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Ballistocardiography with fiber optic sensor in headrest position: a feasibility study and a new processing

Yongwei Zhu, Haihong Zhang, Maniyeri Jayachandran

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 11, 2013
    PubMed
    Summary

    This study introduces headrest ballistocardiography (BCG) for portable e-healthcare. A novel algorithm accurately detects heart rate intervals from distorted BCG signals in this new headrest position.

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    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Wearable Technology

    Background:

    • Ballistocardiography (BCG) offers unobtrusive physiological monitoring for e-healthcare.
    • Existing BCG systems are limited to bed, backrest, seat, or scale configurations.
    • Technological advancements are driving interest in novel BCG applications.

    Purpose of the Study:

    • To investigate the feasibility of BCG in a headrest position for practical, portable e-healthcare.
    • To design and implement a multi-modality sensing system for headrest BCG.
    • To develop and validate a new algorithm for accurate heart rate detection from headrest BCG signals.

    Main Methods:

    • Developed a multi-modality sensing system featuring a high-sensitivity microbend fiber optic BCG sensor.
    • Collected synchronized BCG and electrocardiography (ECG) data from three human subjects.
    • Designed and applied a novel algorithm for heart beat detection and heart rate interval computation.

    Main Results:

    • Identified unique signal characteristics of headrest BCG, distinct from traditional setups.
    • Demonstrated significant signal distortion in the headrest BCG data.
    • Validated the novel algorithm's accuracy in computing heart rate intervals despite signal distortion.

    Conclusions:

    • Headrest BCG is a viable, novel configuration for unobtrusive e-healthcare monitoring.
    • Advanced signal processing techniques, like the developed algorithm, are crucial for accurate heart rate recovery in this setup.
    • This preliminary study paves the way for portable, headrest-based BCG applications.