Title :
Non-invasive electromyography-based fatigue detection and performance analysis on m. biceps brachii muscle
Author :
Ahamed, Nazeer ; Sundaraj, K. ; Ahmad, R.B. ; Rahman, Mosaddequr ; Islam, Aminul ; Ali, Ahmad
Author_Institution :
AI-Rehab Res. Group, Univ. Malaysia Perlis, Kangar, Malaysia
Abstract :
Muscle fatigue occurs most frequently due to repetitive movements in our day-to-day activities. The powerful use of muscles might cause a decline in performance. In this study, the effects of muscle fatigue involving only the m. biceps brachii muscle in the dominant upper arm were investigated during the course of an arm wrestling game where the muscle contractions were produced by the winner and loser, respectively. This competition was conducted to monitor the progress/ decline of muscle strength among young players. Eight male subjects (age: 26±3 years, height: 170±13 cm, weight: 70±13 kg and BMI: 21±4) were participated in this study. Electrodes were placed on the middle of the biceps muscle to record the electromyography (EMG) signals. Each group (two players) participated twice with each other, and the EMG signals were recorded. Muscle fatigue was analyzed and compared using the first-time and second-time EMG data. The results were evaluated by calculating the average EMG, root mean square (RMS) and the highest peak of the signal during muscle contraction. Among these, RMS and highest peak values helped in efficiently assessing muscle fatigue. Most of the results indicated that m. biceps muscle reduced its strength during the second game; also, winners performance were found to be better than the losers (according to EMG amplitudes). The current findings regarding the m. biceps brachii muscle might prove to be useful in developing effective injury prevention and rehabilitation strategies, and other physiological measurements related to the upper arm muscles.
Keywords :
biomechanics; biomedical electrodes; electromyography; medical signal detection; BMI; EMG signals; RMS; arm wrestling game; electrodes; electromyography signals; first-time EMG data; injury prevention; m. biceps brachii muscle; muscle contractions; muscle fatigue; muscle strength; noninvasive electromyography-based fatigue detection; performance analysis; physiological measurements; rehabilitation strategy; root mean square; second-time EMG data; upper arm muscles; Electromyography; arm wrestling; fatigue; m. biceps brachii; muscle contraction;
Conference_Titel :
Control System, Computing and Engineering (ICCSCE), 2012 IEEE International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4673-3142-5
DOI :
10.1109/ICCSCE.2012.6487160