Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation

Hrishikesh H. Pillai; P. S. Lal Priya; Kavinga Upul Ekanayaka; Jackrit Suthakorn; Branesh M. Pillai

doi:10.1109/RAAI59955.2023.10601287

Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation

Hrishikesh H. Pillai
, P. S. Lal Priya
, Kavinga Upul Ekanayaka
, Jackrit Suthakorn
, Branesh M. Pillai

Department of Biomedical Engineering

CET Campus
Accelr

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

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.

Original language	English
Title of host publication	2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	195-199
Number of pages	5
ISBN (Electronic)	9798350307566
DOIs	https://doi.org/10.1109/RAAI59955.2023.10601287
Publication status	Published - 2023
Event	3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023 - Singapore, Singapore Duration: 14 Dec 2023 → 16 Dec 2023

Publication series

Name	2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023

Conference

Conference	3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023
Country/Territory	Singapore
City	Singapore
Period	14/12/23 → 16/12/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Keywords

FFT/IFFT filter
FPGA
Robotic-assisted rehabilitation
bio-signal

Access to Document

10.1109/RAAI59955.2023.10601287

Cite this

Pillai, H. H., Lal Priya, P. S., Ekanayaka, K. U., Suthakorn, J., & Pillai, B. M. (2023). Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation. In 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023 (pp. 195-199). (2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RAAI59955.2023.10601287

Pillai, Hrishikesh H. ; Lal Priya, P. S. ; Ekanayaka, Kavinga Upul et al. / Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation. 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 195-199 (2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023).

@inproceedings{a1de6b47f4d84814bc2b1e6a7df13162,

title = "Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation",

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.",

keywords = "FFT/IFFT filter, FPGA, Robotic-assisted rehabilitation, bio-signal",

author = "Pillai, \{Hrishikesh H.\} and \{Lal Priya\}, \{P. S.\} and Ekanayaka, \{Kavinga Upul\} and Jackrit Suthakorn and Pillai, \{Branesh M.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023 ; Conference date: 14-12-2023 Through 16-12-2023",

year = "2023",

doi = "10.1109/RAAI59955.2023.10601287",

language = "English",

series = "2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "195--199",

booktitle = "2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023",

}

Pillai, HH, Lal Priya, PS, Ekanayaka, KU, Suthakorn, J & Pillai, BM 2023, Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation. in 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023. 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023, Institute of Electrical and Electronics Engineers Inc., pp. 195-199, 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023, Singapore, Singapore, 14/12/23. https://doi.org/10.1109/RAAI59955.2023.10601287

Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation. / Pillai, Hrishikesh H.; Lal Priya, P. S.; Ekanayaka, Kavinga Upul et al.
2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 195-199 (2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation

AU - Pillai, Hrishikesh H.

AU - Lal Priya, P. S.

AU - Ekanayaka, Kavinga Upul

AU - Suthakorn, Jackrit

AU - Pillai, Branesh M.

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - FFT/IFFT filter

KW - FPGA

KW - Robotic-assisted rehabilitation

KW - bio-signal

UR - https://www.scopus.com/pages/publications/85200727471

U2 - 10.1109/RAAI59955.2023.10601287

DO - 10.1109/RAAI59955.2023.10601287

M3 - Conference contribution

AN - SCOPUS:85200727471

T3 - 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023

SP - 195

EP - 199

BT - 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023

Y2 - 14 December 2023 through 16 December 2023

ER -

Pillai HH, Lal Priya PS, Ekanayaka KU, Suthakorn J, Pillai BM. Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation. In 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 195-199. (2023 3rd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2023). doi: 10.1109/RAAI59955.2023.10601287

Bio-Signal Activated FPGA-Based System for Robotic-Assisted Rehabilitation

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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