Analysis of Electromyography Signals for Control of Mechanical Prosthesis using Machine Learning Techniques

This research aims to design, develop, and evaluate a low-cost mechanical prosthesis controlled through EMG signals and integrated with IoT capabilities. The study seeks to achieve a balance between affordability and advanced functionality, making the technology accessible to a broader range of users. Additionally, the study aims to assess the usability, comfort, and overall performance of the developed prosthesis in real-world scenarios. The analysis of electromyography (EMG) signals for the control of mechanical prostheses using machine learning techniques serves the purpose of enabling individuals with limb loss to achieve more natural and intuitive control over their prosthetic devices. The ultimate goal…