Predicting vasovagal reactions to a virtual blood donation using facial image analysis. Issue 4 (21st February 2022)

• Record Type: Journal Article
• Authors: Rudokaite, Judita; Ong, Lee‐Ling Sharon; Janssen, Mart P.; Postma, Eric; Huis in 't Veld, Elisabeth
• Is Part Of: Transfusion. Volume 62:Issue 4(2022)
• Page Start: 838
• Page End: 847
• Publication Date: 2022-02-21
• Subjects: needle fear -- thermal imaging -- vasovagal reactions; Hematology -- Periodicals; Blood -- Transfusion -- Periodicals; Blood Group Antigens -- Periodicals; Blood Preservation -- Periodicals; Blood Transfusion -- Periodicals; 615
• DOI: 10.1111/trf.16832
• Languages: English
• ISSNs: 0041-1132

Abstract

Abstract: Background: People with needle fear experience not only anxiety and stress but also vasovagal reactions (VVR), including nausea, dizziness, sweating, pallor changes, or even fainting. However, the mechanism behind needle fear and the VVR response are not yet well understood. The aim of our study was to explore whether fluctuations in facial temperature in several facial regions are related to the level of experienced vasovagal reactions, in a simulated blood donation. Study design and methods: We recruited 45 students at Tilburg University and filmed them throughout a virtual blood donation procedure using an Infrared Thermal Imaging (ITI) camera. Participants reported their fear of needles and level of experienced vasovagal reactions. ITI data pre‐processing was completed on each video frame by detecting facial landmarks and image alignment before extracting the mean temperature from the six regions of interest. Results: Temperatures of the chin and left and right cheek areas increased during the virtual blood donation. Mixed‐effects linear regression showed a significant association between self‐reported vasovagal reactions and temperature fluctuations in the area below the nose. Discussion: Our results suggest that the area below the nose may be an interesting target for measuring vasovagal reactions using video imaging techniques. This is the first in a line of studies, which assess whether it is possible to automatically detect levels of fear and vasovagal reactions using facial imaging, from which the development of e‐health solutions and interventions can benefit.