Latent Factors Limiting the Performance of sEMG-Interfaces

Latent Factors Limiting the Performance of sEMG-Interfaces

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 relatively high mean performance, sEMG-interf...

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Bibliographic Details
Main Authors: Sergey Lobov, Nadia Krilova, Innokentiy Kastalskiy, Victor Kazantsev, Valeri A. Makarov
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Sensors
Subjects:
electromyography
human–computer interface
motor control
pattern classification
artificial neural networks
Online Access:http://www.mdpi.com/1424-8220/18/4/1122

Internet

http://www.mdpi.com/1424-8220/18/4/1122

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