The Quality Assessment and Selection of Dynamic Spectrum Signal

: Near infrared spectroscopy analysis, as a kind of nondestructive real-time continuous detection method, has provided ideas for the noninvasive measurement of blood components. In this article, in order to ensure the accuracy and reliability of the collected spectral data, the 405 acquired samples are evaluated by combining valid single edge counts of dynamic spectrum pulse wave in the time domain with the quality factor Q value of dynamic spectrum pulse wave in the frequency domain. As a result, the abnormal samples are removed and 218 cases of valid samples are selected. We use the dynamic spectrum data of the selected 218 samples as the experimental group and another 218 samples as a control group modeling analysis with the hemoglobin concentration of the corresponding samples. Each group select 200 cases of samples as a calibration set and 18 cases of sample as a prediction set. The prediction accuracy of the experimental group reach 93.8%. The prediction accuracy of the two control group respectively evaluated by the valid single edge counts or Q value are 65.6% and 67.7% and the three unfiltered control groups are 53.7%, 33.3%, 42.6% respectively. The prediction mean relative error (MSEP) of the experimental group is 0.067 5, the other two control groups are 0.072 3 and 0.072 2, and the other three control groups are 0.082.3, 0.078 9, 0.082 8. So compared with another control groups, the MSEP of the experimental group is the minimal. The results show that the filtering method of the spectral data samples through combining time domain with frequency domain is reliable and effective.this will provide a method to the precision research of dynamic spectrum noninvasive detection.