Windowed Double-FFT Algorithm for SpO2 Measurement in Areas of Low Vascular Density

To effectively monitor the status of critically ill patients, particularly in clinical scenarios such as the prevention of pressure injury (PI), it is crucial to accurately measure blood oxygen saturation (SpO2) at sites with low vascular density. Traditional reflective SpO2 sensor algorithms often yield invalid measurements and poor accuracy in these areas. To address these challenges, this study proposes a novel photoplethysmography (PPG) signal processing algorithm that combines windowing techniques with a double-fast Fourier transform (FFT). The algorithm significantly reduces spectral leakage impacts on the amplitude of both alternating current (ac) and direct current (dc) components, thereby greatly enhancing the precision of SpO2 measurements. In addition, it innovatively introduces harmonic-based feature extraction technology, which more effectively and accurately extracts ac and dc components, enabling precise SpO2 measurements. The experimental results demonstrate that, compared to existing methods, the proposed algorithm improves SpO2 measurement effectiveness to over 95%, enhances the R-value stability by 50%, and reduces the mean absolute error (MAE) by 65% compared to standard fingertip values. These results clearly confirm the substantial benefits of the algorithm in enhancing the effectiveness, stability, and accuracy of SpO2 measurement in areas of low vascular density.