Noise removal of functional Near Infrared Spectroscopy signals using Emperical Mode Decomposition and Independent Component Analysis

C. Pham, Vo Tuan, Hui Yu, Thang Nguyen

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Abstract

    In this work, we propose the combination of emperical mode decomposition (EMD) method and independent component analysis (ICA) to extract the heart rate signal. EMD is the fundamental part of Hilbert – Huang transform which is used to decompose signal into intrinsic mode functions that are not set analytically and are instead determined by an analyzed sequence alone. ICA uses Hyvarinen's fixed-point algorithm to estimate the independent components from given multidimensional signals. Our proposed approach is able to extract the heart rate signal from multiple fNIRS channels with the accuracy of 80% to 90% compared with the one measured from the real device. Our further work will integrate this result with noise attenuation using adaptive filters to mitigate the global inference of physiological activities to fNIRS measurement.
    Original languageEnglish
    Title of host publication6th International Conference on the Development of Biomedical Engineering in Vietnam (BME6)
    EditorsToi Van Vo, Thanh An Nguyen Le, Thang Nguyen Duc
    PublisherSpringer
    Pages925-929
    Number of pages5
    ISBN (Electronic)978-9811043611
    ISBN (Print)978-9811043604
    DOIs
    Publication statusPublished - Jan 2018
    Event6th International Conference on the Development of Biomedical Engineering - Ho Chi Minh, Vietnam
    Duration: 27 Jun 201629 Jun 2016

    Publication series

    NameIFMBE Proceedings
    PublisherSpringer Singapore
    ISSN (Print)1680-0737

    Conference

    Conference6th International Conference on the Development of Biomedical Engineering
    Country/TerritoryVietnam
    CityHo Chi Minh
    Period27/06/1629/06/16

    Keywords

    • near infrared spectroscopy
    • emperical mode decomposition
    • independet component analysis
    • noise attenuation
    • physiological signal

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