Abstract
There are physiological, hormonal and psychological markers that occur early in a procedure involving needles. These so-called vasovagal reactions range from feeling nauseous, dizzy, to completely passing out. In an early stage, they are difficult to measure and self-report before it is too late to prevent them. This study aims to explore different features from regular video and thermal facial video recordings of blood donors in the waiting room, prior to a blood donation procedure, in order to assess to what extent it is possible to predict whether a donor will experience a low or high level of vasovagal reaction later on during the blood donation. The results showed that the best performance was achieved using pre-trained ResNet152 models with GRU on a continuous video stream, achieving an F1 of 0.69, a PR-AUC score of 0.81, and an MCC score of 0.56. This model also achieved a precision of 0.52, recall of 0.94, F1 score of 0.67, and MCC score of 0.42 on new, previously unseen mobile video data. Although the model requires further improvement, it outperforms self-reported vasovagal reaction scores and shows the potential to predict who is at risk of experiencing vasovagal reactions using facial video data.
Original language | English |
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Title of host publication | 2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition, FG 2024 |
Publisher | IEEE |
Number of pages | 10 |
ISBN (Electronic) | 9798350394948 |
DOIs | |
Publication status | Published - 11 Jul 2024 |
Event | 18th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2024 - Istanbul, Turkey Duration: 27 May 2024 → 31 May 2024 |
Publication series
Name | 2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition, FG 2024 |
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Conference
Conference | 18th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2024 |
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Country/Territory | Turkey |
City | Istanbul |
Period | 27/05/24 → 31/05/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.