Please use this identifier to cite or link to this item: http://ir.unikl.edu.my/jspui/handle/123456789/18742
metadata.fyp.dc.title: Muscle Fatigue Detection and analysis using EMG sensor
metadata.fyp.dc.contributor.*: Muhammad Hafizul bin Osman
Bachelor of Engineering Technology (Hons.) in Electrical
metadata.fyp.dc.date.issued: 10-Apr-2018
metadata.fyp.dc.description.abstract: Electromyography (EMG) is a sensor to diagnose the health of muscle with a placement of electrode through the surface of the skin. Nowadays, the muscular disorder occurs where the problem is the cause of muscle weakness, pain, fatigue and also due to paralysis. Biomedical applications where the electromyography (EMG) sensor are used to collect data of a normal muscles contradiction and there are two classifier which is linear discriminant analysis (LDA) and support vector machines (SVM) that are prompt to undergo with the process and also mean absolute value feature (MAV) traces are used to extract from the electromyography (EMG). Ascertain part of body muscle targeted with the different subject with certain body mass index (BMI), the movement contradiction of the muscles through the sensor pad electrodes that are attached to the human body where the point of muscles that wanted to observe and the data collected or being used. The study provides guidelines for prediction of muscle fatigue using electromyography (EMG) sensor with classification methods that are approved.
metadata.fyp.dc.description: Top 20
metadata.fyp.dc.identifier.uri: http://ir.unikl.edu.my/jspui/handle/123456789/18742
Appears in Collections:Final Year Project - UniKL BMI



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