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http://dx.doi.org/10.1097/jpo.0000000000000482 | DOI Listing |
J Prosthet Orthot
July 2024
Department of Bioengineering, George Mason University, Fairfax, VA.
Impairment of hand functions in individuals with spinal cord injury (SCI) severely disrupts activities of daily living. Recent advances have enabled rehabilitation assisted by robotic devices to augment the residual function of the muscles. Traditionally, electromyography-based muscle activity sensing interfaces have been utilized to sense volitional motor intent to drive robotic assistive devices.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
November 2023
Accurate hand motion intention recognition is essential for the intuitive control of intelligent prosthetic hands and other human-machine interaction systems. Sonomyography, which can detect the changes in muscle morphology and structure precisely, is a promising signal source for fine hand movement recognition. However, sonomyography measured by traditional rigid ultrasound probes may suffer from poor acoustic coupling because the rigid probe surfaces cannot accommodate the curvilinear shape of the human body, particularly in the case of small and irregular residual limbs in amputees.
View Article and Find Full Text PDFSci Rep
August 2023
Department of Bioengineering, George Mason University, Fairfax, VA, 22030, USA.
There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging.
View Article and Find Full Text PDFRes Sq
May 2023
Department of Bioengineering, George Mason University, Fairfax VA, 22030, USA.
There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging.
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