Zobrazeno 1 - 10
of 1 124
pro vyhledávání: '"Surface Electromyography sEMG"'
Publikováno v:
Journal of Informatics and Web Engineering, Vol 3, Iss 3, Pp 121-132 (2024)
Muscle fatigue, a key concern in sports science, rehabilitation, and occupational health, influences performance, injury risk, and provides insights into muscle functionality and endurance. Surface electromyography (sEMG) has emerged as a vital tool
Externí odkaz:
https://doaj.org/article/3e8c7ea1dc74489a90b4ace254d214d5
Publikováno v:
Frontiers in Neurology, Vol 15 (2024)
Externí odkaz:
https://doaj.org/article/758969629c4b4d17b0df22c150069643
Publikováno v:
Frontiers in Rehabilitation Sciences, Vol 5 (2024)
IntroductionSurface electromyography (sEMG) is a non-invasive technique that records muscle electrical activity using skin-surface electrodes, aiding physiotherapists in assessing and treating muscular and neuromuscular conditions. Despite its potent
Externí odkaz:
https://doaj.org/article/69570338dbc74e4ab1d846b984bbc3d6
Publikováno v:
Orthopaedic Surgery, Vol 16, Iss 3, Pp 724-732 (2024)
Objective Spinal endoscopy radiofrequency is a minimally invasive technique for lumbar disc herniation (LDH) and low back pain (LBP). However, recurring LDH/LBP following spinal endoscopy radiofrequency is a significant problem. Paravertebral muscula
Externí odkaz:
https://doaj.org/article/ae13f774486b4a4587721be089864950
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 3577-3589 (2024)
Decoding continuous human motion from surface electromyography (sEMG) in advance is crucial for improving the intelligence of exoskeleton robots. However, incomplete sEMG signals are prevalent on account of unstable data transmission, sensor malfunct
Externí odkaz:
https://doaj.org/article/07d40ec6468d4ef792c66bb67d920c6c
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 1487-1504 (2024)
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
Externí odkaz:
https://doaj.org/article/d6f560cf77ce4b428ecf9e0a0deafe49
Autor:
Yunus Bicer, Niklas Smedemark-Margulies, Basak Celik, Elifnur Sunger, Ryan Orendorff, Stephanie Naufel, Tales Imbiriba, Deniz Erdogmus, Eugene Tunik, Mathew Yarossi
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 1187-1197 (2024)
We designed and tested a system for real-time control of a user interface by extracting surface electromyographic (sEMG) activity from eight electrodes in a wristband configuration. sEMG data were streamed into a machine-learning algorithm that class
Externí odkaz:
https://doaj.org/article/b2eafb41fcf54b5fae54118a4c4736f0
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 102-111 (2024)
Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on the wrist is more comfortable for general consumers because of its unobtrusiveness and incorporation with the existing wrist-based wearables. Recently, deep
Externí odkaz:
https://doaj.org/article/2e9dc195553747498833f2322de1ea47
Autor:
Riccardo Fratti, Niccolò Marini, Manfredo Atzori, Henning Müller, Cesare Tiengo, Franco Bassetto
Publikováno v:
Sensors, Vol 24, Iss 22, p 7147 (2024)
Advancements in neural network approaches have enhanced the effectiveness of surface Electromyography (sEMG)-based hand gesture recognition when measuring muscle activity. However, current deep learning architectures struggle to achieve good generali
Externí odkaz:
https://doaj.org/article/42312ffaeec644c69e50904778467c6e
Autor:
XU Qing
Publikováno v:
Zhiye weisheng yu yingji jiuyuan (2024)
Externí odkaz:
https://doaj.org/article/a27f4f0bc775424296916ce7d94464a9