Zhen Zhang, Hongqiang Li, Zheng Gong, Rize Jin, Tae-Sun Chung
{"title":"兼容心电诊断云计算框架及原型应用","authors":"Zhen Zhang, Hongqiang Li, Zheng Gong, Rize Jin, Tae-Sun Chung","doi":"10.1145/3404555.3404640","DOIUrl":null,"url":null,"abstract":"The ECG signal analysis and diagnosis algorithms have been studied for decades. There are some state of art algorithms that have been developed. In this paper, we proposed a compatible ECG automatic diagnosis Cloud Computing framework in order to integrate these exist algorithms. On the other hand, there are many studies regarding the IoT based health diagnosis system. But there are few of that aiming at the personal use health monitor and diagnose. Basing on our proposed framework, users can diagnose their heart health status by themselves conveniently anywhere and anytime through the mobile application. The ECG character automatic classification computing algorithm is compatible for Python and MATLAB by introducing the hybrid programming technic on the cloud computing side. So that, it is easy for researchers to integrate their developed algorithm into this framework to build an application quickly. We developed a prototype application as well to verify the availability of this framework.","PeriodicalId":220526,"journal":{"name":"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Compatible ECG Diagnosis Cloud Computing Framework and Prototype Application\",\"authors\":\"Zhen Zhang, Hongqiang Li, Zheng Gong, Rize Jin, Tae-Sun Chung\",\"doi\":\"10.1145/3404555.3404640\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ECG signal analysis and diagnosis algorithms have been studied for decades. There are some state of art algorithms that have been developed. In this paper, we proposed a compatible ECG automatic diagnosis Cloud Computing framework in order to integrate these exist algorithms. On the other hand, there are many studies regarding the IoT based health diagnosis system. But there are few of that aiming at the personal use health monitor and diagnose. Basing on our proposed framework, users can diagnose their heart health status by themselves conveniently anywhere and anytime through the mobile application. The ECG character automatic classification computing algorithm is compatible for Python and MATLAB by introducing the hybrid programming technic on the cloud computing side. So that, it is easy for researchers to integrate their developed algorithm into this framework to build an application quickly. We developed a prototype application as well to verify the availability of this framework.\",\"PeriodicalId\":220526,\"journal\":{\"name\":\"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3404555.3404640\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3404555.3404640","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Compatible ECG Diagnosis Cloud Computing Framework and Prototype Application
The ECG signal analysis and diagnosis algorithms have been studied for decades. There are some state of art algorithms that have been developed. In this paper, we proposed a compatible ECG automatic diagnosis Cloud Computing framework in order to integrate these exist algorithms. On the other hand, there are many studies regarding the IoT based health diagnosis system. But there are few of that aiming at the personal use health monitor and diagnose. Basing on our proposed framework, users can diagnose their heart health status by themselves conveniently anywhere and anytime through the mobile application. The ECG character automatic classification computing algorithm is compatible for Python and MATLAB by introducing the hybrid programming technic on the cloud computing side. So that, it is easy for researchers to integrate their developed algorithm into this framework to build an application quickly. We developed a prototype application as well to verify the availability of this framework.