Neuromuscular Abnormalities Detection On Stroke Patient By Using Electromyography (EMG)

Abstract

This project is concerned with neuromuscular abnormalities detection in stroke patients by using electromyography (EMG). This project aims to recognize the EMG signal on Upper Limb using MATLAB software, which aims to generate the raw EMG using a sensor, analyze the EMG signal on the upper limb with noise minimization, and record the neuromuscular abnormalities detection in the stroke patient and healthy individual. After cardiovascular illnesses and cancer, stroke is now the third highest cause of mortality, and it is the main cause of severe disability and impairment in the industrial world. Thus, the symptoms of a stroke seem to fluctuate on which area of the brain is affected. Usually, the symptoms could quickly and without any sign, a person may not even be aware that he or she has had a stroke. As a result, when a stroke occurs, the symptoms are usually the most acute, but they may gradually worsen. To overcome these issues, Electromyography (EMG) has to be conducted by a hardware circuit to recognize the signal of a stroke patient in an autonomous way on the skin of the patient. This project includes one sensor an EMG sensor, an Arduino board, and two batteries and is connected with MATLAB software. When the power is supplied to the hardware circuit, the sensor measured the signal on the upper limb of a stroke patient and healthy individual and then has been analyze it in MATLAB software. Therefore, the results from this project contain four positions from one patient who has been diagnosed with stroke for five years and has been compared the result with a healthy individual. The results show that neuromuscular abnormalities occur in stroke patients.