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Quantitative Evaluation of Hypomimia in Parkinson's Disease: A Face Tracking Approach.

Pegolo, E; Volpe, D; Cucca, A; Ricciardi, L; Sawacha, Z (2022) Quantitative Evaluation of Hypomimia in Parkinson's Disease: A Face Tracking Approach. Sensors (Basel), 22 (4). p. 1358. ISSN 1424-8220 https://doi.org/10.3390/s22041358
SGUL Authors: Ricciardi, Lucia

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Abstract

Parkinson's disease (PD) is a neurological disorder that mainly affects the motor system. Among other symptoms, hypomimia is considered one of the clinical hallmarks of the disease. Despite its great impact on patients' quality of life, it remains still under-investigated. The aim of this work is to provide a quantitative index for hypomimia that can distinguish pathological and healthy subjects and that can be used in the classification of emotions. A face tracking algorithm was implemented based on the Facial Action Coding System. A new easy-to-interpret metric (face mobility index, FMI) was defined considering distances between pairs of geometric features and a classification based on this metric was proposed. Comparison was also provided between healthy controls and PD patients. Results of the study suggest that this index can quantify the degree of impairment in PD and can be used in the classification of emotions. Statistically significant differences were observed for all emotions when distances were taken into account, and for happiness and anger when FMI was considered. The best classification results were obtained with Random Forest and kNN according to the AUC metric.

Item Type: Article
Additional Information: Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: Facial Action Coding System, Parkinson’s disease, classification, emotions, face, facial expression, feature tracking, hypomimia, Emotions, Face, Facial Expression, Humans, Parkinson Disease, Quality of Life, Face, Humans, Parkinson Disease, Facial Expression, Emotions, Quality of Life, Parkinson's disease, facial expression, Facial Action Coding System, feature tracking, emotions, classification, face, hypomimia, 0301 Analytical Chemistry, 0906 Electrical and Electronic Engineering, Analytical Chemistry
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Sensors (Basel)
ISSN: 1424-8220
Language: eng
Dates:
DateEvent
10 February 2022Published
6 February 2022Accepted
Publisher License: Creative Commons: Attribution 4.0
PubMed ID: 35214255
Web of Science ID: WOS:000769505300001
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/114266
Publisher's version: https://doi.org/10.3390/s22041358

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