Noninvasive stress recognition considering the current activity. Issue 7 (October 2015)

• Record Type: Journal Article
• Authors: Sysoev, Mikhail; Kos, Andrej; Pogačnik, Matevž
• Is Part Of: Personal and ubiquitous computing. Volume 19:Issue 7(2015)
• Page Start: 1045
• Page End: 1052
• Publication Date: 2015-10
• Subjects: Mobile computing -- Periodicals; Portable computers -- Periodicals; Human-computer interaction -- Periodicals; 004.16
• DOI: 10.1007/s00779-015-0885-5
• Languages: English
• ISSNs: 1617-4909

Abstract

Abstract In this study, we aim to determine the stress level in a non-invasive way to the maximum extent possible by analyzing behavioral and contextual data received from the only source being a smartphone containing the data gathered in real-life situations. The information collected includes audio, gyroscope and accelerometer features, light condition, screen mode (on/off), current stress level self-assessment, and the current activity type. Three stress analysis models have been built: two with the consideration of current activities of a participant and one without those. Classification of low- and high-stress conditions, which was executed for a separate model for a certain kind of activity only, enabled us to achieve 3.9 % higher accuracy than that under the conditions when those activities were neglected. Also, the Android application was developed as a means for the current activity-type identification.