{"title":"Design of a FHIR interface for wearable healthcare devices","authors":"Junghoon Lee, Seungah Jang, Eunjung Park","doi":"10.1109/ICUFN57995.2023.10199866","DOIUrl":null,"url":null,"abstract":"This paper designs a FHIR (Fast Healthcare Interoperable Resources) interface to provide a standard clinical data exchange for personal wearable healthcare devices, aiming at taking them as a part of remote medical services. In uploading, the agent converts the series of sensor readings, such as electrocardiogram, to the JSON-based standard format, divides it into several subparts if necessary, finds the references to relevant resources, and submits the request via RESTful API. For download, a Python client specifies the set of search parameters, gets the target resources from the server, converts them to the language-specific data structure, and hands over to the analysis module. Our testbed is implemented, making use of diverse FHIR tools including the FRED resource editor and the HAPI server.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUFN57995.2023.10199866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper designs a FHIR (Fast Healthcare Interoperable Resources) interface to provide a standard clinical data exchange for personal wearable healthcare devices, aiming at taking them as a part of remote medical services. In uploading, the agent converts the series of sensor readings, such as electrocardiogram, to the JSON-based standard format, divides it into several subparts if necessary, finds the references to relevant resources, and submits the request via RESTful API. For download, a Python client specifies the set of search parameters, gets the target resources from the server, converts them to the language-specific data structure, and hands over to the analysis module. Our testbed is implemented, making use of diverse FHIR tools including the FRED resource editor and the HAPI server.