Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation
Issued Date
2023-01-01
Resource Type
Scopus ID
2-s2.0-85200727471
Journal Title
2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023
Start Page
195
End Page
199
Rights Holder(s)
SCOPUS
Bibliographic Citation
2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023 (2023) , 195-199
Suggested Citation
Pillai H.H., Lal Priya P.S., Ekanayaka K.U., Suthakorn J., Pillai B.M. Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation. 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023 (2023) , 195-199. 199. doi:10.1109/RAAI59955.2023.10601287 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100500
Title
Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation
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Corresponding Author(s)
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Abstract
This paper presents a pivotal contribution to multi-modal bio-signal processing for robotic control applications, leveraging cutting-edge Field Programmable Gate Array (FPGA) technology to unlock new frontiers in accuracy, efficiency, and real-time control. The comprehensive hardware implementation strategy is characterized by the strategic utilization of a Fast Fourier Transform/ Inverse Fast Fourier Transform (FFT/IFFT) - based filtering algorithm optimized for Electroencephalogra-phy (EEG) signal processing. Concurrently, an inventive movement classification methodology powered by Electrooculography (EOG) signals is introduced. The core proposition of the paper revolves around the implementation of an EEG and EOG-driven Multi Input Single Output (MISO) control system, intended for the control of rehabilitation robots. The effectiveness of the proposed method was verified by simulation in Lab VIEW. The algorithm has been seamlessly integrated into the My Rio 1900 hardware platform, leveraging the immense processing power of a Xilinx FPGA.