Citation :

Harith G. Ayoub, Zaid A. Abdulrazzaq, Ahmed H. Ahmed, 2025. "Advanced Denoising of EMG Signals for Medical Applications: A Novel Arduino-Based Enhancement Approach" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 3, Issue 2: 5-11.

Abstract :

The accurate interpretation of electromyography (EMG) signals is crucial for medical diagnostics and rehabilitation systems. However, the inherent presence of noise, including motion artifacts and powerline interference, significantly hampers signal clarity. This research presents a novel, cost-effective approach for advanced EMG signal denoising using an Arduino-based platform integrated with custom signal processing techniques. By leveraging optimized digital filtering algorithms, the proposed system effectively suppresses noise while preserving critical muscle activity patterns. Experimental results demonstrate a significant improvement in signal-to-noise ratio (SNR), providing clean and reliable EMG data for enhanced medical analysis and real-time biomedical applications. The simplicity, affordability, and efficiency of the system position it as a promising solution for portable healthcare and rehabilitation devices.

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Keywords :

EMG ,Arduino, Embedded System, Denoising, Healthcare Devices.