A Real-Time EMG-Based Fixed-Bandwidth Frequency-Domain Embedded System for Robotic Hand - Chen, Biao; Chen, Chaoyang; Hu, Jie; Nguyen, Thomas; Qi, Jin; Yang, Banghua; Chen, Dawei; Alshahrani, Yousef; Zhou, Yang; Tsai, Andrew; Frush, Todd; Goitz, Henry (Frontiers in Neurorobotics, 2022)
The signals from electromyography (EMG) have been used for volitional control of robotic assistive devices with the challenges of performance improvement. Currently, the most common method of EMG signal processing for robot control is RMS (root mean square) –based algorithm, but system performance accuracy can be affected by noise or artifacts. The hypothesis of this study was that the frequency bandwidth of noise and artifacts are beyond the main EMG signal frequency bandwidth, hence the fixed-bandwidth frequency-domain signal processing methods can filter off noise and artifacts only by processing main frequency bandwidth of EMG signals for robot control. The purpose of this study was to develop a cost-effective embedded system and short-time Fourier transform (STFT) method for an EMG-controlled robotic hand. Healthy volunteers were recruited in this study to identify the optimal myoelectric signal frequency bandwidth of muscle contractions. The STFT embedded system was developed using STM32 microcontroller unit (MCU). The performance of STFT embedded system was compared with RMS embedded system. The results showed that the optimal myoelectric signal frequency band responding to muscle contractions was between 60-80 Hz. STFT embedded system was more stable than the RMS embedded system in detecting muscle contraction. Onsite calibration was required for RMS embedded system. The average accuracy of STFT embedded system 91.55 %. This study presents a novel approach for developing a cost-effective and less complex embedded myoelectric signal processing system for robot control.