Daily Stress and Mood Recognition System Using Deep Learning and Fuzzy Clustering for Promoting Better Well-Being

Worawat Lawanot, Masahiro Inoue, Taketoshi Yokemura, Pornchai Mongkolnam, Chakarida Nukoolkit

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

1 Citation (Scopus)

Abstract

Nowadays, the overall well-being is considered to be one of the most important issue. The company has been taking more and more consideration in improving their employees' well-being. The employees also have been taking several approaches to improve their current well-being status. However, the well-being is usually related to the daily activity and behavior, especially in the workplace where it affects stress and mood level. In other words, the quality of a person's well-being is affected by the behavior in a workplace. In this study, we proposed a well-being recognition system where we adopted a deep learning technique to provide a non-invasive monitoring system. We classified the well-being level using three features from two surveys, which covered both stress and mood. For this preliminary study, we trained the model for both generic classification and personalized classification. The personalized approach was taken as a step to provide a personalized health decision support system, which would help raise awareness in users and encourage them to improve their behavior and eventually contribute to a better well-being. We achieved the accuracy of 83% on generic model and 91% on a personalized model.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Consumer Electronics, ICCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679104
DOIs
Publication statusPublished - 2019 Mar 6
Event2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States
Duration: 2019 Jan 112019 Jan 13

Publication series

Name2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference2019 IEEE International Conference on Consumer Electronics, ICCE 2019
CountryUnited States
CityLas Vegas
Period19/1/1119/1/13

Keywords

  • Consumer Health
  • Deep Learning
  • Digital Healthcare
  • Internet of Things
  • Well-Being

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Media Technology
  • Electrical and Electronic Engineering

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  • Cite this

    Lawanot, W., Inoue, M., Yokemura, T., Mongkolnam, P., & Nukoolkit, C. (2019). Daily Stress and Mood Recognition System Using Deep Learning and Fuzzy Clustering for Promoting Better Well-Being. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 [8661932] (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE.2019.8661932