Abstract
The aim of this work is to develop a real-time system able to classify and passively reduce stress. Heart Rate (HR) and Skin Conductance Response (SCR) are used for stress classification. Entrainment phenomenon is exploited as a possible way to reduce stress via an auditory stimulus. A Support Vector Machine (SVM) produces 84% of stress classification accuracy and a slight effect is obtained for stress reduction.
| Original language | English |
|---|---|
| Title of host publication | 2019 Zooming Innovation in Consumer Technologies Conference, ZINC 2019 |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 9-10 |
| Number of pages | 2 |
| ISBN (Electronic) | 978-1-7281-2901-3 |
| DOIs | |
| Publication status | Published - 1 May 2019 |
| Event | 2019 Zooming Innovation in Consumer Technologies Conference, ZINC 2019 - Novi Sad, Serbia Duration: 29 May 2019 → 30 May 2019 |
Conference
| Conference | 2019 Zooming Innovation in Consumer Technologies Conference, ZINC 2019 |
|---|---|
| Country/Territory | Serbia |
| City | Novi Sad |
| Period | 29/05/19 → 30/05/19 |
Keywords
- Entrainment
- Stress classification
- Stress reduction
- SVM
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