EconPapers    
Economics at your fingertips  
 

Differentiating Use of Facial Expression between Individuals with and without Traumatic Brain Injury Using Affectiva Software: A Pilot Study

Kelly Yiew, Leanne Togher, Emma Power, Melissa Brunner and Rachael Rietdijk ()
Additional contact information
Kelly Yiew: Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
Leanne Togher: Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
Emma Power: Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia
Melissa Brunner: Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
Rachael Rietdijk: Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia

IJERPH, 2023, vol. 20, issue 2, 1-27

Abstract: This study investigated the feasibility of using an automated facial coding engine, Affectiva (integrated in iMotions, version 8.2), for evaluating facial expression after traumatic brain injury (TBI). An observational cross-sectional study was conducted based on facial expression data from videos of participants with TBI and control participants. The aims were to compare TBI and control groups, and identify confounding factors affecting the data analysis. Video samples of two narrative tasks (personal event and story retell) from ten participants with severe TBI and ten control participants without TBI were analyzed using Affectiva. Automated data on participants’ engagement, smile and brow furrow were compared statistically between and within groups. Qualitative notes for each sample were also recorded. Affectiva detected a higher percentage of time of engagement for TBI participants than for control participants on both tasks. There was also a higher percentage of time of smiling for TBI participants in one task. Within groups, there were no significant differences between the two narrative tasks. Affectiva provides standardized data about facial expression and may be sensitive to detecting change in the use of facial expression after TBI. This study also identified factors to avoid during videorecording to ensure high quality samples for future research.

Keywords: traumatic brain injury; software; facial expression; assessment tool; social communication (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/20/2/1169/pdf (application/pdf)
https://www.mdpi.com/1660-4601/20/2/1169/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:20:y:2023:i:2:p:1169-:d:1029782

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1169-:d:1029782