{"title":"个人健康行动计划的智能卫生系统","authors":"Jochen Meyer, Susanne CJ Boll","doi":"10.1109/HealthCom.2014.7001877","DOIUrl":null,"url":null,"abstract":"Smart health systems such as networked activity trackers, scales, or sports watches allow monitoring many aspects of a healthy lifestyle. Nevertheless there is a semantic gap between these systems' measurements and the users' personal health action plan that is not bridged by existing health data aggregators. We describe representative types of health data as measured today and suggest a simple classification of data based on temporality of the data. We present a mapping of physical devices to health action plans that is device-agnostic and bridges this semantic gap. A key concept is the mapping of logical devices to primary health features that translates measurements to a meaningful health concept. We describe a prototype system implementing our mapping and providing lessons learned. The approach shows to be feasible to describe typical personal health action plans.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Smart health systems for personal health action plans\",\"authors\":\"Jochen Meyer, Susanne CJ Boll\",\"doi\":\"10.1109/HealthCom.2014.7001877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart health systems such as networked activity trackers, scales, or sports watches allow monitoring many aspects of a healthy lifestyle. Nevertheless there is a semantic gap between these systems' measurements and the users' personal health action plan that is not bridged by existing health data aggregators. We describe representative types of health data as measured today and suggest a simple classification of data based on temporality of the data. We present a mapping of physical devices to health action plans that is device-agnostic and bridges this semantic gap. A key concept is the mapping of logical devices to primary health features that translates measurements to a meaningful health concept. We describe a prototype system implementing our mapping and providing lessons learned. The approach shows to be feasible to describe typical personal health action plans.\",\"PeriodicalId\":269964,\"journal\":{\"name\":\"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2014.7001877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2014.7001877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Smart health systems for personal health action plans
Smart health systems such as networked activity trackers, scales, or sports watches allow monitoring many aspects of a healthy lifestyle. Nevertheless there is a semantic gap between these systems' measurements and the users' personal health action plan that is not bridged by existing health data aggregators. We describe representative types of health data as measured today and suggest a simple classification of data based on temporality of the data. We present a mapping of physical devices to health action plans that is device-agnostic and bridges this semantic gap. A key concept is the mapping of logical devices to primary health features that translates measurements to a meaningful health concept. We describe a prototype system implementing our mapping and providing lessons learned. The approach shows to be feasible to describe typical personal health action plans.