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    Area of Science:

    • Biomedical Engineering
    • Physiological Signal Processing

    Background:

    • Photoplethysmography (PPG) is a common technique for monitoring heart rate in clinical and consumer devices.
    • Beyond heart rate, PPG waveforms contain physiological information encoded in signal envelopes and amplitude (PPGA).

    Purpose of the Study:

    • To introduce and compare two novel asynchronous envelope detection techniques for PPG signals.
    • To enable extraction of additional physiological information from PPG without relying on peak detection.

    Main Methods:

    • Developed and evaluated the Asymmetric Root-Mean-Square (RMS) detector and the Peak Injection Low-Pass detector.
    • Assessed detector performance on the CapnoBase TBME benchmark dataset for accuracy and time delay.

    Main Results:

    • The Peak Injection method achieved a significantly lower absolute error (0.02) compared to the RMS method (0.60) for upper envelope detection.
    • Both methods provide beat-to-beat values, reducing the need for signal interpolation.

    Conclusions:

    • The proposed asynchronous envelope detectors are simple, efficient, and suitable for real-time patient monitoring.
    • Extracting envelope information from PPG offers a feasible approach to gain deeper physiological insights.