R. A. Hameed, Mohannad K. Sabir, M. Fadhel, O. Al-Shamma, Laith Alzubaidi
{"title":"基于呼吸信号的人类情感分类","authors":"R. A. Hameed, Mohannad K. Sabir, M. Fadhel, O. Al-Shamma, Laith Alzubaidi","doi":"10.1145/3321289.3321315","DOIUrl":null,"url":null,"abstract":"Interactions between people commonly expressed and possessed emotions due to the human beings. Respiration is one of the parameters that reflects an emotion. The reasonable hypothesis, that various respiratory patterns are associated with various emotions, has enhanced the evidence for links between respiration and emotion. For instance, breathing turns out to be, deeper and slower at leisure or relief, shallower and faster at scare or terror, and deeper and faster at anger or excitement. In this study, the breathing signals, which include the features; airflow rate and volume, are acquired from the BIOPAC instrument. The extracted features, which include Max/Min and Mean/Variance of the main features, are analyzed using Fast Fourier Transform (FFT) and classified using Orang open source program, respectively. The result is very successful and agreed by 80%, which in turn, extremely accepted by the researchers.","PeriodicalId":375095,"journal":{"name":"Proceedings of the International Conference on Information and Communication Technology - ICICT '19","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Human emotion classification based on respiration signal\",\"authors\":\"R. A. Hameed, Mohannad K. Sabir, M. Fadhel, O. Al-Shamma, Laith Alzubaidi\",\"doi\":\"10.1145/3321289.3321315\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interactions between people commonly expressed and possessed emotions due to the human beings. Respiration is one of the parameters that reflects an emotion. The reasonable hypothesis, that various respiratory patterns are associated with various emotions, has enhanced the evidence for links between respiration and emotion. For instance, breathing turns out to be, deeper and slower at leisure or relief, shallower and faster at scare or terror, and deeper and faster at anger or excitement. In this study, the breathing signals, which include the features; airflow rate and volume, are acquired from the BIOPAC instrument. The extracted features, which include Max/Min and Mean/Variance of the main features, are analyzed using Fast Fourier Transform (FFT) and classified using Orang open source program, respectively. The result is very successful and agreed by 80%, which in turn, extremely accepted by the researchers.\",\"PeriodicalId\":375095,\"journal\":{\"name\":\"Proceedings of the International Conference on Information and Communication Technology - ICICT '19\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Information and Communication Technology - ICICT '19\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3321289.3321315\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Information and Communication Technology - ICICT '19","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3321289.3321315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Human emotion classification based on respiration signal
Interactions between people commonly expressed and possessed emotions due to the human beings. Respiration is one of the parameters that reflects an emotion. The reasonable hypothesis, that various respiratory patterns are associated with various emotions, has enhanced the evidence for links between respiration and emotion. For instance, breathing turns out to be, deeper and slower at leisure or relief, shallower and faster at scare or terror, and deeper and faster at anger or excitement. In this study, the breathing signals, which include the features; airflow rate and volume, are acquired from the BIOPAC instrument. The extracted features, which include Max/Min and Mean/Variance of the main features, are analyzed using Fast Fourier Transform (FFT) and classified using Orang open source program, respectively. The result is very successful and agreed by 80%, which in turn, extremely accepted by the researchers.