Energy spectral density analysis of muscle fatigue

Driver’s vigilance level is easily distracted when in a state of fatigue and drowsiness. Most drivers’ shows sign of visual fatigue and loss of vigilance during long and monotonous driving. Their ability to maintain adequate driving performance is affected by various factors. Popular technique to es...

Full description

Bibliographic Details
Main Authors: Noor Aisyah, Ab Rahman, Mahfuzah, Mustafa, Rosdiyana, Samad, Nor Rul Hasma, Abdullah, Norizam, Sulaiman
Format: Book Section
Language:English
English
English
Published: Springer Singapore 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/22867/
http://umpir.ump.edu.my/id/eprint/22867/
http://umpir.ump.edu.my/id/eprint/22867/
http://umpir.ump.edu.my/id/eprint/22867/1/37.%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf
http://umpir.ump.edu.my/id/eprint/22867/13/54.%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf
http://umpir.ump.edu.my/id/eprint/22867/14/54.1%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf
id ump-22867
recordtype eprints
spelling ump-228672019-05-30T07:38:56Z http://umpir.ump.edu.my/id/eprint/22867/ Energy spectral density analysis of muscle fatigue Noor Aisyah, Ab Rahman Mahfuzah, Mustafa Rosdiyana, Samad Nor Rul Hasma, Abdullah Norizam, Sulaiman TK Electrical engineering. Electronics Nuclear engineering Driver’s vigilance level is easily distracted when in a state of fatigue and drowsiness. Most drivers’ shows sign of visual fatigue and loss of vigilance during long and monotonous driving. Their ability to maintain adequate driving performance is affected by various factors. Popular technique to estimate driv-er’s vigilance level is physiological measure that use electromyogram (EMG) signal in estimating driver muscle fatigue while driving. In this project, the EMG signal will be obtained by attaching the electrodes to the biceps brachii of each 15 subjects during playing Need for Speed (NFS) game for two hours. Be-fore that, subjects will answer a set of questionnaires and the scores obtained will be calculated. From the questionnaires, driver condition can be determined whether the driver is non-fatigue or mild fatigue or fatigue. Then signal prepro-cessing is applied to remove artifact in EMG signal. Next, the EMG signal is analyzed by using frequency domain analysis and Energy Spectral Density (ESD) extracted from the analysis. Mean, variance and peak energy of ESD is obtained from all the samples. Based on result obtained, the normalized mean (non-fatigue: 0.0514-0.1255), (mild fatigue: 0.0554-0.0802) and (fatigue: 0.0069-0.0188). For the variance range (non-fatigue: 0.0050-0.0311), (mild fa-tigue: 0.0054-0.0802) and (fatigue: 0.0006-0.0047). While for the peak energy of ESD (non-fatigue: 28480-2943000 J/Hz), (mild fatigue: 99440-120500 J/Hz) and (fatigue: 537.7-11440 J/Hz). Springer Singapore 2018-08 Book Section PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22867/1/37.%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf pdf en http://umpir.ump.edu.my/id/eprint/22867/13/54.%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf pdf en http://umpir.ump.edu.my/id/eprint/22867/14/54.1%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf Noor Aisyah, Ab Rahman and Mahfuzah, Mustafa and Rosdiyana, Samad and Nor Rul Hasma, Abdullah and Norizam, Sulaiman (2018) Energy spectral density analysis of muscle fatigue. In: Proceedings of the 10th National Technical Seminar on Underwater System Technology 2018. Lecture Notes in Electrical Engineering . Springer Singapore, Singapore, pp. 437-446. ISBN 978-981-13-3708-6 https://link.springer.com/chapter/10.1007/978-981-13-3708-6_37 DOI: https://doi.org/10.1007/978-981-13-3708-6_37
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Noor Aisyah, Ab Rahman
Mahfuzah, Mustafa
Rosdiyana, Samad
Nor Rul Hasma, Abdullah
Norizam, Sulaiman
Energy spectral density analysis of muscle fatigue
description Driver’s vigilance level is easily distracted when in a state of fatigue and drowsiness. Most drivers’ shows sign of visual fatigue and loss of vigilance during long and monotonous driving. Their ability to maintain adequate driving performance is affected by various factors. Popular technique to estimate driv-er’s vigilance level is physiological measure that use electromyogram (EMG) signal in estimating driver muscle fatigue while driving. In this project, the EMG signal will be obtained by attaching the electrodes to the biceps brachii of each 15 subjects during playing Need for Speed (NFS) game for two hours. Be-fore that, subjects will answer a set of questionnaires and the scores obtained will be calculated. From the questionnaires, driver condition can be determined whether the driver is non-fatigue or mild fatigue or fatigue. Then signal prepro-cessing is applied to remove artifact in EMG signal. Next, the EMG signal is analyzed by using frequency domain analysis and Energy Spectral Density (ESD) extracted from the analysis. Mean, variance and peak energy of ESD is obtained from all the samples. Based on result obtained, the normalized mean (non-fatigue: 0.0514-0.1255), (mild fatigue: 0.0554-0.0802) and (fatigue: 0.0069-0.0188). For the variance range (non-fatigue: 0.0050-0.0311), (mild fa-tigue: 0.0054-0.0802) and (fatigue: 0.0006-0.0047). While for the peak energy of ESD (non-fatigue: 28480-2943000 J/Hz), (mild fatigue: 99440-120500 J/Hz) and (fatigue: 537.7-11440 J/Hz).
format Book Section
author Noor Aisyah, Ab Rahman
Mahfuzah, Mustafa
Rosdiyana, Samad
Nor Rul Hasma, Abdullah
Norizam, Sulaiman
author_facet Noor Aisyah, Ab Rahman
Mahfuzah, Mustafa
Rosdiyana, Samad
Nor Rul Hasma, Abdullah
Norizam, Sulaiman
author_sort Noor Aisyah, Ab Rahman
title Energy spectral density analysis of muscle fatigue
title_short Energy spectral density analysis of muscle fatigue
title_full Energy spectral density analysis of muscle fatigue
title_fullStr Energy spectral density analysis of muscle fatigue
title_full_unstemmed Energy spectral density analysis of muscle fatigue
title_sort energy spectral density analysis of muscle fatigue
publisher Springer Singapore
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/22867/
http://umpir.ump.edu.my/id/eprint/22867/
http://umpir.ump.edu.my/id/eprint/22867/
http://umpir.ump.edu.my/id/eprint/22867/1/37.%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf
http://umpir.ump.edu.my/id/eprint/22867/13/54.%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf
http://umpir.ump.edu.my/id/eprint/22867/14/54.1%20Energy%20spectral%20density%20analysis%20of%20muscle%20fatigue.pdf
first_indexed 2023-09-18T22:33:59Z
last_indexed 2023-09-18T22:33:59Z
_version_ 1777416472999493632