Mr. Xin Yang Profile

Xin Yang

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Proceedings Article | 27 August 2024 Paper

Analysis of temperature effects on plethysmography testing box and research on box pressure correction method

Rui Wang, Yang Huang, Xin Yang, Guo Yang, Zhihui Wang

Proceedings Volume 13252, 1325226 (2024) https://doi.org/10.1117/12.3044156

KEYWORDS: Temperature metrology, Body temperature, Sensors, Data modeling, Neural networks, Education and training, Lung, Genetic algorithms, Chronic obstructive pulmonary disease, Vacuum chambers

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In order to further improve the accuracy and measurement efficiency of the plethysmography method, this paper proposes a genetic algorithm-based optimized back-propagation (GA-BP) neural network method for the correction of the pressure inside the box of the plethysmography box. In this paper, we first analyze how the temperature affects the accuracy and measurement efficiency of plethysmography testing box results, and give the expression of the relationship between the local temperature inside the plethysmography testing box and the pressure inside the box, through the correction of the measurement pressure, the temperature influence of the human body into the plethysmography testing box can be reduced, so as to improve the accuracy of the measurement results. By setting the appropriate temperature detection points, establishing the BP neural network pressure prediction model based on the optimization of genetic algorithm, using the model to predict the pressure changes of different human bodies entering the box, and using the prediction to correct the effect of human body temperature on the pressure inside the box in real time during the measurement process. Finally, the results of simulation and experimental data verified its superiority over the traditional method in terms of accuracy and efficiency performance, which has an important application value in clinical lung function testing.

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