Results 111 to 120 of about 19,737 (228)

Data description regarding sEMG activity in each study, in relation to exercise type and normalized sEMG activation expressed as % peak RMS.

, 2020
Data description regarding sEMG activity in each study, in relation to exercise type and normalized sEMG activation expressed as % peak RMS.
José M. Oliva-Lozano (8501226), José M. Muyor (6843389), Isabel Martín-Fuentes (6843395)   +2 more
core   +1 more source

Motion intention recognition of the affected hand based on the sEMG and improved DenseNet network

Heliyon
The key to sEMG (surface electromyography)-based control of robotic hands is the utilization of sEMG signals from the affected hand of amputees to infer their motion intentions.
Qunfeng Niu, Lei Shi, Yang Niu, Kunming Jia, Guangxiao Fan, Ranran Gui, Li Wang   +6 more
doaj   +1 more source

Motion intention estimation of lower limbs based on sEMG supplement with acceleration signal

, 2015
Lower extremity exoskeleton robot can assist the person standing and walking which are important functions for the disabled or old people who can not make move by themselves.
Ye D(叶丹), Zhao XG(赵新刚), Wang, Rui   +2 more
core  

sEMG data

RMS of sEMG data for patient with chronic non-specific neck pain when doing resistance exercise in six directions under four ...
Bai, Yiwen
core   +1 more source

The Application of Surface Electromyography Technology in Evaluating Paraspinal Muscle Function

Diagnostics
Surface electromyography (sEMG) has emerged as a valuable tool for assessing muscle activity in various clinical and research settings. This review focuses on the application of sEMG specifically in the context of paraspinal muscles.
Moran Suo, Lina Zhou, Jinzuo Wang, Huagui Huang, Jing Zhang, Tianze Sun, Xin Liu, Xin Chen, Chunli Song, Zhonghai Li   +9 more
doaj   +1 more source

A comparative study of denoising sEMG signals

, 2015
0Denoising of surface electromyography (sEMG) signals plays a vital role in sEMG-based mechatronics applications and diagnosis of muscular diseases. In this study, 3 different denoising methods of sEMG signals, empirical mode decomposition, discrete ...

core  

Latent Factors Limiting the Performance of sEMG-Interfaces

, 2018
Recent advances in recording and real-time analysis of surface electromyographic signals (sEMG) have fostered the use of sEMG human-machine interfaces for controlling personal computers, prostheses of upper limbs, and exoskeletons among others. Despite a
Valeri A. Makarov, Nadia Krilova, Innokentiy Kastalskiy, Sergey Lobov, Victor Kazantsev   +4 more
core   +1 more source

Six raw signal based sEMG image representation methods.

, 2018
Six raw signal based sEMG image representation methods.
Wentao Wei (2135263), Weidong Geng (5858237), Yu Hu (126677), Yongkang Wong (5384011), Yu Du (618167), Mohan Kankanhalli (5524991)   +5 more
core   +1 more source

Printed matrices for surface electromyography: acquisition, denoising techniques and influence of geometrical parameters

, 2022
openLo scopo dell’elettromiografia di superficie (sEMG) è quello di prelevare, condizionare ed elaborare i segnali biologici che riguardano nello specifico l’attività muscolare.
COSTA, PIETRO
core  

Surface electromyographic biofeedback versus neuromuscular electrical stimulation for post-stroke dysphagia: a systematic review and network meta-analysis

Frontiers in Neurology
BackgroundPost-stroke dysphagia (PSD) is a common complication with a high incidence rate, significantly impairing patients’ quality of life and health.
Na Li, Qianqian Jin, Yi Zhang, Li Zhang, Xiapei Peng   +4 more
doaj   +1 more source