{"title":"基于支持向量机和多传感器的睡眠跟踪智能可穿戴系统设计","authors":"M. Abo-Zahhad","doi":"10.21608/jesaun.2023.205964.1220","DOIUrl":null,"url":null,"abstract":"- Healthcare has been considered one of the main issues to be spotted and improved in a high manner. Thus, many technology trends are customized to be used in the development of the field of healthcare. One of the fields that highly affects health is sleeping, therefore, the importance of developing a portable and cost-affordable sleep-tracking system has arisen. Getting enough good-quality sleep is essential for living a healthy life. This could be done by monitoring vital signals that affect the quality of sleep such as heart rate, blood oxygen saturation, and positioning. Furthermore, these parameters could be used to detect sleep stages. Detecting sleep stages provides the ability to specify sleep quality and how to get better sleep hygiene. In this paper, a sleep quality monitoring system using commercial off-the-shelf sensors has been developed. The main aims are to make the system cheap, besides being portable, lightweight, and easy to use with better sleep quality and sleep stages accuracies compared to recently published systems. Based on the personalized data collected, the system could identify the sleep onset latency, the wake after sleep onset, the total sleep time, and the pattern based on the step before. Then, users would know about their quality of sleep and sleeping habits, which will be directly reflected in their health and well-being. The obtained results indicate that sleep quality accuracy is 97.5% and sleep stages accuracy is 67.5% which are better than similar systems used with Commercial off the Shelf sensors.","PeriodicalId":166670,"journal":{"name":"JES. Journal of Engineering Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of Smart Wearable System for Sleep Tracking Using SVM and Multi-Sensor Approach\",\"authors\":\"M. Abo-Zahhad\",\"doi\":\"10.21608/jesaun.2023.205964.1220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"- Healthcare has been considered one of the main issues to be spotted and improved in a high manner. Thus, many technology trends are customized to be used in the development of the field of healthcare. One of the fields that highly affects health is sleeping, therefore, the importance of developing a portable and cost-affordable sleep-tracking system has arisen. Getting enough good-quality sleep is essential for living a healthy life. This could be done by monitoring vital signals that affect the quality of sleep such as heart rate, blood oxygen saturation, and positioning. Furthermore, these parameters could be used to detect sleep stages. Detecting sleep stages provides the ability to specify sleep quality and how to get better sleep hygiene. In this paper, a sleep quality monitoring system using commercial off-the-shelf sensors has been developed. The main aims are to make the system cheap, besides being portable, lightweight, and easy to use with better sleep quality and sleep stages accuracies compared to recently published systems. Based on the personalized data collected, the system could identify the sleep onset latency, the wake after sleep onset, the total sleep time, and the pattern based on the step before. Then, users would know about their quality of sleep and sleeping habits, which will be directly reflected in their health and well-being. The obtained results indicate that sleep quality accuracy is 97.5% and sleep stages accuracy is 67.5% which are better than similar systems used with Commercial off the Shelf sensors.\",\"PeriodicalId\":166670,\"journal\":{\"name\":\"JES. Journal of Engineering Sciences\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JES. Journal of Engineering Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21608/jesaun.2023.205964.1220\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JES. Journal of Engineering Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21608/jesaun.2023.205964.1220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of Smart Wearable System for Sleep Tracking Using SVM and Multi-Sensor Approach
- Healthcare has been considered one of the main issues to be spotted and improved in a high manner. Thus, many technology trends are customized to be used in the development of the field of healthcare. One of the fields that highly affects health is sleeping, therefore, the importance of developing a portable and cost-affordable sleep-tracking system has arisen. Getting enough good-quality sleep is essential for living a healthy life. This could be done by monitoring vital signals that affect the quality of sleep such as heart rate, blood oxygen saturation, and positioning. Furthermore, these parameters could be used to detect sleep stages. Detecting sleep stages provides the ability to specify sleep quality and how to get better sleep hygiene. In this paper, a sleep quality monitoring system using commercial off-the-shelf sensors has been developed. The main aims are to make the system cheap, besides being portable, lightweight, and easy to use with better sleep quality and sleep stages accuracies compared to recently published systems. Based on the personalized data collected, the system could identify the sleep onset latency, the wake after sleep onset, the total sleep time, and the pattern based on the step before. Then, users would know about their quality of sleep and sleeping habits, which will be directly reflected in their health and well-being. The obtained results indicate that sleep quality accuracy is 97.5% and sleep stages accuracy is 67.5% which are better than similar systems used with Commercial off the Shelf sensors.