Photoacoustic blood glucose multiple factors measurement based on BP neural network algorithm

Chengxin Xiong; Tao Liu; Wenping Peng; Junli Wu; Zhong Ren

doi:10.1117/12.2645386

26 October 2022 Photoacoustic blood glucose multiple factors measurement based on BP neural network algorithm

Chengxin Xiong, Tao Liu, Wenping Peng, Junli Wu, Zhong Ren

Proceedings Volume 12461, First Conference on Biomedical Photonics and Cross-Fusion (BPC 2022); 1246102 (2022) https://doi.org/10.1117/12.2645386
Event: First Conference on Biomedical Photonics and Cross-Fusion (BPC 2022), 2022, Shanghai, China

Abstract

In this work, to study the effects of multiple factors on the blood glucose photoacoustic detection, five different factors including the laser energy, concentration, temperature, flow velocity and detection distance were considered, and a set of blood glucose photoacoustic detection system combined multiple influence factors was established. The time-resolved photoacoustic signals and peak-to-peak spectra of 625 groups of blood samples were obtained. To predict the blood glucose concentration with high accuracy under the influence of multiple factors, back propagation (BP) neural network was used to train five different factors and photoacoustic peak-to-peak values of 500 groups of blood samples, and 125 groups of blood samples were used as the test samples. Meanwhile, the effects of neurons number in the hidden layer, learning rate and training times on the root-mean-square error(RMSE) of predicting blood glucose concentration were investigated. Under the optimal parameters, the RMSE of blood glucose concentration for 125 groups of test blood samples is about 0.807679mmol/L. Compared with the results of partial least square (PLS) algorithm with RMSE of 1.78mmol/L, it is demonstrated that the BP algorithm has good performance in the prediction blood glucose concentration under multiple influence factors based on photoacoustic detection technology.

Citation Download Citation

Chengxin Xiong, Tao Liu, Wenping Peng, Junli Wu, and Zhong Ren "Photoacoustic blood glucose multiple factors measurement based on BP neural network algorithm", Proc. SPIE 12461, First Conference on Biomedical Photonics and Cross-Fusion (BPC 2022), 1246102 (26 October 2022); https://doi.org/10.1117/12.2645386

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