Detection and Classification of Muscular Fatigueness on Upper Extremities using Surface EMG Electrode Interfaced with Labview

Long-term use of mobile phones fosters the continual usage of the trapezius muscles, which contributes to degradation to the muscle fibres, compounding impairment like acute trauma, and myogenic tonus, which mostly affects the collar and shoulders. Before it becomes evident, physical weariness must be noticed to improve the performance and prevent more catastrophes.. The objective of this paper is to measure the weariness of the muscles in cervical erector spinae and trapezius muscles and also to categorise the effect of fatigueness created due to prolonged use of cell phones. The surface electromyography signals are used for analysing and also for extracting the features from muscle activities. These signals are non-linear, non-stationary and exhibit self-similar multifractal behaviour. Experimental session where 30 individuals are involved to record surface electromyography signals before and after usage of smart phone by connecting electrodes to the cervical erector spinae and trapezius muscles to note down the variations in the parameters obtained by sending the data via DAQ card to the LABVIEW software. A similar system was also constructed and measured the performance using MATLAB software through data acquisition system. Fatigue mostly influences the frequency spectrum and strength of the signal. Thus, as crucial components of the EMG signal, the most credible metrics, such as Variance, Median value, Root Mean Square (RMS),Mean Frequency of the power spectrum (MNF), are adopted and a classification algorithm was developed using Fuzzy logic techniques that estimates the extent of muscle fatigueness.

I. Introduction(Heading 1)

Muscular fatigue occurs in the cervical erector spinae and trapezius muscles due to prolonged stress like usage of smart phone for a long period of time, involving in rigorous training and also due to sports related activities.