Arduino Based Fatigue Level Measurement in Muscular Activity using RMS Technique

Human fatigue reduces ability to work for some time as a result of abnormal or prolonged workloads. For this problem, an electromyography (EMG) is used to evaluate the physical health of muscles. Each muscle in a human body transmits signals which are produced when a muscle makes different movements. In this paper, forearm muscle is investigated using MyoWare EMG sensor (AT-04-001), an Arduino Uno, keypad and LCD. The EMG sensor receives signal containing 235 samples from forearm muscle of person in time span of 30 seconds. RMS (Root Mean Square) value of recorded samples is calculated. Experiments show that RMS value increases with increase in BMI (Body Mass Index), hence threshold level of fatigue also increases as BMI tells the muscle strength, as more the strength, lesser will be the fatigue. The system is trained with ranges of (0.25, 0.35], (0.35, 0.45], 0.45+ and (0.37, 0.48], (0.48, 0.65], 0.65+ for low, medium and high fatigue using corresponding positions of fingers of hand for class1 (underweight or normal weight person) and class2 (overweight person) respectively. After training, BMI class is entered using keypad by entering either 1 for class1 or 2 for class2 and LCD shows fatigue level of a person.