{"title":"基于手指脉冲波信号和卷积神经网络的焦虑预测","authors":"Jianliang Gan, Junsheng Yu","doi":"10.1109/CSRSWTC56224.2022.10098328","DOIUrl":null,"url":null,"abstract":"One of the key elements of Traditional Chinese Medicine (TCM) is the pulse wave diagnosis technique, and the pulse wave signal contains a variety of physiological information. A deep learning model was used in this study to train and predict 500 pieces of pulse wave data from adult males during the novel coronavirus epidemic, and it was able to do so with a prediction accuracy of over 70%.","PeriodicalId":198168,"journal":{"name":"2022 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Anxiety Prediction Based on Finger Pulse Wave Signal and Convolutional Neural Network\",\"authors\":\"Jianliang Gan, Junsheng Yu\",\"doi\":\"10.1109/CSRSWTC56224.2022.10098328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the key elements of Traditional Chinese Medicine (TCM) is the pulse wave diagnosis technique, and the pulse wave signal contains a variety of physiological information. A deep learning model was used in this study to train and predict 500 pieces of pulse wave data from adult males during the novel coronavirus epidemic, and it was able to do so with a prediction accuracy of over 70%.\",\"PeriodicalId\":198168,\"journal\":{\"name\":\"2022 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSRSWTC56224.2022.10098328\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSRSWTC56224.2022.10098328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Anxiety Prediction Based on Finger Pulse Wave Signal and Convolutional Neural Network
One of the key elements of Traditional Chinese Medicine (TCM) is the pulse wave diagnosis technique, and the pulse wave signal contains a variety of physiological information. A deep learning model was used in this study to train and predict 500 pieces of pulse wave data from adult males during the novel coronavirus epidemic, and it was able to do so with a prediction accuracy of over 70%.
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