Developent of switching technique adaptation on different types of hand movement for exoskeleton hand

Mohd Nordin, Nurul Fatihah (2025) Developent of switching technique adaptation on different types of hand movement for exoskeleton hand. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Post-stroke patients often face significant challenges in regaining control of their limb movements, particularly their arms and hands. Electromyography (EMG) signals, commonly used to measure muscle electrical activity and strength, have proven valuable but suffer from critical limitations such as high noise sensitivity, signal distortion, and cross-talk. These challenges hinder the accuracy of muscle strength measurements, requiring complex processing techniques and leading to inconsistent output. To address these issues, this project develops a novel switching technique that integrates Force Sensitive Resistor (FSR) sensors with EMG signals, improving the reliability and accuracy of data for hand movement analysis. The system combines the strengths of both EMG and FSR technologies, leveraging FSR sensors to reduce noise interference, improve threshold values, and ensure precise data collection. Input data is derived from various hand movements, specifically focusing on the thumb, index, and middle fingers, enabling a diverse dataset for analysis. The use of Arduino IDE, MATLAB, and Excel facilitates efficient simulation, data analysis, and visualization, supporting the project's technical goals. Results demonstrate that the FSR sensor outperforms traditional EMG-only methods, delivering consistent, accurate, and noise-resistant datasets that effectively represent hand movements. This integrated approach enhances the detection of muscle activity and provides a reliable method for producing high-quality data, meeting the project's objectives. By addressing the inherent weaknesses of EMG signals, this cost-effective and efficient system contributes to advancements in post-stroke rehabilitation and exoskeleton hand technologies. The project lays a foundation for further development of switching methods, with potential applications in broader rehabilitation contexts and wearable technologies aimed at improving patient outcomes.

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