G. B. Salah, K. Abbes, C. Abdelmoula, Mohamed Hédi Abdelmoula, Mohamed Turki, M. Masmoudi
{"title":"食道压力Pes检测阻塞性睡眠呼吸暂停OSA","authors":"G. B. Salah, K. Abbes, C. Abdelmoula, Mohamed Hédi Abdelmoula, Mohamed Turki, M. Masmoudi","doi":"10.1109/DTSS.2019.8914748","DOIUrl":null,"url":null,"abstract":"Obstructive Sleep Apnea OSA is a potentially common pathology characterized by partial or complete collapses of upper. If diagnosed late and untreated, it can lead to serious complications especially which are related to cardiovascular system. However, most of cases are undiagnosed because of expenses and discomfort of hospital diagnostic. Therefore, new techniques are being developed by investigators to detect OSA. In this paper, we present a new approach to control the occurrence of OSA based on esophageal pressure parameter. Then, we have developed an efficient algorithm to process the signal in real-time to detect apnea episodes.","PeriodicalId":342516,"journal":{"name":"2019 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Obstructive Sleep Apnea OSA detection through esophageal Pressure Pes\",\"authors\":\"G. B. Salah, K. Abbes, C. Abdelmoula, Mohamed Hédi Abdelmoula, Mohamed Turki, M. Masmoudi\",\"doi\":\"10.1109/DTSS.2019.8914748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Obstructive Sleep Apnea OSA is a potentially common pathology characterized by partial or complete collapses of upper. If diagnosed late and untreated, it can lead to serious complications especially which are related to cardiovascular system. However, most of cases are undiagnosed because of expenses and discomfort of hospital diagnostic. Therefore, new techniques are being developed by investigators to detect OSA. In this paper, we present a new approach to control the occurrence of OSA based on esophageal pressure parameter. Then, we have developed an efficient algorithm to process the signal in real-time to detect apnea episodes.\",\"PeriodicalId\":342516,\"journal\":{\"name\":\"2019 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)\",\"volume\":\"205 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DTSS.2019.8914748\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTSS.2019.8914748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Obstructive Sleep Apnea OSA detection through esophageal Pressure Pes
Obstructive Sleep Apnea OSA is a potentially common pathology characterized by partial or complete collapses of upper. If diagnosed late and untreated, it can lead to serious complications especially which are related to cardiovascular system. However, most of cases are undiagnosed because of expenses and discomfort of hospital diagnostic. Therefore, new techniques are being developed by investigators to detect OSA. In this paper, we present a new approach to control the occurrence of OSA based on esophageal pressure parameter. Then, we have developed an efficient algorithm to process the signal in real-time to detect apnea episodes.