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Pain Expressions in Dementia: Validity of Observers’ Pain Judgments as a Function of Angle of Observation

Facial expressions of pain are important in assessing individuals with dementia and severe communicative limitations. Though frontal views of the face are assumed to allow for the most valid and reliable observational assessments, the impact of viewing angle is unknown. We video-recorded older adult...

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Detalles Bibliográficos
Autores principales: Erin Browne, M., Hadjistavropoulos, Thomas, Prkachin, Kenneth, Ashraf, Ahmed, Taati, Babak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656786/
https://www.ncbi.nlm.nih.gov/pubmed/31404130
http://dx.doi.org/10.1007/s10919-019-00303-4
Descripción
Sumario:Facial expressions of pain are important in assessing individuals with dementia and severe communicative limitations. Though frontal views of the face are assumed to allow for the most valid and reliable observational assessments, the impact of viewing angle is unknown. We video-recorded older adults with and without dementia using cameras capturing different observational angles (e.g., front vs. profile view) both during a physiotherapy examination designed to identify painful areas and during a baseline period. Facial responses were coded using the fine-grained Facial Action Coding System, as well as a systematic clinical observation method. Coding was conducted separately for panoramic (incorporating left, right, and front views), and a profile view of the face. Untrained observers also judged the videos in a laboratory setting. Trained coder reliability was satisfactory for both the profile and panoramic view. Untrained observer judgments from a profile view were substantially more accurate compared to the front view and accounted for more variance in differentiating non-painful from painful situations. The findings add specificity to the communications models of pain (clarifying factors influencing observers’ ability to decode pain messages). Perhaps more importantly, the findings have implications for the development of computer vision algorithms and vision technologies designed to monitor and interpret facial expressions in a pain context. That is, the performance of such automated systems is heavily influenced by how reliably these human annotations could be provided and, hence, evaluation of human observers’ reliability, from multiple angles of observation, has implications for machine learning development efforts.