Designing opportune stress intervention delivery timing using multi-modal data

Akane Sano, Paul Johns, Mary Czerwinski

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

23 Scopus citations

Abstract

This paper describes a micro-stress intervention system for information office workers in the workplace, their responses to the interventions and machine learning models to predict the most opportune timing for providing the interventions. We studied 30 office workers for 10 days and examined their work patterns by monitoring their computer and application usage, sleep, activity, heart rate and its variability, as well as the history of micro-stress interventions provided through our desktop software. We analyzed temporal patterns of stress intervention acceptance/rejection and the relationships between their subjective and objective responses to the interventions and perceived work engagement, challenge and stress levels. We then developed machine learning models to predict better stress intervention delivery timing based on this multi-modal data. We found that features from computer and application usage, activity, heart rate variability and stress intervention history showed up to 80.0% accuracy in predicting good or bad intervention timing using a multi-kernel support vector machine algorithm. These findings could help practitioners design the most effective, just-in-time, closed-loop, stress interventions. To our knowledge, this is one of the first papers to review opportune stress interventions' delivery timing research, which could have a big influence in designing stress intervention technologies.

Original languageEnglish (US)
Title of host publication2017 7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages346-353
Number of pages8
ISBN (Electronic)9781538605639
DOIs
StatePublished - Jul 2 2017
Event7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017 - San Antonio, United States
Duration: Oct 23 2017Oct 26 2017

Publication series

Name2017 7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
Volume2018-January

Conference

Conference7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
Country/TerritoryUnited States
CitySan Antonio
Period10/23/1710/26/17

ASJC Scopus subject areas

  • Behavioral Neuroscience
  • Social Psychology
  • Artificial Intelligence
  • Human-Computer Interaction

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