{"title":"基于活动的病人监护系统风险分析的情境感知框架","authors":"S. Don, Eumin Choi, D. Min","doi":"10.1109/ICAWST.2011.6163087","DOIUrl":null,"url":null,"abstract":"This paper presents a conceptual architecture of activity based risk analysis for monitoring the health status of the patients in their residence. By incorporating the patient records and medical domain knowledge, it will be easy to detect and prevent accidental events immediately even if the patient is not in the hospital. Data are collected using wearable sensors and transmitted to server using a smart phone through internet or mobile network. The received events are filtered, aggregated and predicted based on the concept of Situation Awareness. This gives high level information that can surpass the patient conditions. However, building this high level information is still an open challenge. To demonstrate the feasibility of the proposed system, some application scenarios are considered.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A situation aware framework for activity based risk analysis of patient monitoring system\",\"authors\":\"S. Don, Eumin Choi, D. Min\",\"doi\":\"10.1109/ICAWST.2011.6163087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a conceptual architecture of activity based risk analysis for monitoring the health status of the patients in their residence. By incorporating the patient records and medical domain knowledge, it will be easy to detect and prevent accidental events immediately even if the patient is not in the hospital. Data are collected using wearable sensors and transmitted to server using a smart phone through internet or mobile network. The received events are filtered, aggregated and predicted based on the concept of Situation Awareness. This gives high level information that can surpass the patient conditions. However, building this high level information is still an open challenge. To demonstrate the feasibility of the proposed system, some application scenarios are considered.\",\"PeriodicalId\":126169,\"journal\":{\"name\":\"2011 3rd International Conference on Awareness Science and Technology (iCAST)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 3rd International Conference on Awareness Science and Technology (iCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAWST.2011.6163087\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAWST.2011.6163087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A situation aware framework for activity based risk analysis of patient monitoring system
This paper presents a conceptual architecture of activity based risk analysis for monitoring the health status of the patients in their residence. By incorporating the patient records and medical domain knowledge, it will be easy to detect and prevent accidental events immediately even if the patient is not in the hospital. Data are collected using wearable sensors and transmitted to server using a smart phone through internet or mobile network. The received events are filtered, aggregated and predicted based on the concept of Situation Awareness. This gives high level information that can surpass the patient conditions. However, building this high level information is still an open challenge. To demonstrate the feasibility of the proposed system, some application scenarios are considered.