V. Aharonson, Sarah R. Ward, David Anderson, D. Rubin, M. Postema
{"title":"用于运动障碍检测的形状跟踪应用程序","authors":"V. Aharonson, Sarah R. Ward, David Anderson, D. Rubin, M. Postema","doi":"10.1109/SAUPEC/RobMech/PRASA48453.2020.9041051","DOIUrl":null,"url":null,"abstract":"Shape tracing tests for the detection and assessment of hand movement disorders are predominantly performed manually in the presence of a clinician. These procedures are therefore labour intensive, expensive, and subjective. Digital tests have been proposed to automate this assessment process, to answer the need of affordable healthcare for all. A straightforward automation solution is a conversion of the shape tracing tests from pen and paper to a mobile device. This study implemements realtime dynamic touch detection on a mid-range tablet for shape tracing. The tracing app developed was tested on 20 movement disorder patients and 10 control subjects. The results convey that the interface allows for successful self-administration of the tests. For all subjects, the accuracy was successfully preserved in the real-time dynamic acquisition of the tracing process.","PeriodicalId":215514,"journal":{"name":"2020 International SAUPEC/RobMech/PRASA Conference","volume":"171 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shape tracing app for movement disorder detection\",\"authors\":\"V. Aharonson, Sarah R. Ward, David Anderson, D. Rubin, M. Postema\",\"doi\":\"10.1109/SAUPEC/RobMech/PRASA48453.2020.9041051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Shape tracing tests for the detection and assessment of hand movement disorders are predominantly performed manually in the presence of a clinician. These procedures are therefore labour intensive, expensive, and subjective. Digital tests have been proposed to automate this assessment process, to answer the need of affordable healthcare for all. A straightforward automation solution is a conversion of the shape tracing tests from pen and paper to a mobile device. This study implemements realtime dynamic touch detection on a mid-range tablet for shape tracing. The tracing app developed was tested on 20 movement disorder patients and 10 control subjects. The results convey that the interface allows for successful self-administration of the tests. For all subjects, the accuracy was successfully preserved in the real-time dynamic acquisition of the tracing process.\",\"PeriodicalId\":215514,\"journal\":{\"name\":\"2020 International SAUPEC/RobMech/PRASA Conference\",\"volume\":\"171 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International SAUPEC/RobMech/PRASA Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International SAUPEC/RobMech/PRASA Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Shape tracing tests for the detection and assessment of hand movement disorders are predominantly performed manually in the presence of a clinician. These procedures are therefore labour intensive, expensive, and subjective. Digital tests have been proposed to automate this assessment process, to answer the need of affordable healthcare for all. A straightforward automation solution is a conversion of the shape tracing tests from pen and paper to a mobile device. This study implemements realtime dynamic touch detection on a mid-range tablet for shape tracing. The tracing app developed was tested on 20 movement disorder patients and 10 control subjects. The results convey that the interface allows for successful self-administration of the tests. For all subjects, the accuracy was successfully preserved in the real-time dynamic acquisition of the tracing process.