Results 51 to 60 of about 39,692 (260)

Movement recognition via channel-activation-wise sEMG attention

Methods, 2023
ABSTRACTContextSurface electromyography (sEMG) signals contain rich information recorded from muscle movements and therefore reflect the user’s intention. sEMG has seen dominant applications in reha-bilitation, clinical diagnosis as well as human engineering, etc.
Jiaxuan Zhang, Yuki Matsuda, Manato Fujimoto, Hirohiko Suwa, Keiichi Yasumoto   +4 more
openaire   +2 more sources

Influence of the quality of sleep on the masticatory muscle activity - a pilot study

Journal of Education, Health and Sport, 2018
Introduction: Modern literature indicates an uptrend in the occurrence of sleep disorders. Currently, about 30-40% of adults are suffering from sleep disorders, which makes them one of the most common health problems of the population.
Grzegorz Zieliński, Aleksandra Byś, Michał Baszczowski, Michał Ginszt, Marta Suwała, Jacek Szkutnik, Piotr Majcher   +6 more
doaj   +1 more source

A quantitative taxonomy of human hand grasps [PDF]

, 2019
Background: A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative ...
Atzori, Manfredo, Cognolato, Matteo, M\ufcller, Henning, Michieletto, Stefano, Pagello, Enrico, Stival, Francesca   +5 more
core   +1 more source

Deep Learning for Prediction of Diaphragm Activity from the Surface Electromyogram

Current Directions in Biomedical Engineering, 2019
The electrical activity of the diaphragm (EAdi) is a novel monitoring parameter for patients under assisted ventilation and is used for assessing the patient’s neural respiratory drive. It is recorded by an array of electrodes placed inside the esophagus
Bockelmann Niclas, Graßhoff Jan, Hansen Lasse, Bellani Giacomo, Heinrich Mattias P., Rostalski Philipp   +5 more
doaj   +1 more source

sEMG-Based Gesture Classifier for a Rehabilitation Glove

Frontiers in Neurorobotics, 2022
Human hand gesture recognition from surface electromyography (sEMG) signals is one of the main paradigms for prosthetic and rehabilitation device control. The accuracy of gesture recognition is correlated with the control mechanism. In this work, a new classifier based on the Bayesian neural network, pattern recognition networks, and layer recurrent ...
Dorin Copaci, Janeth Arias, Marcos Gómez-Tomé, Luis Moreno, Dolores Blanco   +4 more
openaire   +4 more sources

E-textile based modular sEMG suit for large area level of effort analysis

Scientific Reports, 2022
We present a novel design for an e-textile based surface electromyography (sEMG) suit that incorporates stretchable conductive textiles as electrodes and interconnects within an athletic compression garment.
K. Ohiri, C. Pyles, Leslie Hamilton, Megan M. Baker, Matthew McGuire, Eric Q Nguyen, Luke E. Osborn, Katelyn M Rossick, Emil G. McDowell, Leah M Strohsnitter, L. Currano   +10 more
semanticscholar   +1 more source

Surface Electromyography Normalization Affects the Interpretation of Muscle Activity and Coactivation in Children With Cerebral Palsy During Walking

Frontiers in Neurology, 2020
Investigating muscle activity and coactivation with surface electromyography (sEMG) gives insight into pathological muscle function during activities like walking in people with neuromuscular impairments, such as children with cerebral palsy (CP).
Yngvild Gagnat, Yngvild Gagnat, Siri Merete Brændvik, Siri Merete Brændvik, Karin Roeleveld, Karin Roeleveld   +5 more
doaj   +1 more source

Near Real-Time Data Labeling Using a Depth Sensor for EMG Based Prosthetic Arms

, 2018
Recognizing sEMG (Surface Electromyography) signals belonging to a particular action (e.g., lateral arm raise) automatically is a challenging task as EMG signals themselves have a lot of variation even for the same action due to several factors.
A Vakkuri, C Frigo, CJ Luca De, D Blana, H Hermens, HM Al-Angari, M Solomonow, N Golyandina, R Vautard, RH Chowdhury, WMBW Daud   +10 more
core   +1 more source

Detecting muscle fatigue among community-dwelling senior adults with shape features of the probability density function of sEMG

Journal of NeuroEngineering and Rehabilitation
Physical exercise is an important method for both the physical and mental health of the senior population. However, excessive exertion can lead to increased risks of falls, severe injuries, and diminished quality of life.
Jiarui Ou, Na Li, Haoru He, Jiayuan He, Le Zhang, Ning Jiang   +5 more
semanticscholar   +1 more source

Exploration of a machine learning approach for diagnosing sarcopenia among Chinese community-dwelling older adults using sEMG-based data

Journal of NeuroEngineering and Rehabilitation
In the practical application of sarcopenia screening, there is a need for faster, time-saving, and community-friendly detection methods. The primary purpose of this study was to perform sarcopenia screening in community-dwelling older adults and ...
Na Li, Jiarui Ou, Haoru He, Jiayuan He, Le Zhang, Zhengchun Peng, Junwen Zhong, Ning Jiang   +7 more
semanticscholar   +1 more source