Optimized Approach on EMG Signal Classification

Classification of electromyography (EMG) signals, also known as muscle signals, allow the study of human movements via the extraction of useful patterns from the signals after proper processing. An optimized approach is developed and introduced to enhance the performance of the classification system to improve the accuracy on classification of wrist and finger movements. A graphical user interface that allows user to upload and classify EMG signals is created. With further modifications, the output from the graphical user interface can be used to control an exoskeleton unit to mimic human movements, or to monitor human movements for ergonomic studies.