ActDetector: Detecting Daily Activities Using Smartwatches

Xiao Sun, Li Qiu, Yibo Wu, Guohong Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Detecting daily activities is helpful for health care and clinical medicine. In this paper, we present ActDetector, a smartwatch based application which detects 8 common daily activities, including sitting, walking, running, going upstairs, going downstairs, eating, driving and sitting in a vehicle. By leveraging the built-in sensors on smartwatch, a multi-level classification system is proposed which considers both detection accuracy and energy efficiency. ActDetector is designed to work unobtrusively, no matter on which wrist the smartwatch is worn. We have implemented ActDetector on Sony Smartwatch 3 and evaluated its performance in real experiments involving 12 users. Experimental results show that ActDetector is energy efficient and can detect the daily activities with high accuracy.

Original languageEnglish (US)
Title of host publicationProceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-9
Number of pages9
ISBN (Electronic)9781538623237
DOIs
StatePublished - Nov 14 2017
Event14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017 - Orlando, United States
Duration: Oct 22 2017Oct 25 2017

Publication series

NameProceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017

Other

Other14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
Country/TerritoryUnited States
CityOrlando
Period10/22/1710/25/17

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Instrumentation
  • Electrical and Electronic Engineering

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