Paper Info
Title
Muscle Fatigue Assessment Through Electrodermal Activity Analysis During Isometric Contraction
Abstract
We studied the effects of muscle fatigue on the Autonomic Nervous System (ANS) dynamics. Specifically, we monitored the electrodermal activity (EDA) on 32 healthy subjects performing isometric biceps contraction. As assessed by means of an electromyography (EMG) analysis, 15 subjects showed muscle fatigue and 17 did not.EDA signals were analyzed using the recently proposed cvxEDA model in order to decompose them into their phasic and tonic components and extract effective features to study ANS dynamics. A statistical comparison between the two groups of subjects was performed. Results revealed that relevant phasic EDA features significantly increased in the fatigued group. Moreover, a pattern recognition system was applied to the EDA dataset in order to automatically discriminate between fatigued and non-fatigued subjects. The proposed leave-one-subject-out KNN classifier showed an accuracy of 75.69%. These results suggest the use of EDA as correlate of muscle fatigue, providing integrative information to the standard indices extracted from the EMG signals.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8036846
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Biceps,Autonomic nervous system,Tonic (music),Physical therapy,Psychology,Electromyography,Artificial intelligence,Muscle fatigue,Physical medicine and rehabilitation,Isometric exercise,Pattern recognition system
Conference
2017
ISSN
Citations 
PageRank 
1094-687X
0
0.34
References 
Authors
6
10
Name
Order
Citations
PageRank
Alberto Greco19120.51
A. Guidi2224.26
Federica Felici300.34
Andrea Leo432.76
Emiliano Ricciardi5145.25
Matteo Bianchi627647.56
Antonio Bicchi74104387.23
luca citi816827.88
Gaetano Valenza931448.21
Enzo Pasquale Scilingo1039498.07