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Wearable Continuous Body Temperature Measurement Using Multiple Artificial Neural Networks
Song CH(宋纯贺); Zeng P(曾鹏); Wang ZF(王忠锋); Zhao H(赵海); Yu HB(于海斌)
Department工业控制网络与系统研究室
Source PublicationIEEE Transactions on Industrial Informatics
ISSN1551-3203
2018
Volume14Issue:10Pages:4395-4406
Indexed BySCI ; EI
EI Accession number20180704785283
WOS IDWOS:000446673500011
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China ; Hundred Talents Program of Shenyang Institute of Automation, Chinese Academy of Sciences
KeywordWearable Computing Continue Body Temperature Measurement Non-invasive Artificial Neural Network
Abstract

Continuous body temperature measurement (CBTM) is of great significance for human health state monitoring. To avoid interfering with users daily activities, CBTM is usually achieved using wearable non-invasive thermometers. Current wearable non-invasive thermometers employ steady-state models used in non-wearable thermometers, as a result, the reaction time is long and the measurement can be disturbed by users activities. However, there is no work to solve these issues. In this paper, first, differences between wearable and non-wearable temperature measurement are analyzed. Second, the relationship among the human body temperature, the skin temperature and the device temperature is modeled based on Artificial Neural Networks (ANNs). Third, this paper proposes a novel multiple ANNs based wearable CBTM method. Experiments show that, the reaction time of the proposed method is about 1/10 of that of other popular wearable non-invasive CBTM methods, meanwhile the accuracy and the robustness are improved.

Language英语
WOS SubjectAutomation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial
WOS KeywordDISEASE
WOS Research AreaAutomation & Control Systems ; Computer Science ; Engineering
Funding ProjectNational Natural Science Foundation of China[61533015] ; National Natural Science Foundation of China[61773368] ; National Natural Science Foundation of China[61773366] ; Hundred Talents Program of Shenyang Institute of Automation, Chinese Academy of Sciences[Y6F8130801]
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/21525
Collection工业控制网络与系统研究室
Corresponding AuthorSong CH(宋纯贺)
Affiliation1.Laboratory of Industrial Control Network and System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning China 110016
2.Northeastern University, 12434 Shenyang China 110004
Recommended Citation
GB/T 7714
Song CH,Zeng P,Wang ZF,et al. Wearable Continuous Body Temperature Measurement Using Multiple Artificial Neural Networks[J]. IEEE Transactions on Industrial Informatics,2018,14(10):4395-4406.
APA Song CH,Zeng P,Wang ZF,Zhao H,&Yu HB.(2018).Wearable Continuous Body Temperature Measurement Using Multiple Artificial Neural Networks.IEEE Transactions on Industrial Informatics,14(10),4395-4406.
MLA Song CH,et al."Wearable Continuous Body Temperature Measurement Using Multiple Artificial Neural Networks".IEEE Transactions on Industrial Informatics 14.10(2018):4395-4406.
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