Noninvasive hemoglobin measurement based on optimizing Dynamic Spectrum method

An optimizing Dynamic Spectrum method based on short-time Fourier transform for noninvasive hemoglobin measurement was proposed. A total of 187 volunteers' spectral data and blood samples were prepared for the calibration (167 samples) and prediction (20 samples) sets. Data processing with optimizing dynamic spectrum method was set as experimental group, while control group was with classical method based on fast Fourier transform. The model for hemoglobin prediction was established with partial least square regression. In the experimental group, the average prediction correlation coefficient was 0.8399, while that of the control group was 0.6686. The results demonstrate that the optimizing method has a good accuracy improvement for noninvasive hemoglobin measurement. The optimizing dynamic spectrum method combining statistical characteristics analysis as a modified analytical method has a promising application prospect of application in noninvasive blood component measurement field.