{"title":"基于面部视频的认知测试结果评价","authors":"Terumi Umematsu, M. Tsujikawa, H. Sawada","doi":"10.23919/APSIPAASC55919.2022.9980211","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a method of discriminating between concentration and non-concentration on the basis of facial videos, and we confirm the usefulness of excluding cognitive test results when a user has not been concentrating. In a preliminary experiment, we have confirmed that level of concentration has a strong impact on correct answer rates in memory tests. Our proposed concentration/non-concentration discrimination method uses 15 features extracted from facial videos, including blinking, gazing, and facial expressions (Action Units), and discriminates between concentration and non-concentration, which are reflected in terms of a binary correct answer label set based on subjectively rated concentration levels. In the preliminary experiment, memory test scores during non-concentration states were lower than those during concentration states by an average of 18%. This has usually been included as measurement error, and, by excluding scores during non-concentration states using the proposed method, measurement error was reduced to 4%. The proposed method is shown to be capable of obtaining test results that indicate true cognitive functions when people are concentrating, making possible a more accurate understanding of cognitive functions.","PeriodicalId":382967,"journal":{"name":"2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Cognitive Test Results Using Concentration Estimation from Facial Videos\",\"authors\":\"Terumi Umematsu, M. Tsujikawa, H. Sawada\",\"doi\":\"10.23919/APSIPAASC55919.2022.9980211\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a method of discriminating between concentration and non-concentration on the basis of facial videos, and we confirm the usefulness of excluding cognitive test results when a user has not been concentrating. In a preliminary experiment, we have confirmed that level of concentration has a strong impact on correct answer rates in memory tests. Our proposed concentration/non-concentration discrimination method uses 15 features extracted from facial videos, including blinking, gazing, and facial expressions (Action Units), and discriminates between concentration and non-concentration, which are reflected in terms of a binary correct answer label set based on subjectively rated concentration levels. In the preliminary experiment, memory test scores during non-concentration states were lower than those during concentration states by an average of 18%. This has usually been included as measurement error, and, by excluding scores during non-concentration states using the proposed method, measurement error was reduced to 4%. The proposed method is shown to be capable of obtaining test results that indicate true cognitive functions when people are concentrating, making possible a more accurate understanding of cognitive functions.\",\"PeriodicalId\":382967,\"journal\":{\"name\":\"2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/APSIPAASC55919.2022.9980211\",\"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 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/APSIPAASC55919.2022.9980211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluation of Cognitive Test Results Using Concentration Estimation from Facial Videos
In this paper, we propose a method of discriminating between concentration and non-concentration on the basis of facial videos, and we confirm the usefulness of excluding cognitive test results when a user has not been concentrating. In a preliminary experiment, we have confirmed that level of concentration has a strong impact on correct answer rates in memory tests. Our proposed concentration/non-concentration discrimination method uses 15 features extracted from facial videos, including blinking, gazing, and facial expressions (Action Units), and discriminates between concentration and non-concentration, which are reflected in terms of a binary correct answer label set based on subjectively rated concentration levels. In the preliminary experiment, memory test scores during non-concentration states were lower than those during concentration states by an average of 18%. This has usually been included as measurement error, and, by excluding scores during non-concentration states using the proposed method, measurement error was reduced to 4%. The proposed method is shown to be capable of obtaining test results that indicate true cognitive functions when people are concentrating, making possible a more accurate understanding of cognitive functions.