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[Compensation-fitting extraction of dynamic spectrum based on least squares method].

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    A new compensation-fitting extraction method enhances dynamic spectrum (DS) analysis for noninvasive blood component detection. This technique improves signal-to-noise ratio and reduces processing time, paving the way for more accurate measurements.

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    Area of Science:

    • Biomedical Engineering
    • Optical Sensing
    • Signal Processing

    Background:

    • High signal-to-noise ratio dynamic spectrum (DS) extraction is crucial for accurate noninvasive blood component detection.
    • Existing methods face challenges in speed and precision, particularly with motion artifacts and random noise.

    Purpose of the Study:

    • To develop and validate a novel compensation-fitting extraction method for dynamic spectrum (DS) analysis.
    • To improve the accuracy, speed, and signal-to-noise ratio (SNR) of noninvasive blood component measurements.

    Main Methods:

    • Analysis of linear similarity between photoelectric plethysmography (PPG) signals at different wavelengths.
    • Implementation of a compensation-fitting extraction technique involving baseline compensation and least squares fitting.
    • Comparative experiments in NIR and Vis wavebands using 25 samples, contrasting with single-trial estimation.

    Main Results:

    • The compensation-fitting method significantly improved DS flatness, reducing average variance to 69.0% (NIR) and 57.4% (Vis) compared to single-trial estimation.
    • Data processing time was substantially reduced, to 10% (NIR) and 20% (Vis) of single-trial estimation.
    • Improved signal-to-noise ratio and simplified procedures were observed.

    Conclusions:

    • The dynamic spectrum compensation-fitting extraction method offers a significant advancement over single-trial estimation.
    • This technique enhances SNR, improves estimation quality, and reduces processing time for noninvasive blood component analysis.
    • The method shows strong potential for advancing noninvasive blood component measurement technologies.