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Automated analysis of facial emotions in subjects with cognitive impairment
Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782312/ https://www.ncbi.nlm.nih.gov/pubmed/35061824 http://dx.doi.org/10.1371/journal.pone.0262527 |
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author | Jiang, Zifan Seyedi, Salman Haque, Rafi U. Pongos, Alvince L. Vickers, Kayci L. Manzanares, Cecelia M. Lah, James J. Levey, Allan I. Clifford, Gari D. |
author_facet | Jiang, Zifan Seyedi, Salman Haque, Rafi U. Pongos, Alvince L. Vickers, Kayci L. Manzanares, Cecelia M. Lah, James J. Levey, Allan I. Clifford, Gari D. |
author_sort | Jiang, Zifan |
collection | PubMed |
description | Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer vision-based deep learning model for facial emotion recognition trained on 400.000 faces was utilized to analyze facial emotions expressed during a passive viewing memory test. In addition, this study was conducted on a large number of individuals (n = 493), including healthy controls and individuals with cognitive impairment due to diverse underlying etiologies and across different disease stages. Diagnoses included subjective cognitive impairment, Mild Cognitive Impairment (MCI) due to AD, MCI due to other etiologies, dementia due to Alzheimer’s diseases (AD), and dementia due to other etiologies (e.g., Vascular Dementia, Frontotemporal Dementia, Lewy Body Dementia, etc.). The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance across all participants. A participant with a score of less than or equal to 24 was considered cognitively impaired (CI). Compared to cognitively unimpaired (CU) participants, CI participants expressed significantly less positive emotions, more negative emotions, and higher facial expressiveness during the test. In addition, classification analysis revealed that facial emotions expressed during the test allowed effective differentiation of CI from CU participants, largely independent of sex, race, age, education level, mood, and eye movements (derived from an eye-tracking-based digital biomarker for cognitive impairment). No screening methods reliably differentiated the underlying etiology of the cognitive impairment. The findings provide quantitative and comprehensive evidence that the expression of facial emotions is significantly different in people with cognitive impairment, and suggests this may be a useful tool for passive screening of cognitive impairment. |
format | Online Article Text |
id | pubmed-8782312 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87823122022-01-22 Automated analysis of facial emotions in subjects with cognitive impairment Jiang, Zifan Seyedi, Salman Haque, Rafi U. Pongos, Alvince L. Vickers, Kayci L. Manzanares, Cecelia M. Lah, James J. Levey, Allan I. Clifford, Gari D. PLoS One Research Article Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer vision-based deep learning model for facial emotion recognition trained on 400.000 faces was utilized to analyze facial emotions expressed during a passive viewing memory test. In addition, this study was conducted on a large number of individuals (n = 493), including healthy controls and individuals with cognitive impairment due to diverse underlying etiologies and across different disease stages. Diagnoses included subjective cognitive impairment, Mild Cognitive Impairment (MCI) due to AD, MCI due to other etiologies, dementia due to Alzheimer’s diseases (AD), and dementia due to other etiologies (e.g., Vascular Dementia, Frontotemporal Dementia, Lewy Body Dementia, etc.). The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance across all participants. A participant with a score of less than or equal to 24 was considered cognitively impaired (CI). Compared to cognitively unimpaired (CU) participants, CI participants expressed significantly less positive emotions, more negative emotions, and higher facial expressiveness during the test. In addition, classification analysis revealed that facial emotions expressed during the test allowed effective differentiation of CI from CU participants, largely independent of sex, race, age, education level, mood, and eye movements (derived from an eye-tracking-based digital biomarker for cognitive impairment). No screening methods reliably differentiated the underlying etiology of the cognitive impairment. The findings provide quantitative and comprehensive evidence that the expression of facial emotions is significantly different in people with cognitive impairment, and suggests this may be a useful tool for passive screening of cognitive impairment. Public Library of Science 2022-01-21 /pmc/articles/PMC8782312/ /pubmed/35061824 http://dx.doi.org/10.1371/journal.pone.0262527 Text en © 2022 Jiang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Jiang, Zifan Seyedi, Salman Haque, Rafi U. Pongos, Alvince L. Vickers, Kayci L. Manzanares, Cecelia M. Lah, James J. Levey, Allan I. Clifford, Gari D. Automated analysis of facial emotions in subjects with cognitive impairment |
title | Automated analysis of facial emotions in subjects with cognitive impairment |
title_full | Automated analysis of facial emotions in subjects with cognitive impairment |
title_fullStr | Automated analysis of facial emotions in subjects with cognitive impairment |
title_full_unstemmed | Automated analysis of facial emotions in subjects with cognitive impairment |
title_short | Automated analysis of facial emotions in subjects with cognitive impairment |
title_sort | automated analysis of facial emotions in subjects with cognitive impairment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782312/ https://www.ncbi.nlm.nih.gov/pubmed/35061824 http://dx.doi.org/10.1371/journal.pone.0262527 |
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