02728nmm a2200325 a 4500001001400000003000700014005001700021008004100038020002200079039009500101040000800196090002400204090001300228100003200241245012300273260003400396300004600430500004100476500001800517502011800535520128200653538002301935610005601958650004502014650001102059856007102070952012902141999002502270999010702295vtls000098393KUKTEM20251117113332.0161213s2016    my     fq  d  001 0 eng d  aTHE0005083(Local) 9a201905101614bhanafiahc201905101613dhanafiahc201712131157dfateehay201612131403zsaini  aUMP  aFKP .A44 2016 r Bc.  aCD 104120 aNur Amelia Izzati Mohd Amin10aEvaluation of muscle fatigue identification based on EMG featureh[electronic resource] /cNur Amelia Izzati Mohd Amin  aKuantan, Pahang :bUMP,c2016  a1 computer disc :bdigital data ;c12 cm.  aFaculty of Manufacturing Engineering  aTheses Gred B  aProject Paper (Bachelor of Engineering in Mechatronis Engineering (Hons.)) -- Universiti Malaysia Pahang – 20163 aThe 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.  aItem in PDF format20aFaculty of Manufacturing EngineeringxDissertations 0aUniversities and CollegesxDissertations 0aTheses40uhttp://ecollib.ump.edu.my/id/eprint/3982zAccess in library only    00104071a20000b20000d2019-09-04l0oFKP .A44 2016 r Bc. | CD 10412p0000115927r2019-09-04 00:00:00t1w2019-09-04yPSM  aVIRTUA40c6936d6942  aVTLSSORT0080*0200*0400*0900*0901*1000*2450*2600*3000*5000*5001*5020*5200*5380*6100*6500*6501*8560*9992