Linda Senigagliesi, Manola Ricciuti, Gianluca Ciattaglia, E. Gambi
{"title":"Physiological Parameters Extraction by Accelerometric Signal Analysis During Sleep","authors":"Linda Senigagliesi, Manola Ricciuti, Gianluca Ciattaglia, E. Gambi","doi":"10.1109/ISCC55528.2022.9912931","DOIUrl":null,"url":null,"abstract":"Sleep quality is an index of well-being, since sleep disorders, such as sleep apnea, may constitute a health risk. A constant monitoring of subjects, especially when there are heart or respiratory diseases, is essential. The present paper aims to offer a non-invasive and comfortable sleep monitoring, by employing a BallistoCardioGraphic (BCG) signal processing. In particular, with a BCG device located below the mattress, we are able to extract the heart rate, respiratory rate and, therefore, to exploit this information to develop an automatic sleep apnea recognition algorithm. The automatic approach presented has proven to achieve accuracy and reliability and could represent a valid resource to prevent serious damages during sleep.","PeriodicalId":309606,"journal":{"name":"2022 IEEE Symposium on Computers and Communications (ISCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Symposium on Computers and Communications (ISCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCC55528.2022.9912931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Sleep quality is an index of well-being, since sleep disorders, such as sleep apnea, may constitute a health risk. A constant monitoring of subjects, especially when there are heart or respiratory diseases, is essential. The present paper aims to offer a non-invasive and comfortable sleep monitoring, by employing a BallistoCardioGraphic (BCG) signal processing. In particular, with a BCG device located below the mattress, we are able to extract the heart rate, respiratory rate and, therefore, to exploit this information to develop an automatic sleep apnea recognition algorithm. The automatic approach presented has proven to achieve accuracy and reliability and could represent a valid resource to prevent serious damages during sleep.
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