German Shein, Sankar Sathynaryanan, A. Sagahyroon, Michel Pasquier
{"title":"Sensors equipped mattress for assessing sleep apnea symptoms","authors":"German Shein, Sankar Sathynaryanan, A. Sagahyroon, Michel Pasquier","doi":"10.1109/ICWISE.2017.8267159","DOIUrl":null,"url":null,"abstract":"Sleep apnea is a sleep disorder characterized mainly by episodes of cessation of breathing or shallow breathing. Around 20 million adult Americans are reported to suffer from this disease and often times it is detected too late by subjecting the individual to an expensive procedure of polysomnography that can be completed only in a fully equipped sleep lab within a medical facility. In this work, we propose a novel solution that assists in detecting the symptoms at an early stage. The idea is to convert the sleeping mattress to a monitoring platform in a nonintrusive manner. The mattress is embedded with sensory devices that reads physiological parameters related to apnea detection and transmit it to a server where residing algorithms analyses the collected data and generate an informed decision of whether the person might be suffering from the apnea sleep disorder. The implemented system is tested on few subjects with promising results.","PeriodicalId":414964,"journal":{"name":"2017 IEEE Conference on Wireless Sensors (ICWiSe)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Wireless Sensors (ICWiSe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWISE.2017.8267159","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 apnea is a sleep disorder characterized mainly by episodes of cessation of breathing or shallow breathing. Around 20 million adult Americans are reported to suffer from this disease and often times it is detected too late by subjecting the individual to an expensive procedure of polysomnography that can be completed only in a fully equipped sleep lab within a medical facility. In this work, we propose a novel solution that assists in detecting the symptoms at an early stage. The idea is to convert the sleeping mattress to a monitoring platform in a nonintrusive manner. The mattress is embedded with sensory devices that reads physiological parameters related to apnea detection and transmit it to a server where residing algorithms analyses the collected data and generate an informed decision of whether the person might be suffering from the apnea sleep disorder. The implemented system is tested on few subjects with promising results.