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...

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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
Description
Summary: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).