Abstract
Developing evidence-based parameters to enhance the reliability of face emotion recognition (FER) systems in detecting depression among the elderly is essential. This study aims to elucidate the relationship between the ratio of each emotion valence captured by the FER system and heart rate variability (HRV) while participants watch a video in relation to their depression scores. YOLO, an open-source data analysis toolkit, was used to extract three facial emotion valence features (neutral, positive, and negative) and determine the ratio of each emotion valence over time during video viewing. Additionally, HRV was assessed, and the Geriatric Depression Scale was administered to understand the correlation between FER parameters and depression scores.
| Original language | English |
|---|---|
| Title of host publication | Health. Innovation. Community |
| Subtitle of host publication | It Starts With Us - Papers from the 28th Australian Digital Health and Health Informatics Conference, HIC 2024 |
| Editors | Jen Bichel-Findlay |
| Publisher | IOS Press BV |
| Pages | 194-195 |
| Number of pages | 2 |
| Volume | 318 |
| ISBN (Electronic) | 9781643685410 |
| DOIs | |
| State | Published - 24 09 2024 |
| Event | 28th Australian Digital Health and Health Informatics Conference, HIC 2024 - Brisbane, Australia Duration: 05 08 2024 → 07 08 2024 |
Publication series
| Name | Studies in health technology and informatics |
|---|---|
| ISSN (Print) | 0926-9630 |
Conference
| Conference | 28th Australian Digital Health and Health Informatics Conference, HIC 2024 |
|---|---|
| Country/Territory | Australia |
| City | Brisbane |
| Period | 05/08/24 → 07/08/24 |
Bibliographical note
Publisher Copyright:© 2024 The Authors.
Keywords
- depression
- facial emotion recognition
- FER
- heart rate variability
- HRV
- Depression/diagnosis
- Reproducibility of Results
- Heart Rate/physiology
- Humans
- Facial Expression
- Male
- Emotions
- Aged, 80 and over
- Female
- Aged
- Facial Recognition/physiology