A. A, Devika. T.D, Varsha. K.R, Sree Sanjanaa Bose.S
{"title":"基于物联网的多参数患者监护系统的设计与开发","authors":"A. A, Devika. T.D, Varsha. K.R, Sree Sanjanaa Bose.S","doi":"10.1109/ICACCS48705.2020.9074293","DOIUrl":null,"url":null,"abstract":"Multi-parameter patient monitor captures the physiological vital signs and continuously monitors the patient condition by alerting the medical staff via alarm. The revolutionization in machine learning techniques and Internet of Things (IOT) in healthcare. In this paper, we have designed an IOT based MPM system where four parameter namely heart rate, respiration rate, oxygen saturation and temperature are monitored using corresponding sensors and an email is sent to patient's guardian in case of emergency. The project also focuses on improving the performance of MPM system using Support Vector Machine(SVM) algorithm. The classification accuracy of 95% has been achieved.","PeriodicalId":439003,"journal":{"name":"2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)","volume":"1130 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Design and Development of IOT Based Multi-Parameter Patient Monitoring System\",\"authors\":\"A. A, Devika. T.D, Varsha. K.R, Sree Sanjanaa Bose.S\",\"doi\":\"10.1109/ICACCS48705.2020.9074293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-parameter patient monitor captures the physiological vital signs and continuously monitors the patient condition by alerting the medical staff via alarm. The revolutionization in machine learning techniques and Internet of Things (IOT) in healthcare. In this paper, we have designed an IOT based MPM system where four parameter namely heart rate, respiration rate, oxygen saturation and temperature are monitored using corresponding sensors and an email is sent to patient's guardian in case of emergency. The project also focuses on improving the performance of MPM system using Support Vector Machine(SVM) algorithm. The classification accuracy of 95% has been achieved.\",\"PeriodicalId\":439003,\"journal\":{\"name\":\"2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)\",\"volume\":\"1130 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACCS48705.2020.9074293\",\"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 6th International Conference on Advanced Computing and Communication Systems (ICACCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACCS48705.2020.9074293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Development of IOT Based Multi-Parameter Patient Monitoring System
Multi-parameter patient monitor captures the physiological vital signs and continuously monitors the patient condition by alerting the medical staff via alarm. The revolutionization in machine learning techniques and Internet of Things (IOT) in healthcare. In this paper, we have designed an IOT based MPM system where four parameter namely heart rate, respiration rate, oxygen saturation and temperature are monitored using corresponding sensors and an email is sent to patient's guardian in case of emergency. The project also focuses on improving the performance of MPM system using Support Vector Machine(SVM) algorithm. The classification accuracy of 95% has been achieved.