Facial expressions to identify post-stroke: A pilot study

Author(s)

Oliveira, Guilherme C. ; Ngo, Quoc C. ; Passos, Leandro A. ; Oliveira, Leonardo S. ; Papa, Joao P. ; Kumar, Dinesh

• Document type: Journal article
• Source: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE; v. 250, p. 7-pg., 2024-04-30.

Abstract

Background and Objective: Timely stroke treatment can limit brain damage and improve outcomes, which depends on early recognition of the symptoms. However, stroke cases are often missed by the first respondent paramedics. One of the earliest external symptoms of stroke is based on facial expressions. Methods: We propose a computerized analysis of facial expressions using action units to distinguish between Post -Stroke and healthy people. Action units enable analysis of subtle and specific facial movements and are interpretable to the facial expressions. The RGB videos from the Toronto Neuroface Dataset, which were recorded during standard orofacial examinations of 14 people with post -stroke (PS) and 11 healthy controls (HC) were used in this study. Action units were computed using XGBoost which was trained using HC, and classified using regression analysis for each of the nine facial expressions. The analysis was performed without manual intervention. Results: The results were evaluated using leave -one -our validation. The accuracy was 82% for Kiss and Spread, with the best sensitivity of 91% in the differentiation of PS and HC. The features corresponding to mouth muscles were most suitable. Conclusions: This pilot study has shown that our method can detect PS based on two simple facial expressions. However, this needs to be tested in real -world conditions, with people of different ethnicities and smartphone use. The method has the potential for a computerized assessment of the videos for use by the first respondents using a smartphone to perform screening tests, which can facilitate the timely start of the treatment. (AU)

• FAPESP's process: 23/10823-6 - On the Study and Development of Biological Plausible Computational Intelligent Models
• Grantee: Leandro Aparecido Passos Junior
• Support Opportunities: Scholarships in Brazil - Support Program for Fixating Young Doctors
• FAPESP's process: 23/14427-8 - Data Science for Smart Industry (CDII)
• Grantee: José Alberto Cuminato
• Support Opportunities: Research Grants - Research Centers in Engineering Program
• FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
• Grantee: Fabio Gagliardi Cozman
• Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
• FAPESP's process: 23/14197-2 - HIDE - HypomImia DetEction using lightweight architectures
• Grantee: João Paulo Papa
• Support Opportunities: Regular Research Grants
• FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
• Grantee: Francisco Louzada Neto
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC