Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction

This study examined the effects of electromyographic (EMG) signals from Biceps Brachii (BB) muscle on the root mean square (RMS)-time relationships during dynamic contraction. Ten healthy and right hand dominated male subjects were volunteered for the experiments. The RMS features were extracted fro...

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Main Authors: Ahamed, Nizam Uddin, Altwijri, Omar, Rahaman, S. A. M. Matiur, Alqahtani, Mahdi, Ahmed, Nasim, Sundaraj, Kenneth
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2015
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/11559/1/IEEE.pdf
http://umpir.ump.edu.my/id/eprint/11559/7/fkp-2015-nizzam-Relation%20Between%20EMG%20Signal.pdf
http://umpir.ump.edu.my/id/eprint/11559/
http://dx.doi.org/10.1109/ICAICTA.2015.7335359
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spelling my.ump.umpir.115592018-05-02T02:39:20Z http://umpir.ump.edu.my/id/eprint/11559/ Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction Ahamed, Nizam Uddin Altwijri, Omar Rahaman, S. A. M. Matiur Alqahtani, Mahdi Ahmed, Nasim Sundaraj, Kenneth TA Engineering (General). Civil engineering (General) This study examined the effects of electromyographic (EMG) signals from Biceps Brachii (BB) muscle on the root mean square (RMS)-time relationships during dynamic contraction. Ten healthy and right hand dominated male subjects were volunteered for the experiments. The RMS features were extracted from the corresponding EMG signals (amplitude of the full wave EMG) for 10 seconds in 5 minutes intervals between each trial. Ten seconds (or 10000 ms) were divided into 4 time lags to identify the muscle activity and relationship between EMG and time using different statistical analysing techniques, such as mean, regression analysis, correlation, ANOVA, and coefficient of variation (CoV) for muscle activity variation. The results shows that large positive linear association between EMG and endurance time where the points are close to the linear trend line (R squared = 0.93 and F-ratio = 453.1). Signal steadiness is better during last time lags (1.66% during 7501–10000 ms) compared to initial time duration (10.35% during 0–2500 ms). IEEE 2015-08-15 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11559/1/IEEE.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11559/7/fkp-2015-nizzam-Relation%20Between%20EMG%20Signal.pdf Ahamed, Nizam Uddin and Altwijri, Omar and Rahaman, S. A. M. Matiur and Alqahtani, Mahdi and Ahmed, Nasim and Sundaraj, Kenneth (2015) Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction. In: 2nd IEEE International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA 2015), 19-22 August 2015 , Chonburi, Thailand. pp. 1-4., 2015. ISSN 978-1-4673-8142-0 ISBN 978-1-4673-8142-0 http://dx.doi.org/10.1109/ICAICTA.2015.7335359 10.1109/ICAICTA.2015.7335359
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Ahamed, Nizam Uddin
Altwijri, Omar
Rahaman, S. A. M. Matiur
Alqahtani, Mahdi
Ahmed, Nasim
Sundaraj, Kenneth
Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
description This study examined the effects of electromyographic (EMG) signals from Biceps Brachii (BB) muscle on the root mean square (RMS)-time relationships during dynamic contraction. Ten healthy and right hand dominated male subjects were volunteered for the experiments. The RMS features were extracted from the corresponding EMG signals (amplitude of the full wave EMG) for 10 seconds in 5 minutes intervals between each trial. Ten seconds (or 10000 ms) were divided into 4 time lags to identify the muscle activity and relationship between EMG and time using different statistical analysing techniques, such as mean, regression analysis, correlation, ANOVA, and coefficient of variation (CoV) for muscle activity variation. The results shows that large positive linear association between EMG and endurance time where the points are close to the linear trend line (R squared = 0.93 and F-ratio = 453.1). Signal steadiness is better during last time lags (1.66% during 7501–10000 ms) compared to initial time duration (10.35% during 0–2500 ms).
format Conference or Workshop Item
author Ahamed, Nizam Uddin
Altwijri, Omar
Rahaman, S. A. M. Matiur
Alqahtani, Mahdi
Ahmed, Nasim
Sundaraj, Kenneth
author_facet Ahamed, Nizam Uddin
Altwijri, Omar
Rahaman, S. A. M. Matiur
Alqahtani, Mahdi
Ahmed, Nasim
Sundaraj, Kenneth
author_sort Ahamed, Nizam Uddin
title Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
title_short Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
title_full Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
title_fullStr Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
title_full_unstemmed Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
title_sort relation between emg signal activation and time lags using feature analysis during dynamic contraction
publisher IEEE
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/11559/1/IEEE.pdf
http://umpir.ump.edu.my/id/eprint/11559/7/fkp-2015-nizzam-Relation%20Between%20EMG%20Signal.pdf
http://umpir.ump.edu.my/id/eprint/11559/
http://dx.doi.org/10.1109/ICAICTA.2015.7335359
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score 13.154949