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An FPGA-based, multi-channel, real-time, motion artifact detection technique for fNIRS/DOT systems

Xia, Yunjia; Frijia, Elisabetta Maria; Loureiro, Rui; Cooper, Robert J; Zhao, Hubin; (2024) An FPGA-based, multi-channel, real-time, motion artifact detection technique for fNIRS/DOT systems. In: 2024 IEEE International Symposium on Circuits and Systems. IEEE: Singapore. (In press).

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Abstract

Functional Near-Infrared Spectroscopy (fNIRS) and its extension, Diffuse Optical Tomography (DOT), are emerging non-invasive neuroimaging techniques that measure brain activities by monitoring changes in blood oxygenation using near infrared light. However, motion artifacts from subject movements in fNIRS/DOT data could severely undermine data quality. Current solutions typically rely on offline methods executed on conventional computers in laboratories/hospitals, limiting real-time applications and flexibility in wider environments. To address these limitations, we present an FPGA-based multi-channel real-time motion artifact detection system. The proposed system, tested against an expert-annotated dataset, showcases encouraging overall performance, with a minimal delay of 2.75 ms across 12-channel raw fNIRS data, and boasts a sensitivity rate of 85.28% and accuracy of 87.06%. This efficiency is achieved using less than 10% of FPGA resources, underscoring that the proposed realtime processing system holds the potential to be scaled up to 3630 channels. These results indicate a promising avenue towards real-time motion artifact processing in large-size multichannel fNIRS/DOT data. Our design lays the groundwork for its application in areas including wearable real-time functional brain imaging, brain-computer interfaces, human-robot interaction, and surgical monitoring.

Type: Proceedings paper
Title: An FPGA-based, multi-channel, real-time, motion artifact detection technique for fNIRS/DOT systems
Event: ISCAS 2024: 2024 IEEE International Symposium on Circuits and Systems
Publisher version: https://ieee-cas.org/event/conference/2024-ieee-in...
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Ortho and MSK Science
URI: https://discovery.ucl.ac.uk/id/eprint/10187347
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