Despite decades of research and development, myoelectric prosthetic hands lack functionality and are often rejected by users. This lack in functionality can be partially attributed to the widely accepted anthropomorphic design ideology in the field; attempting to replicate human hand form and function despite severe limitations in control and sensing technology. Instead, prosthetic hands can be tailored to perform specific tasks without increasing complexity by shedding the constraints of anthropomorphism. In this paper, we develop and evaluate four open-source modular non-humanoid devices to perform the motion required to replicate human flicking motion and to twist a screwdriver, and the functionality required to pick and place flat objects and to cut paper. Experimental results from these devices demonstrate that, versus a humanoid prosthesis, non-humanoid prosthesis design dramatically improves task performance, reduces user compensatory movement, and reduces task load. Case studies with two end users demonstrate the translational benefits of this research. We found that special attention should be paid to monitoring end-user task load to ensure positive rehabilitation outcomes.
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http://dx.doi.org/10.1109/TNSRE.2025.3528725 | DOI Listing |
J Neuroeng Rehabil
March 2025
Department of Biomedical Engineering, Faculty of Engineering, College of Natural and Applied Science, University of Alberta, Edmonton, AB, Canada.
Background: Prosthesis users often rely on vision to monitor the activity of their prosthesis, which can be cognitively demanding. This compensatory visual behaviour may be attributed to an absence of feedback from the prosthesis or the unreliability of myoelectric control. Unreliability can arise from the unpredictable control due to variations in electromyography signals that can occur when the arm moves through different limb positions during functional use.
View Article and Find Full Text PDFJ Neural Eng
March 2025
Electrical and Computer Engineering, University of Tehran College of Engineering, North Kargar Street, Tehran, Tehran, Tehran, 1439957131, Iran (the Islamic Republic of).
Despite remarkable advances in EMG-based hand motor decoding, developing a practical and reliable decoder for robotic prosthetic hands remains unsolved. This study highlights inter-individual, inter-session, and intra-session variabilities of EMG signals as practical challenges and introduces a novel personalized and adaptive motor decoding framework, designed to mitigate their impact and improve hand motor decoding. A dataset was collected from twelve participants (8 male, 4 female), incorporating EMG signals from three forearm muscles during 20 repetitions of 9 distinct hand motions.
View Article and Find Full Text PDFThis study presents a novel deep learning approach for surface electromyography (sEMG) gesture recognition using stacked autoencoder neural network (SAE)s. The method leverages hierarchical representation learning to extract meaningful features from raw sEMG signals, enhancing the precision and robustness of gesture classification.•Feature Extraction and Classification MODWT Decomposition: The sEMG signals were decomposed using the MODWT DECOMPOSITION(Maximal Overlap Discrete Wavelet Transform) to capture various frequency components.
View Article and Find Full Text PDFInt Med Case Rep J
March 2025
Department of Joint and Hand Orthopedics, Hunan University of Medicine General Hospital, Huaihua, Hunan Province, 418000, People's Republic of China.
Purpose: Aseptic loosening (AL) of prostheses is a complex and multi-factorial consequences characterized by nonspecific hip start-up pain, impaired gait, or ambulation. The AL of acetabular components associated with femur prostheses can lead to challenges in accurate diagnosis and suitable therapy, potentially resulting in disaster consequence. This study reported revision of in four cases with AL of acetabular components associated with or without femur prostheses after underwent primary total hip arthroplasty.
View Article and Find Full Text PDFClin Biomech (Bristol)
February 2025
Ludwig Boltzmann Institute for Traumatology, The Research Center in Cooperation with the AUVA, 1200 Vienna, Austria.
Background: Pain, social integration, and walking safely with divided attention challenge people with lower-limb amputation. Tactile feedback systems aim to improve sensations and rehabilitation by facilitating prosthesis utility and embodiment. The non-invasive vibrotactile feedback device Suralis® (Saphenus Medical Technology, Vienna, Austria) aims to improve gait, postural control, and pain treatment.
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