Jinyang Li, Yongpan Liu, Hehe Li, Rui Hua, C. Xue, H. Lee, Huazhong Yang
{"title":"Accurate personal ultraviolet dose estimation with multiple wearable sensors","authors":"Jinyang Li, Yongpan Liu, Hehe Li, Rui Hua, C. Xue, H. Lee, Huazhong Yang","doi":"10.1109/BSN.2016.7516286","DOIUrl":null,"url":null,"abstract":"Wearable devices begin to integrate into the daily lives along with recent technology development. One of such important applications is to accurately monitor ultraviolet (UV) radiation received by the human body. To compensate for the localized monitoring area of existing personal UV monitoring devices, this paper proposes a reconstruction method to estimate the UV dose over the entire body based on multiple discrete wearable UV sensor nodes. Ambient factors and individual factors are both considered in this paper. The proposed estimation method is validated by a range of UV data collection experiments in realistic scenarios. Experimental results show that the proposed method reduces 68.3% estimation errors on average compared with existing single sensor based methods.","PeriodicalId":205735,"journal":{"name":"2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BSN.2016.7516286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Wearable devices begin to integrate into the daily lives along with recent technology development. One of such important applications is to accurately monitor ultraviolet (UV) radiation received by the human body. To compensate for the localized monitoring area of existing personal UV monitoring devices, this paper proposes a reconstruction method to estimate the UV dose over the entire body based on multiple discrete wearable UV sensor nodes. Ambient factors and individual factors are both considered in this paper. The proposed estimation method is validated by a range of UV data collection experiments in realistic scenarios. Experimental results show that the proposed method reduces 68.3% estimation errors on average compared with existing single sensor based methods.