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《Intelligent Computer and Applications》 2019-04
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Research on non-contact apnea algorithm based on Convolutional Neural Network

HUANG Yongfeng;JIANG Yipeng;YANG Shuchen;School of Computer Science and Technology,Donghua University;Shanghai Yueyang Medical Technology Co.,Ltd.;  
Based on the piezoelectric ceramics sensor signal,this paper proposes a one-dimensional Convolutional Neural Network detection algorithm for sleep apnea syndrome. The Convolutional Neural Network model consists of six layers of convolutional layers. Each layer containing a Re LU activation function,a batch normalization layer,a dropout layer,and a max pooling layer. Simultaneously,the piezoelectric ceramics sensor signals and polysomnographic signals of 11 subjects are collected and 40 988 balanced samples are generated. The training set,verification set and test set are divided according to the ratio of 60%,20% and 20%. Based on the above,using the model proposed in this paper,an accuracy of 92.76%,a precision of 88.67%,a recall of 98.06% and an F1-score of 93.13% are attached with the test dataset.
【CateGory Index】: TP212.9;R766
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