Analysis of facial expressions in parkinson's disease through video-based automatic methods
•Objectify facial hypomimia in Parkinson’s disease through video analysis.•Basic facial expressions of Patients and healthy subjects were investigated.•The distance from a neutral baseline was computed to quantify expression changes.•Parkinsonian patients reported on average lower amounts of facial...
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Veröffentlicht in: | Journal of neuroscience methods 2017-04, Vol.281, p.7-20 |
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container_title | Journal of neuroscience methods |
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creator | Bandini, Andrea Orlandi, Silvia Escalante, Hugo Jair Giovannelli, Fabio Cincotta, Massimo Reyes-Garcia, Carlos A. Vanni, Paola Zaccara, Gaetano Manfredi, Claudia |
description | •Objectify facial hypomimia in Parkinson’s disease through video analysis.•Basic facial expressions of Patients and healthy subjects were investigated.•The distance from a neutral baseline was computed to quantify expression changes.•Parkinsonian patients reported on average lower amounts of facial mimicry.•We demonstrated that contactless methods are suitable for objectifying hypomimia.
The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson’s disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia.
In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based
17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions.
Results show that control subjects reported on average higher distances than PD patients along the tasks.
This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients.
Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform. |
doi_str_mv | 10.1016/j.jneumeth.2017.02.006 |
format | Article |
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The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson’s disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia.
In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based
17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions.
Results show that control subjects reported on average higher distances than PD patients along the tasks.
This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients.
Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform.</description><identifier>ISSN: 0165-0270</identifier><identifier>EISSN: 1872-678X</identifier><identifier>DOI: 10.1016/j.jneumeth.2017.02.006</identifier><identifier>PMID: 28223023</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Aged ; Aged, 80 and over ; Automatic facial expression recognition ; Contactless ; Emotions ; Facial Expression ; Facial mimicry ; Female ; Humans ; Hypomimia ; Image Interpretation, Computer-Assisted - methods ; Imitative Behavior ; Male ; Middle Aged ; Parkinson Disease - classification ; Parkinson Disease - diagnosis ; Parkinson Disease - physiopathology ; Parkinson's disease ; Support Vector Machine ; Video Recording - methods ; Video-based</subject><ispartof>Journal of neuroscience methods, 2017-04, Vol.281, p.7-20</ispartof><rights>2017 Elsevier B.V.</rights><rights>Copyright © 2017 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c434t-352a2a64dffcdccac6a37f2cd189094413bdfe150e8e0d1bca2678dd2a6baefc3</citedby><cites>FETCH-LOGICAL-c434t-352a2a64dffcdccac6a37f2cd189094413bdfe150e8e0d1bca2678dd2a6baefc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jneumeth.2017.02.006$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28223023$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bandini, Andrea</creatorcontrib><creatorcontrib>Orlandi, Silvia</creatorcontrib><creatorcontrib>Escalante, Hugo Jair</creatorcontrib><creatorcontrib>Giovannelli, Fabio</creatorcontrib><creatorcontrib>Cincotta, Massimo</creatorcontrib><creatorcontrib>Reyes-Garcia, Carlos A.</creatorcontrib><creatorcontrib>Vanni, Paola</creatorcontrib><creatorcontrib>Zaccara, Gaetano</creatorcontrib><creatorcontrib>Manfredi, Claudia</creatorcontrib><title>Analysis of facial expressions in parkinson's disease through video-based automatic methods</title><title>Journal of neuroscience methods</title><addtitle>J Neurosci Methods</addtitle><description>•Objectify facial hypomimia in Parkinson’s disease through video analysis.•Basic facial expressions of Patients and healthy subjects were investigated.•The distance from a neutral baseline was computed to quantify expression changes.•Parkinsonian patients reported on average lower amounts of facial mimicry.•We demonstrated that contactless methods are suitable for objectifying hypomimia.
The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson’s disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia.
In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based
17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions.
Results show that control subjects reported on average higher distances than PD patients along the tasks.
This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients.
Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Automatic facial expression recognition</subject><subject>Contactless</subject><subject>Emotions</subject><subject>Facial Expression</subject><subject>Facial mimicry</subject><subject>Female</subject><subject>Humans</subject><subject>Hypomimia</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Imitative Behavior</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Parkinson Disease - classification</subject><subject>Parkinson Disease - diagnosis</subject><subject>Parkinson Disease - physiopathology</subject><subject>Parkinson's disease</subject><subject>Support Vector Machine</subject><subject>Video Recording - methods</subject><subject>Video-based</subject><issn>0165-0270</issn><issn>1872-678X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1P3DAQhi1EBVvav4B8g0vSsZN1khsIFVoJqZciIXGwHHvc9TaJt54ElX-PVwu99jTS6Hnn42HsXEApQKgv23I74TLivCkliKYEWQKoI7YSbSML1bSPx2yVwXUBsoFT9pFoCwB1B-qEncpWygpktWJP15MZXigQj557Y4MZOP7dJSQKcSIeJr4z6XeYKE4XxF0gNIR83qS4_Nrw5-AwFn1uOW6WOY5mDpbvz4qOPrEP3gyEn9_qGXu4_frz5ltx_-Pu-831fWHrqp6Lai2NNKp23ltnrbHKVI2X1om2g66uRdU7j2IN2CI40Vsj83_O5Uxv0NvqjF0e5u5S_LMgzXoMZHEYzIRxIZ2VQNcq0amMqgNqUyRK6PUuhdGkFy1A78XqrX4Xq_diNUidxebg-duOpR_R_Yu9m8zA1QHA_OlzwKTJBpwsupDQztrF8L8dr2uNkDg</recordid><startdate>20170401</startdate><enddate>20170401</enddate><creator>Bandini, Andrea</creator><creator>Orlandi, Silvia</creator><creator>Escalante, Hugo Jair</creator><creator>Giovannelli, Fabio</creator><creator>Cincotta, Massimo</creator><creator>Reyes-Garcia, Carlos A.</creator><creator>Vanni, Paola</creator><creator>Zaccara, Gaetano</creator><creator>Manfredi, Claudia</creator><general>Elsevier B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20170401</creationdate><title>Analysis of facial expressions in parkinson's disease through video-based automatic methods</title><author>Bandini, Andrea ; Orlandi, Silvia ; Escalante, Hugo Jair ; Giovannelli, Fabio ; Cincotta, Massimo ; Reyes-Garcia, Carlos A. ; Vanni, Paola ; Zaccara, Gaetano ; Manfredi, Claudia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c434t-352a2a64dffcdccac6a37f2cd189094413bdfe150e8e0d1bca2678dd2a6baefc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Automatic facial expression recognition</topic><topic>Contactless</topic><topic>Emotions</topic><topic>Facial Expression</topic><topic>Facial mimicry</topic><topic>Female</topic><topic>Humans</topic><topic>Hypomimia</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Imitative Behavior</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Parkinson Disease - classification</topic><topic>Parkinson Disease - diagnosis</topic><topic>Parkinson Disease - physiopathology</topic><topic>Parkinson's disease</topic><topic>Support Vector Machine</topic><topic>Video Recording - methods</topic><topic>Video-based</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bandini, Andrea</creatorcontrib><creatorcontrib>Orlandi, Silvia</creatorcontrib><creatorcontrib>Escalante, Hugo Jair</creatorcontrib><creatorcontrib>Giovannelli, Fabio</creatorcontrib><creatorcontrib>Cincotta, Massimo</creatorcontrib><creatorcontrib>Reyes-Garcia, Carlos A.</creatorcontrib><creatorcontrib>Vanni, Paola</creatorcontrib><creatorcontrib>Zaccara, Gaetano</creatorcontrib><creatorcontrib>Manfredi, Claudia</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of neuroscience methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bandini, Andrea</au><au>Orlandi, Silvia</au><au>Escalante, Hugo Jair</au><au>Giovannelli, Fabio</au><au>Cincotta, Massimo</au><au>Reyes-Garcia, Carlos A.</au><au>Vanni, Paola</au><au>Zaccara, Gaetano</au><au>Manfredi, Claudia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analysis of facial expressions in parkinson's disease through video-based automatic methods</atitle><jtitle>Journal of neuroscience methods</jtitle><addtitle>J Neurosci Methods</addtitle><date>2017-04-01</date><risdate>2017</risdate><volume>281</volume><spage>7</spage><epage>20</epage><pages>7-20</pages><issn>0165-0270</issn><eissn>1872-678X</eissn><abstract>•Objectify facial hypomimia in Parkinson’s disease through video analysis.•Basic facial expressions of Patients and healthy subjects were investigated.•The distance from a neutral baseline was computed to quantify expression changes.•Parkinsonian patients reported on average lower amounts of facial mimicry.•We demonstrated that contactless methods are suitable for objectifying hypomimia.
The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson’s disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia.
In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based
17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions.
Results show that control subjects reported on average higher distances than PD patients along the tasks.
This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients.
Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>28223023</pmid><doi>10.1016/j.jneumeth.2017.02.006</doi><tpages>14</tpages></addata></record> |
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subjects | Aged Aged, 80 and over Automatic facial expression recognition Contactless Emotions Facial Expression Facial mimicry Female Humans Hypomimia Image Interpretation, Computer-Assisted - methods Imitative Behavior Male Middle Aged Parkinson Disease - classification Parkinson Disease - diagnosis Parkinson Disease - physiopathology Parkinson's disease Support Vector Machine Video Recording - methods Video-based |
title | Analysis of facial expressions in parkinson's disease through video-based automatic methods |
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