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Related Experiment Video

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Piezoelectric Ceramic Sensor Array Based Obstructive Sleep Apnea Event Detection.

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    IEEE Journal of Biomedical and Health Informatics
    |April 28, 2025
    PubMed
    Summary
    This summary is machine-generated.

    A new piezoelectric sensor array and AI method (DRFNet) enable contactless monitoring for obstructive sleep apnea (OSA). This system improves detection accuracy, offering potential for home-based sleep studies.

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    Area of Science:

    • Biomedical Engineering
    • Sleep Medicine
    • Artificial Intelligence

    Background:

    • Obstructive sleep apnea (OSA) is a significant sleep disorder linked to serious health issues like cardiovascular disease and hypertension.
    • Contactless pressure sensors offer a non-invasive approach for sleep monitoring, but existing methods suffer from noise and positional constraints.
    • Poor signal quality from limited sensors hinders accurate OSA event detection.

    Purpose of the Study:

    • To develop a sensitive sensor array for capturing weak pressure signals beneath a mattress.
    • To create an automated method for detecting obstructive sleep apnea events using deep learning.
    • To evaluate the performance of the developed system in a pilot study with adult volunteers.

    Main Methods:

    • Designed a piezoelectric ceramic sensor array (PCSA) with sixteen sensors integrated into a mat for chest and abdomen monitoring.
    • Collected overnight pressure signals and polysomnography data from 36 adult volunteers.
    • Developed DRFNet, an automated OSA event detection method fusing ResNet18 and DenseNet121 for time-domain and frequency-domain feature extraction.

    Main Results:

    • The PCSA effectively captured weak pressure signals through mattresses up to 30cm thick.
    • DRFNet achieved 75.19% sensitivity, 87.78% specificity, and 81.48% accuracy in OSA event detection.
    • The system demonstrated competitive performance compared to existing state-of-the-art methods.

    Conclusions:

    • The combination of PCSA and DRFNet offers a promising solution for contactless sleep monitoring.
    • This technology has the potential for deployment in embedded devices for home-based obstructive sleep apnea monitoring.
    • The developed system can improve the accessibility and convenience of sleep disorder diagnosis.