Daily stress recognition system using activity tracker and smartphone based on physical activity and heart rate data

Worawat Lawanont, Pornchai Mongkolnam, Chakarida Nukoolkit, Masahiro Inoue

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

3 Citations (Scopus)

Abstract

Everyday, people experience stress, and it has been suggested for a long time that stress will eventually develop into anxiety as well as other physical issues. The emerging technology, such as wearable sensors and smartphone, have enabled the opportunity of using the technology to help solve the issue. In this paper, we proposed a system using Internet of Things architecture where we adopted an activity tracker as our sensing device to reduce cumbersome for daily use. Among the total of 17 features extracted from activity tracker, five features from sleep data and six features from heart rate data were proposed to develop the stress recognition model. In the evaluation of our system, we achieved the accuracy as high as 81.70% on the cross validation and 78.95% when tested on the test set. Despite that this is a preliminary result, it has shown that it is possible to use the IoT architecture along with the activity tracker to accurately recognize stress and help improve one’s wellbeing.

Original languageEnglish
Title of host publicationIntelligent Decision Technologies 2018 - Proceedings of the 10th KES International Conference on Intelligent Decision Technologies KES-IDT 2018
EditorsLakhmi C. Jain, Ireneusz Czarnowski, Robert J. Howlett, Ljubo Vlacic
PublisherSpringer Science and Business Media Deutschland GmbH
Pages11-21
Number of pages11
ISBN (Print)9783319920276
DOIs
Publication statusPublished - 2019 Jan 1
Event10th International KES Conference on Intelligent Decision Technologies, KES-IDT 2018 - Gold Coast, Australia
Duration: 2018 Jun 202018 Jun 22

Publication series

NameSmart Innovation, Systems and Technologies
Volume97
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Other

Other10th International KES Conference on Intelligent Decision Technologies, KES-IDT 2018
CountryAustralia
CityGold Coast
Period18/6/2018/6/22

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Keywords

  • Activity tracker
  • Digital healthcare
  • Internet of Things
  • Stress recognition
  • Wearable sensor

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

Cite this

Lawanont, W., Mongkolnam, P., Nukoolkit, C., & Inoue, M. (2019). Daily stress recognition system using activity tracker and smartphone based on physical activity and heart rate data. In L. C. Jain, I. Czarnowski, R. J. Howlett, & L. Vlacic (Eds.), Intelligent Decision Technologies 2018 - Proceedings of the 10th KES International Conference on Intelligent Decision Technologies KES-IDT 2018 (pp. 11-21). (Smart Innovation, Systems and Technologies; Vol. 97). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-92028-3_2