This review article presents an in-depth examination of research and development in the fields of rehabilitation, assistive technologies, and humanoid robots. It focuses on parallel robots designed for human body joints with three degrees of freedom, specifically the neck, shoulder, wrist, hip, and ankle. A systematic search was conducted across multiple databases, including Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, the Directory of Open Access Journals, and the ASME Journal. This systematic review offers an updated overview of advancements in the field from 2012 to 2023. After applying exclusion criteria, 93 papers were selected for in-depth review. This cohort included 13 articles focusing on the neck joint, 19 on the shoulder joint, 22 on the wrist joint, 9 on the hip joint, and 30 on the ankle joint. The article discusses the timeline and advancements of parallel robots, covering technology readiness levels (TRLs), design, the number of degrees of freedom, kinematics structure, workspace assessment, functional capabilities, performance evaluation methods, and material selection for the development of parallel robotics. It also examines critical technological challenges and future prospects in rehabilitation, assistance, and humanoid robots.

This review article aims to provide an updated and comprehensive overview of the latest trends in adult upper limb prostheses, specifically targeting various amputation levels such as transradial, transmetacarpal, transcarpal, and transhumeral. A systematic search was conducted across multiple databases, including IEEE Xplore, MDPI, Scopus, Frontiers, and Espacenet, covering from 2018 to 2023. After applying exclusion criteria, 49 scientific articles (33 patents and 16 commercial prostheses) were meticulously selected for review. The article offers an in-depth analysis of several critical aspects of upper limb prostheses. It discusses the evolution and current state of input control mechanisms, the number of degrees of freedom, and the variety of grips available in prostheses, all tailored according to the level of amputation. Additionally, the review delves into the selection of materials used in developing these prostheses and examines the progression of technology readiness levels. A significant focus is also placed on the evolution of prosthesis weight over the years for different amputation levels. Moreover, the review identifies and explores critical technological challenges and prospects in upper limb prostheses. Finally, the article culminates with a conclusion that encapsulates the key findings and insights on the advancements and ongoing developments in this field.

Despite recent advancements in prosthetic technology, lower-limb amputees often remain limited to passive prostheses, which leads to an asymmetric gait and increased energy expenditure. Developing active prostheses with effective control systems is important to improve mobility for these individuals. This study presents a machine-learning-based approach to classify five distinct locomotion tasks: ground-level walking (GWL), ramp ascent (RPA), ramp descent (RPD), stairs ascent (SSA), and stairs descent (SSD). The dataset comprises fused electromyographic (EMG) and inertial measurement unit (IMU) signals from twenty non-amputated and five transtibial amputated participants. EMG sensors were strategically positioned on the thigh muscles, while IMU sensors were placed on various leg segments. The performance of two classification algorithms, support vector machine (SVM) and long short-term memory (LSTM), were evaluated on segmented data. The results indicate that SVM models outperform LSTM models in accuracy, precision, and F1 score in the individual evaluation of amputee and non-amputee datasets for 80–20 and 50–50 data distributions. In the 80–20 distribution, an accuracy of 95.46% and 95.35% was obtained with SVM for non-amputees and amputees, respectively. An accuracy of 93.33% and 93.30% was obtained for non-amputees and amputees by using LSTM, respectively. LSTM models show more robustness and inter-population generalizability than SVM models when applying domain-adaptation techniques. Furthermore, the average classification latency for SVM and LSTM models was 19.84 ms and 37.07 ms, respectively, within acceptable limits for real-time applications. This study contributes to the field by comprehensively comparing SVM and LSTM classifiers for locomotion tasks, laying the foundation for the future development of real-time control systems for active transtibial prostheses.

To assist an individual with an amputation in regaining daily quality of life, a 2SPU-RU type parallel mechanism was developed based on ankle biomechanics. The inverse kinematic analysis of this mechanism was performed using the vector method. Subsequently, the Jacobian matrices were analyzed. The dynamic model of the mechanism was then created based on the principle of virtual work, and its theoretical solution was compared with numerical results obtained in a simulation environment. Additionally, the validity of the dynamic model and the inverse kinematics was verified by comparing theoretical and simulation results for the movements of plantarflexion–dorsiflexion, eversion–inversion, and abduction–adduction during the gait cycle.

Background: Restoring hand functionality is critical for fostering independence in individuals with neurological disorders. Various therapeutic approaches have emerged to address motor function restoration, with music-based therapies demonstrating notable advantages in enhancing neuroplasticity, an integral component of neurorehabilitation. Despite the positive effects observed, there remains a gap in the literature regarding implementing music treatments in neurorehabilitation, such as Neurologic Music Therapy (NMT), especially in conjunction with emerging fields like wearable devices and game-based therapies. Methods: A literature search was conducted in various databases, including PubMed, Scopus, IEEE Xplore, and ACM Digital Library. The search was performed using a literature search methodology based on keywords. Information collected from the studies pertained to the approach used in music therapy, the design of the video games, and the types of wearable devices utilized. Results: A total of 158 articles were found, including 39 from PubMed, 34 from IEEE Xplore, 48 from Scopus, 37 from ACM Digital Library, and 35 from other sources. Duplicate entries, of which there were 41, were eliminated. In the first screening phase, 152 papers were screened for title and Subsequently, 89 articles were removed if they contained at least one exclusion criterion. Sixteen studies were considered after 63 papers had their full texts verified. Conclusions: The convergence of NMT with emerging fields, such as gamification and wearable devices designed for hand functionality, not only expands therapeutic horizons but also lays the groundwork for innovative, personalized approaches to neurorehabilitation. However, challenges persist in effectively incorporating NMT into rehabilitation programs, potentially hindering its effectiveness.

This study presents the design exploration and kinematic validation of a transtibial prosthesis based on a 2SPU-RU parallel mechanism. The prototype is currently at Technology Readiness Level 3 (TRL 3), indicating an early-stage concept that has been evaluated under controlled conditions. The mechanism replicates dorsiflexion–plantarflexion, inversion–eversion, and abduction–adduction, corresponding to ankle motion in the sagittal, frontal, and transverse anatomic planes. The system integrates electric actuators and an ESP32 DevKit V1 microcontroller to control joint movements. Functional tests were conducted to assess kinematic performance using inertial sensors and video tracking. Additional evaluations included force distribution analysis using pressure insoles during dorsiflexion and plantarflexion, as well as energy consumption measurements across gait cycles. While the prototype demonstrates the ability to reproduce fundamental gait patterns in a suspended setup, limitations in torque, speed, and control precision restrict its current applicability. These findings provide a foundation for further development. Future work will focus on improving actuator performance, refining control strategies, and extending validation to real-world scenarios and amputee trials.