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A Real-Time Machine Learning Module for Motion Artifact Detection in fNIRS

Ercan, Renas; Xia, Yunjia; Zhao, Yunyi; Loureiro, Rui; Yang, Shufan; Zhao, Hubin; (2024) A Real-Time Machine Learning Module for Motion Artifact Detection in fNIRS. In: 2024 IEEE International Symposium on Circuits and Systems. IEEE: Singapore. (In press).

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Abstract

Functional Near-Infrared Spectroscopy (fNIRS) is a neuroimaging method which can be implemented with a wearable form factor. However, the data of fNIRS can be affected by motion artifact, which is conventionally processed offline using MATLAB-based software package via a bulky PC. This study trains a Support Vector Machine (SVM) algorithm and proposes a hardware design approach based on an FPGA to achieve the first real-time fNIRS motion artifact detection. The SVM hardware architecture proposed here utilizes a partially sequential–partially parallel implementation of the classification algorithm where Support Vector channels are consolidated into a single oversampled channel. A high classification accuracy of 97.42%, low FPGA resource utilization of 38,354 look-up tables and 6024 flip-flops with 10.92 us latency is achieved, outperforming conventional CPU SVM methods. These results show that an FPGA-based fNIRS motion artifact detector can be exploited whilst meeting real-time and resource constraints that are crucial in high-performance reconfigurable hardware systems.

Type: Proceedings paper
Title: A Real-Time Machine Learning Module for Motion Artifact Detection in fNIRS
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/10187348
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