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Evaluation of muscle fatigue identification based on EMG feature [electronic resource] / Nur Amelia Izzati Mohd Amin

By:

Nur Amelia Izzati Mohd Amin

Material type:

Computer filePublication details: Kuantan, Pahang : UMP, 2016Description: 1 computer disc : digital data ; 12 cmISBN:

THE0005083(Local)

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Dissertation note: Project Paper (Bachelor of Engineering in Mechatronis Engineering (Hons.)) -- Universiti Malaysia Pahang – 2016 Abstract: The aim of this study was to identify muscle fatigue during sub-maximal contraction on biceps brachii and triceps muscle on upper limb muscle through EMG feature. The relationship between muscle fatigues with EMG feature was evaluated by conducting on six volunteers on their upper limb muscle. The raw EMG signal was recorded from biceps brachii muscle and triceps muscle in static posture at 30%, 50% and 70% of their maximum voluntary contraction (MVC). Band pass Butterworth filter (20-1000 Hz) and 1000 Hz of sampling frequency was applied during the experiments. The subjects was instructed to grip the hand dynamometer and the sEMG activity of the biceps brachii muscle and triceps muscle was recorded. Root mean square feature was calculated as EMG amplitude which have been computed in the filtered EMG signal recorded. Regression analysis and analysis of variance (ANOVA) were implemented to determine the significant of the feature with the muscle force. The result shows that muscle fatigue was performed at 70% of MVC at both of muscle. The relationship between 30% and 70% of force was most significant value which was 0.000 (P<0.05) on biceps brachii muscle while most significant value was 0.035 (P<0.05) resulted between 30% and 70% of force on triceps muscle.

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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	FKP .A44 2016 r Bc. \| CD 10412 (Browse shelf(Opens below))	1	Not for loan		0000115927

Faculty of Manufacturing Engineering

Theses Gred B

Project Paper (Bachelor of Engineering in Mechatronis Engineering (Hons.)) -- Universiti Malaysia Pahang – 2016

The aim of this study was to identify muscle fatigue during sub-maximal contraction on biceps brachii and triceps muscle on upper limb muscle through EMG feature. The relationship between muscle fatigues with EMG feature was evaluated by conducting on six volunteers on their upper limb muscle. The raw EMG signal was recorded from biceps brachii muscle and triceps muscle in static posture at 30%, 50% and 70% of their maximum voluntary contraction (MVC). Band pass Butterworth filter (20-1000 Hz) and 1000 Hz of sampling frequency was applied during the experiments. The subjects was instructed to grip the hand dynamometer and the sEMG activity of the biceps brachii muscle and triceps muscle was recorded. Root mean square feature was calculated as EMG amplitude which have been computed in the filtered EMG signal recorded. Regression analysis and analysis of variance (ANOVA) were implemented to determine the significant of the feature with the muscle force. The result shows that muscle fatigue was performed at 70% of MVC at both of muscle. The relationship between 30% and 70% of force was most significant value which was 0.000 (P<0.05) on biceps brachii muscle while most significant value was 0.035 (P<0.05) resulted between 30% and 70% of force on triceps muscle.

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