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...
Main Authors: | , , , , |
---|---|
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 |