{"title":"疼痛表达作为一种生物特征:为什么患者自我报告的疼痛与客观测量的疼痛不匹配?","authors":"M. A. Haque, Kamal Nasrollahi, T. Moeslund","doi":"10.1109/ISBA.2017.7947690","DOIUrl":null,"url":null,"abstract":"Developing a vision-based efficient and automatic pain intensity measurement system requires the understanding of the relationship between self-reported pain intensity and pain expression in the facial videos. In this paper, we first demonstrate how pain expression in facial video frames may not match with the self-reported score. This is because the pain and non-pain frames are not always visually distinctive; though the self-report tells different story of having pain and non-pain status. On the other hand previous studies reported that general facial expressions can be used as biometrics. Thus, in this paper we investigated the relevance of pain expression from facial video to be used as a biometric or soft-biometric trait. In order to do that, we employed a biometric person recognition scenario by using features obtained from the pain expression pattern found in the temporal axis of subjects' videos. The results confirmed that the pain expression patterns have distinctive features between the subjects of the UNBC McMaster shoulder pain database. We concluded that as the pain expression patterns have subjective features as a biometric, this can also cause the difference between self-reported pain level and the visually observed pain intensity level.","PeriodicalId":436086,"journal":{"name":"2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Pain expression as a biometric: Why patients' self-reported pain doesn't match with the objectively measured pain?\",\"authors\":\"M. A. Haque, Kamal Nasrollahi, T. Moeslund\",\"doi\":\"10.1109/ISBA.2017.7947690\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Developing a vision-based efficient and automatic pain intensity measurement system requires the understanding of the relationship between self-reported pain intensity and pain expression in the facial videos. In this paper, we first demonstrate how pain expression in facial video frames may not match with the self-reported score. This is because the pain and non-pain frames are not always visually distinctive; though the self-report tells different story of having pain and non-pain status. On the other hand previous studies reported that general facial expressions can be used as biometrics. Thus, in this paper we investigated the relevance of pain expression from facial video to be used as a biometric or soft-biometric trait. In order to do that, we employed a biometric person recognition scenario by using features obtained from the pain expression pattern found in the temporal axis of subjects' videos. The results confirmed that the pain expression patterns have distinctive features between the subjects of the UNBC McMaster shoulder pain database. We concluded that as the pain expression patterns have subjective features as a biometric, this can also cause the difference between self-reported pain level and the visually observed pain intensity level.\",\"PeriodicalId\":436086,\"journal\":{\"name\":\"2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBA.2017.7947690\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBA.2017.7947690","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pain expression as a biometric: Why patients' self-reported pain doesn't match with the objectively measured pain?
Developing a vision-based efficient and automatic pain intensity measurement system requires the understanding of the relationship between self-reported pain intensity and pain expression in the facial videos. In this paper, we first demonstrate how pain expression in facial video frames may not match with the self-reported score. This is because the pain and non-pain frames are not always visually distinctive; though the self-report tells different story of having pain and non-pain status. On the other hand previous studies reported that general facial expressions can be used as biometrics. Thus, in this paper we investigated the relevance of pain expression from facial video to be used as a biometric or soft-biometric trait. In order to do that, we employed a biometric person recognition scenario by using features obtained from the pain expression pattern found in the temporal axis of subjects' videos. The results confirmed that the pain expression patterns have distinctive features between the subjects of the UNBC McMaster shoulder pain database. We concluded that as the pain expression patterns have subjective features as a biometric, this can also cause the difference between self-reported pain level and the visually observed pain intensity level.