{"title":"远程呼吸监测的视频处理","authors":"D. Alinovi","doi":"10.5565/rev/elcvia.1124","DOIUrl":null,"url":null,"abstract":"Monitoring of vital signs is a key tool in medical diagnostics. Among fundamental vital parameters, the Respiratory Rate (RR) plays an important role as indicator of possible pathological events. For this reason, respiration needs to be carefully monitored in order to detect potential signs indicating possible changes of health conditions. In this work, novel techniques for the visualization and analysis of respiration by remote and non-invasive video monitoring, based on the study of breathing-related movements, are proposed. The lack of large video databases, associated with clinical data, essential for performance evaluation and optimization of the video processing-based algorithms, is also addressed; statistical models of respiration and apnea events are proposed together with proper simulators, useful to test the remote monitoring algorithms.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"52 1","pages":"9-12"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Video Processing for Remote Respiration Monitoring\",\"authors\":\"D. Alinovi\",\"doi\":\"10.5565/rev/elcvia.1124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Monitoring of vital signs is a key tool in medical diagnostics. Among fundamental vital parameters, the Respiratory Rate (RR) plays an important role as indicator of possible pathological events. For this reason, respiration needs to be carefully monitored in order to detect potential signs indicating possible changes of health conditions. In this work, novel techniques for the visualization and analysis of respiration by remote and non-invasive video monitoring, based on the study of breathing-related movements, are proposed. The lack of large video databases, associated with clinical data, essential for performance evaluation and optimization of the video processing-based algorithms, is also addressed; statistical models of respiration and apnea events are proposed together with proper simulators, useful to test the remote monitoring algorithms.\",\"PeriodicalId\":38711,\"journal\":{\"name\":\"Electronic Letters on Computer Vision and Image Analysis\",\"volume\":\"52 1\",\"pages\":\"9-12\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Letters on Computer Vision and Image Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5565/rev/elcvia.1124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Letters on Computer Vision and Image Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5565/rev/elcvia.1124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Video Processing for Remote Respiration Monitoring
Monitoring of vital signs is a key tool in medical diagnostics. Among fundamental vital parameters, the Respiratory Rate (RR) plays an important role as indicator of possible pathological events. For this reason, respiration needs to be carefully monitored in order to detect potential signs indicating possible changes of health conditions. In this work, novel techniques for the visualization and analysis of respiration by remote and non-invasive video monitoring, based on the study of breathing-related movements, are proposed. The lack of large video databases, associated with clinical data, essential for performance evaluation and optimization of the video processing-based algorithms, is also addressed; statistical models of respiration and apnea events are proposed together with proper simulators, useful to test the remote monitoring algorithms.