Title
Advanced biofeedback from surface electromyography signals using fuzzy system.
Abstract
The aims of this study were to develop a fuzzy inference-based biofeedback system and investigate its effects when inducing active (shoulder elevation) and passive (relax) pauses on the trapezius muscle electromyographic (EMG) activity during computer work. Surface EMG signals were recorded from clavicular, descending (bilateral) and ascending parts of the trapezius muscles during computer work. The fuzzy system readjusted itself based on the history of previous inputs. The effect of feedback was assessed in terms of muscle activation regularity and amplitude. Active pause resulted in non-uniform muscle activity changes in the trapezius muscle depicted by increase and decrease of permuted sample entropy in ascending and clavicular parts of trapezius, respectively (P < 0.05) compared with no pause. Concomitantly, the normalized root mean square of EMG increased approximately 5% in descending part of trapezius bilaterally (P < 0.01). These findings confirm that advanced feedback can change the pattern of muscle activation.
Year
DOI
Venue
2010
10.1007/s11517-010-0651-9
Med. Biol. Engineering and Computing
Keywords
Field
DocType
fuzzy system,root mean square
Muscle activity,Anatomy,Sample entropy,Artificial intelligence,Physical medicine and rehabilitation,Fuzzy control system,Computer vision,Fuzzy inference,Electromyography,Muscle activation,Biofeedback,Mathematics,Trapezius muscle
Journal
Volume
Issue
ISSN
48
9
1741-0444
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
Afshin Samani171.96
A Holtermann240.98
Karen Søgaard300.34
Pascal Madeleine4184.30