Evaluation of sEMG Signal Features and Segmentation Parameters for Limb Movement Prediction Using a Feedforward Neural Network

Evaluation of sEMG Signal Features and Segmentation Parameters for Limb Movement Prediction Using a Feedforward Neural Network

Limb movement prediction based on surface electromyography (sEMG) for the control of wearable robots, such as active orthoses and exoskeletons, is a promising approach since it provides an intuitive control interface for the user. Further, sEMG signals contain early information about the onset and c...

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Bibliographic Details
Main Authors: David Leserri, Nils Grimmelsmann, Malte Mechtenberg, Hanno Gerd Meyer, Axel Schneider
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Mathematics
Subjects:
limb movement prediction
surface electromyography
EMG
wearable robotics
feature engineering
neural network
Online Access:https://www.mdpi.com/2227-7390/10/6/932

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