either the left or right container, as indicated. The target container is highlighted both visually on the screen and via an illuminated LED indicator. Pre-programmed sequences for object retrieval and placement are presented on the display, offering clear guidance for the correct positioning and ordering of blocks within the designated containers. The device includes 12 dedicated blocks varying in shape, colour, material, and texture. A mechatronic control system governs the container positioning and arm inclination, enabling a precise adjustment of range of movement according to the exercise’s requirements. A dedicated software system has also been developed for control and management. Functional testing of the prototype was conducted to assess the device’s effectiveness and practical applicability in rehabilitation settings. Full article

This publication aims to present the preliminary results of research on an innovative device designed to support the rehabilitation of drivers with neurological disorders, developed as part of a multidisciplinary project. The device was designed for individuals recovering from neurological diseases, injuries, and COVID-19-related complications, who experience difficulties with coordination and the speed of performing motor exercises. Its goal is to improve the quality of life for patients and increase their chances of safely driving vehicles, which also contributes to the safety of all road users. The device allows for controlled upper limb exercises using a diagnostic module, exercise program, and biofeedback system. The main component is a mechatronic driving simulator, enhanced with dedicated software to support the rehabilitation of individuals with neurological disorders and older adults. Through driving simulations and rehabilitation tasks, patients perform exercises that improve their health, facilitating a faster recovery. The innovation of the solution is confirmed by a submitted patent application, and preliminary research results indicate its effectiveness in rehabilitation and improving mobility for individuals with neurological disorders. Full article

To address the precision challenges in upper-limb joint motion prediction, this study proposes a novel artificial neural network (COANN) enhanced by the Cheetah Optimization Algorithm (COA). The model integrates surface electromyography (sEMG) signals with joint angle data through multi-source information fusion, effectively resolving the local optima issue in neural network training and improving the accuracy limitations of single sEMG predictions. Experimental results demonstrate that the COANN achieves significant performance improvements: compared with RBF neural networks, it reduces the root mean square error (RMSE) by 24.32% (ΔR² + 18.75%) with a 22.6% shorter system runtime; relative to conventional ANNs, it decreases the RMSE by 31.59% (ΔR² + 12.15%) while reducing computational time by 35.1%; compared with CNN neural networks, it reduces the root mean square error (RMSE) by 14.9% (ΔR² + 3.84%); and relative to conventional LSTM, it decreases the RMSE by 15.31% (ΔR² + 4.86%). Multi-source integration enhanced elbow joint prediction accuracy by 5.7% and shoulder joint accuracy by 6.9% compared with single sEMG approaches. This methodology provides theoretical foundations for human–robot interaction systems in upper-limb rehabilitation robotics and motion-assistive devices. Full article

Recovering from upper limb injuries is very important because having limited functionality affects everyday tasks. Rehabilitation supporting systems significantly impact the results; however, it is important to ensure that they are safe and accurate. This study addressed friction forces and gravity on the movement quality of a mechatronic rehabilitation device (MWR) for the upper limb. At first, an experimental analysis was conducted to quantify the active torque required to maintain specific angular positions. The results revealed the significant impact of the mass of mechanical components and friction between moving parts on the device’s movement quality. To address these issues, friction and gravity compensation functions were derived empirically and integrated into the control system’s algorithm. Implementing these compensation functions resulted in a substantial improvement in movement quality, as demonstrated by a reduction of over 50% in the integral of the absolute position error. These results underscore the importance of physical constraints in the control design of rehabilitation devices and provide a foundation for developing adaptive rehabilitation technologies that enhance therapeutic outcomes. Full article

This paper explores the design, control, construction, and leading manufacturers of upper limb rehabilitation robots through a thorough literature review. Utilizing databases such as Scopus, IEEE Xplore, Science Direct, Springer Link, and the Clinical Trials database, the research adhered to a rigorous screening process in accordance with PRISMA guidelines. This included analyzing abstracts and conducting comprehensive reviews of full articles when necessary. A total of fourteen relevant papers were systematically selected for in-depth analysis. The study offers a detailed classification of robotic technologies along with their Technology Readiness Levels (TRLs), discusses the primary challenges hindering their adoption, and proposes strategic research directions to address these issues. In conclusion, while upper limb robotic devices exhibit significant potential, persistent technological and design challenges must be addressed, underscoring the need for ongoing research and multidisciplinary collaboration to facilitate broader and more effective adoption. Full article

(1) Background: Patients bedridden due to accidental injuries, diseases, or age-related functional impairments require accelerated recovery of autonomous limb movement. A prone-position rehabilitation training device was developed to provide training intensity tailored to patients’ motor capabilities. (2) Methods: Based on principles of human prone limb motion mechanics and torque balance, this study analyzed joint torque during limb movements using optical motion capture and six-dimensional force plate data. Joint torque curves during prone-position training were simulated, and a prototype device was developed. Prototype assembly and experimental validation of device–human synergy was conducted. (3) Results: Comparative analysis of joint torques between healthy individuals and patients revealed that joint torque increases as limbs contract inward. The maximum torque for upper limb joints was approximately 3.5 Nm, while the knee joint torque reached around 40 Nm. (4) Conclusions: Prototype testing confirmed the device’s design rationality, meeting human–machine synergy and rehabilitation training intensity requirements. This study provides a reference for the design of prone-position rehabilitation training devices. Full article

Two primary challenges in controlling robotic rehabilitation devices are the uncertainties in dynamic models and, more importantly, the need for controllers capable of adapting to external disturbances due to human–robot interaction. To address these issues, this paper proposes the particle swarm optimization (PSO) algorithm for the real-time gain tuning in the sliding mode controller (SMC) based on the exponential reaching law (ERL). The proposed approach was designed for a seven-degrees-of-freedom (DOF) robotic exoskeleton used in upper-limb physical rehabilitation. The optimization algorithm aims to minimize tracking errors in rehabilitation exercises through the robust ERL controller applied to nonlinear systems with external disturbances. The proposed method was validated through experimental tests conducted on two healthy subjects, and the outcomes indicated a reduction of over 20% in tracking errors compared to heuristically tuned gains. Mathematical analyses of dynamic modeling and algorithm convergence are shown. Full article

Mechanomyography (MMG) is a non-invasive technique for assessing muscle activity by measuring mechanical signals, offering high sensitivity and real-time monitoring capabilities, and it has many applications in rehabilitation training. Traditional MMG-based motion recognition relies on feature extraction and classifier training, which require segmenting continuous actions, leading to challenges in real-time performance and segmentation accuracy. Therefore, this paper proposes an innovative method for the real-time segmentation and classification of upper limb rehabilitation actions based on the You Only Look Once (YOLO) algorithm, integrating the Squeeze-and-Excitation (SE) attention mechanism to enhance the model’s performance. In this paper, the collected MMG signals were transformed into one-dimensional time-series images. After image processing, the training set and test set were divided for the training and testing of the YOLOv5s-SE model. The results demonstrated that the proposed model effectively segmented isolated and continuous MMG motions while simultaneously performing real-time motion category prediction and outputting results. In segmentation tasks, the base YOLOv5s model achieved 97.9% precision and 98.0% recall, while the improved YOLOv5s-SE model increased precision to 98.7% (+0.8%) and recall to 98.3% (+0.3%). Additionally, the model demonstrated exceptional accuracy in predicting motion categories, achieving an accuracy of 98.9%. This method realizes the automatic segmentation of time-domain motions, avoids the limitations of manual parameter adjustment in traditional methods, and simultaneously enhances the real-time performance of MMG motion recognition through image processing, providing an effective solution for motion analysis in wearable devices. Full article

Background/Objectives: Thrombocytopenia–absent radius (TAR) syndrome is a rare genetic disorder characterized by the bilateral absence of the radius and thrombocytopenia, often leading to functional limitations and gait asymmetries. Prosthetic devices are sometimes employed to improve mobility and posture, but their impact on gait mechanics in pediatric patients remains poorly understood. Methods: The methodology used is based on a study that evaluated the gait parameters of a 10-year-old child with TAR syndrome under static and dynamic conditions, both with and without the use of a custom-designed upper limb prosthesis. The analysis focused on assessing the prosthesis’s impact on gait symmetry and biomechanics. A key aspect of the methodology involved studying the distribution of pressure forces on the ground during walking using the FreeMed EXTREME Maxi baropodometric platform. Results: Gait analysis demonstrated asymmetries between the left and right feet. In the absence of the prosthesis, the patient exhibited excessive forward loading and uneven pressure distributions. The use of a custom prosthesis, particularly with counterbalancing features, improved gait symmetry but led to increased reliance on the left foot. This foot experienced higher pressures (738–852 g/cm²) and longer ground contact times (690–865 ms) compared to the right foot (619–748 g/cm² and 673–771 ms). The left foot displayed elevated forefoot pressures (61–65%), while the right foot bore weight laterally (66–74%). Conclusions: The custom prosthesis influenced gait mechanics by redistributing plantar pressures and modifying ground contact times, partially improving gait symmetry. However, compensatory strategies, such as increased loading on the left foot, could contribute to musculoskeletal strain over time. Individualized rehabilitation programs and prosthetic designs are essential for optimizing gait mechanics, improving mobility, and minimizing long-term complications in TAR syndrome patients. Full article