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Poster Abstract: Automated sleep period estimation in wearable multi-sensor systems

  • Yuezhou Zhang
  • , Zhicheng Yang
  • , Zhengbo Zhang
  • , Xiaoli Liu
  • , Desen Cao
  • , Peiyao Li
  • , Jiewen Zheng
  • , Ke Lan
  • Beijing Health Regulation Technology
  • University of California at Davis
  • General Hospital of People's Liberation Army

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Sleep period determination is essential to accurate sleep quality analysis. In this paper, we propose an automated algorithm for wearable multi-sensor systems to precisely estimate the sleep period. It leverages the information of accelerometer, and vital signs such as heart rate and breathing rate. Compared to the sleep periods determined by the clinical diagnosing-grade equipment, our algorithm achieves average time differences of 9.0 and 10.4 minutes for healthy subjects and clinical patients, respectively.

Original languageEnglish
Title of host publicationSenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery, Inc
Pages305-306
Number of pages2
ISBN (Electronic)9781450359528
DOIs
StatePublished - 4 Nov 2018
Event16th ACM Conference on Embedded Networked Sensor Systems, SENSYS 2018 - Shenzhen, China
Duration: 4 Nov 20187 Nov 2018

Publication series

NameSenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems

Conference

Conference16th ACM Conference on Embedded Networked Sensor Systems, SENSYS 2018
Country/TerritoryChina
CityShenzhen
Period4/11/187/11/18

Keywords

  • Algorithm
  • Healthcare
  • Sleep periods
  • Wearable sensors

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