Statistical Analysis for EMG Extracted Time and Frequency Domain Features during Different Dumbbell Activity

Electromyography on the surface of the body (EMG) is used to examine the electrical activity of the muscles. In order to evaluate human fitness, it is now essential to extract qualitative features from EMG signals. Fourteen distinct time-domain and frequency-domain features have been derived for various hand movements. In this study, EMG signals collected during six distinct hand activities have been analysed by using statistical tests, such as the t-test, sign-rank test and the analysis of variance, to determine the degree to which specific properties vary. The hand movement under study was dumbbell up, dumbbell down and hand gripper with both hands i.e two sets of data for each movement. The results show that there is no such difference for the dumbbell activity considering either up or down movement except for a few features regardless of the hand used. Although the non-significant result was found for all features considering both left-hand griper and right-hand griper. But the majority of the features show there is enough evidence (p<0.05) showing significant difference when considering up and down movement for both hands' dumbbell activity. Similarly, there was a significant difference ($p < 0.5$) in the majority case for all features considering all dumbbell activity at a time using analysis of variance.