Automated vs. manual pain coding and heart rate estimations based on videos of older adults with and without dementia
| Autor: | Thomas Hadjistavropoulos, Louise I R Castillo, Kenneth M. Prkachin, M. Erin Browne, Rafik Goubran |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
business.industry Computer science 0206 medical engineering 02 engineering and technology medicine.disease 020601 biomedical engineering behavioral observation 03 medical and health sciences 0302 clinical medicine Software Physical medicine and rehabilitation Elderly Facial analysis Heart rate medicine physiological measurement Dementia Original Article business Alzheimer’s disease 030217 neurology & neurosurgery Coding (social sciences) |
| Zdroj: | Journal of Rehabilitation and Assistive Technologies Engineering |
| ISSN: | 2055-6683 |
| Popis: | Introduction Technological advances have allowed for the estimation of physiological indicators from video data. FaceReader™ is an automated facial analysis software that has been used widely in studies of facial expressions of emotion and was recently updated to allow for the estimation of heart rate (HR) using remote photoplethysmography (rPPG). We investigated FaceReader™-based heart rate and pain expression estimations in older adults in relation to manual coding by experts. Methods Using a video dataset of older adult patients with and without dementia, we assessed the relationship between FaceReader’s™ HR estimations against a well-established Video Magnification (VM) algorithm during baseline and pain conditions. Furthermore, we examined the correspondence between the Facial Action Coding System (FACS)-based pain scores obtained through FaceReader™ and manual coding. Results FaceReader’s™ HR estimations were correlated with VM algorithm in baseline and pain conditions. Non-verbal FaceReader™ pain scores and manual coding were also highly correlated despite discrepancies between the FaceReader™ and manual coding in the absolute value of scores based on pain-related facial action coding of the events preceding and following the pain response. Conclusions Compared to expert manual FACS coding and optimized VM algorithm, FaceReader™ showed good results in estimating HR values and non-verbal pain scores. |
| Databáze: | OpenAIRE |
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