The spectrum of facial palsy: The MEEI facial palsy photo and video standard set
Objectives Facial palsy causes variable facial disfigurement ranging from subtle asymmetry to crippling deformity. There is no existing standard database to serve as a resource for facial palsy education and research. We present a standardized set of facial photographs and videos representing the en...
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| Veröffentlicht in: | The Laryngoscope 2020-01, Vol.130 (1), p.32-37 |
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| container_title | The Laryngoscope |
| container_volume | 130 |
| creator | Greene, Jacqueline J. Guarin, Diego L. Tavares, Joana Fortier, Emily Robinson, Mara Dusseldorp, Joseph Quatela, Olivia Jowett, Nate Hadlock, Tessa |
| description | Objectives
Facial palsy causes variable facial disfigurement ranging from subtle asymmetry to crippling deformity. There is no existing standard database to serve as a resource for facial palsy education and research. We present a standardized set of facial photographs and videos representing the entire spectrum of flaccid and nonflaccid (aberrantly regenerated or synkinetic) facial palsy. To demonstrate the utility of the dataset, we describe the relationship between level of facial function and perceived emotion expression as determined by an automated emotion detection, machine learning‐based algorithm.
Methods
Photographs and videos of patients with both flaccid and nonflaccid facial palsy were prospectively gathered. The degree of facial palsy was quantified using eFACE, House‐Brackmann, and Sunnybrook scales. Perceived emotion during a standard video of facial movements was determined using an automated, machine learning algorithm.
Results
Sixty participants were enrolled and categorized by eFACE score across the range of facial function. Patients with complete flaccid facial palsy (eFACE |
| doi_str_mv | 10.1002/lary.27986 |
| format | Article |
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Facial palsy causes variable facial disfigurement ranging from subtle asymmetry to crippling deformity. There is no existing standard database to serve as a resource for facial palsy education and research. We present a standardized set of facial photographs and videos representing the entire spectrum of flaccid and nonflaccid (aberrantly regenerated or synkinetic) facial palsy. To demonstrate the utility of the dataset, we describe the relationship between level of facial function and perceived emotion expression as determined by an automated emotion detection, machine learning‐based algorithm.
Methods
Photographs and videos of patients with both flaccid and nonflaccid facial palsy were prospectively gathered. The degree of facial palsy was quantified using eFACE, House‐Brackmann, and Sunnybrook scales. Perceived emotion during a standard video of facial movements was determined using an automated, machine learning algorithm.
Results
Sixty participants were enrolled and categorized by eFACE score across the range of facial function. Patients with complete flaccid facial palsy (eFACE <60) had a significant loss of perceived joy compared to the nonflaccid and normal groups. Additionally, patients with only moderate flaccid and nonflaccid facial palsy had a significant increase in perceived negative emotion (contempt) when compared to the normal group.
Conclusion
We provide this open‐source database to assist in comparing current and future scales of facial function as well as facilitate comprehensive investigation of the entire spectrum of facial palsy. The automated machine learning‐based algorithm detected negative emotions at moderate levels of facial palsy and suggested a threshold severity of flaccid facial palsy beyond which joy was not perceived.
Level of Evidence
NA Laryngoscope, 130:32–37, 2020</description><identifier>ISSN: 0023-852X</identifier><identifier>EISSN: 1531-4995</identifier><identifier>DOI: 10.1002/lary.27986</identifier><identifier>PMID: 31021433</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>affectiva ; Algorithms ; Artificial intelligence ; Automation ; Comparative analysis ; emotion ; facial expression ; Facial palsy ; facial paralysis ; joy perception ; Machine learning ; nonflaccid facial palsy ; standard set</subject><ispartof>The Laryngoscope, 2020-01, Vol.130 (1), p.32-37</ispartof><rights>2019 The American Laryngological, Rhinological and Otological Society, Inc.</rights><rights>2020 The American Laryngological, Rhinological and Otological Society, Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4236-a28fa6bdba3db1f86264ac676968bc15abfcb972eca84379a33237fab1b9ebce3</citedby><cites>FETCH-LOGICAL-c4236-a28fa6bdba3db1f86264ac676968bc15abfcb972eca84379a33237fab1b9ebce3</cites><orcidid>0000-0003-4889-1052 ; 0000-0002-2884-4198</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Flary.27986$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Flary.27986$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31021433$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Greene, Jacqueline J.</creatorcontrib><creatorcontrib>Guarin, Diego L.</creatorcontrib><creatorcontrib>Tavares, Joana</creatorcontrib><creatorcontrib>Fortier, Emily</creatorcontrib><creatorcontrib>Robinson, Mara</creatorcontrib><creatorcontrib>Dusseldorp, Joseph</creatorcontrib><creatorcontrib>Quatela, Olivia</creatorcontrib><creatorcontrib>Jowett, Nate</creatorcontrib><creatorcontrib>Hadlock, Tessa</creatorcontrib><title>The spectrum of facial palsy: The MEEI facial palsy photo and video standard set</title><title>The Laryngoscope</title><addtitle>Laryngoscope</addtitle><description>Objectives
Facial palsy causes variable facial disfigurement ranging from subtle asymmetry to crippling deformity. There is no existing standard database to serve as a resource for facial palsy education and research. We present a standardized set of facial photographs and videos representing the entire spectrum of flaccid and nonflaccid (aberrantly regenerated or synkinetic) facial palsy. To demonstrate the utility of the dataset, we describe the relationship between level of facial function and perceived emotion expression as determined by an automated emotion detection, machine learning‐based algorithm.
Methods
Photographs and videos of patients with both flaccid and nonflaccid facial palsy were prospectively gathered. The degree of facial palsy was quantified using eFACE, House‐Brackmann, and Sunnybrook scales. Perceived emotion during a standard video of facial movements was determined using an automated, machine learning algorithm.
Results
Sixty participants were enrolled and categorized by eFACE score across the range of facial function. Patients with complete flaccid facial palsy (eFACE <60) had a significant loss of perceived joy compared to the nonflaccid and normal groups. Additionally, patients with only moderate flaccid and nonflaccid facial palsy had a significant increase in perceived negative emotion (contempt) when compared to the normal group.
Conclusion
We provide this open‐source database to assist in comparing current and future scales of facial function as well as facilitate comprehensive investigation of the entire spectrum of facial palsy. The automated machine learning‐based algorithm detected negative emotions at moderate levels of facial palsy and suggested a threshold severity of flaccid facial palsy beyond which joy was not perceived.
Level of Evidence
NA Laryngoscope, 130:32–37, 2020</description><subject>affectiva</subject><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Comparative analysis</subject><subject>emotion</subject><subject>facial expression</subject><subject>Facial palsy</subject><subject>facial paralysis</subject><subject>joy perception</subject><subject>Machine learning</subject><subject>nonflaccid facial palsy</subject><subject>standard set</subject><issn>0023-852X</issn><issn>1531-4995</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLAzEYRYMotlY3_gAJuBFhah7zSNyVUrVQUaSCrkKSydAp02ZMZpT-e1OnCrpw9YXvHm6SA8ApRkOMELmqpNsMScZZugf6OKE4ijlP9kE_hDRiCXnpgSPvlwjhjCboEPQoRgTHlPbB43xhoK-Nbly7graAhdSlrGAtK7-5htv0fjKZ_lrDemEbC-U6h-9lbiz0TThLl0NvmmNwUATInOzmADzfTObju2j2cDsdj2aRjglNI0lYIVOVK0lzhQuWkjSWOs1SnjKlcSJVoRXPiNGSxTTjklJCs0IqrLhR2tABuOh6a2ffWuMbsSq9NlUl18a2XhCCk_BJHm4bgPM_6NK2bh1eJwglWUIZwixQlx2lnfXemULUrlwFtQIjsfUstp7Fl-cAn-0qW7Uy-Q_6LTYAuAM-ysps_qkSs9HTa1f6CX-lh24</recordid><startdate>202001</startdate><enddate>202001</enddate><creator>Greene, Jacqueline J.</creator><creator>Guarin, Diego L.</creator><creator>Tavares, Joana</creator><creator>Fortier, Emily</creator><creator>Robinson, Mara</creator><creator>Dusseldorp, Joseph</creator><creator>Quatela, Olivia</creator><creator>Jowett, Nate</creator><creator>Hadlock, Tessa</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-4889-1052</orcidid><orcidid>https://orcid.org/0000-0002-2884-4198</orcidid></search><sort><creationdate>202001</creationdate><title>The spectrum of facial palsy: The MEEI facial palsy photo and video standard set</title><author>Greene, Jacqueline J. ; Guarin, Diego L. ; Tavares, Joana ; Fortier, Emily ; Robinson, Mara ; Dusseldorp, Joseph ; Quatela, Olivia ; Jowett, Nate ; Hadlock, Tessa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4236-a28fa6bdba3db1f86264ac676968bc15abfcb972eca84379a33237fab1b9ebce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>affectiva</topic><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Automation</topic><topic>Comparative analysis</topic><topic>emotion</topic><topic>facial expression</topic><topic>Facial palsy</topic><topic>facial paralysis</topic><topic>joy perception</topic><topic>Machine learning</topic><topic>nonflaccid facial palsy</topic><topic>standard set</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Greene, Jacqueline J.</creatorcontrib><creatorcontrib>Guarin, Diego L.</creatorcontrib><creatorcontrib>Tavares, Joana</creatorcontrib><creatorcontrib>Fortier, Emily</creatorcontrib><creatorcontrib>Robinson, Mara</creatorcontrib><creatorcontrib>Dusseldorp, Joseph</creatorcontrib><creatorcontrib>Quatela, Olivia</creatorcontrib><creatorcontrib>Jowett, Nate</creatorcontrib><creatorcontrib>Hadlock, Tessa</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>The Laryngoscope</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Greene, Jacqueline J.</au><au>Guarin, Diego L.</au><au>Tavares, Joana</au><au>Fortier, Emily</au><au>Robinson, Mara</au><au>Dusseldorp, Joseph</au><au>Quatela, Olivia</au><au>Jowett, Nate</au><au>Hadlock, Tessa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The spectrum of facial palsy: The MEEI facial palsy photo and video standard set</atitle><jtitle>The Laryngoscope</jtitle><addtitle>Laryngoscope</addtitle><date>2020-01</date><risdate>2020</risdate><volume>130</volume><issue>1</issue><spage>32</spage><epage>37</epage><pages>32-37</pages><issn>0023-852X</issn><eissn>1531-4995</eissn><abstract>Objectives
Facial palsy causes variable facial disfigurement ranging from subtle asymmetry to crippling deformity. There is no existing standard database to serve as a resource for facial palsy education and research. We present a standardized set of facial photographs and videos representing the entire spectrum of flaccid and nonflaccid (aberrantly regenerated or synkinetic) facial palsy. To demonstrate the utility of the dataset, we describe the relationship between level of facial function and perceived emotion expression as determined by an automated emotion detection, machine learning‐based algorithm.
Methods
Photographs and videos of patients with both flaccid and nonflaccid facial palsy were prospectively gathered. The degree of facial palsy was quantified using eFACE, House‐Brackmann, and Sunnybrook scales. Perceived emotion during a standard video of facial movements was determined using an automated, machine learning algorithm.
Results
Sixty participants were enrolled and categorized by eFACE score across the range of facial function. Patients with complete flaccid facial palsy (eFACE <60) had a significant loss of perceived joy compared to the nonflaccid and normal groups. Additionally, patients with only moderate flaccid and nonflaccid facial palsy had a significant increase in perceived negative emotion (contempt) when compared to the normal group.
Conclusion
We provide this open‐source database to assist in comparing current and future scales of facial function as well as facilitate comprehensive investigation of the entire spectrum of facial palsy. The automated machine learning‐based algorithm detected negative emotions at moderate levels of facial palsy and suggested a threshold severity of flaccid facial palsy beyond which joy was not perceived.
Level of Evidence
NA Laryngoscope, 130:32–37, 2020</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>31021433</pmid><doi>10.1002/lary.27986</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0003-4889-1052</orcidid><orcidid>https://orcid.org/0000-0002-2884-4198</orcidid></addata></record> |
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| source | Wiley Online Library All Journals |
| subjects | affectiva Algorithms Artificial intelligence Automation Comparative analysis emotion facial expression Facial palsy facial paralysis joy perception Machine learning nonflaccid facial palsy standard set |
| title | The spectrum of facial palsy: The MEEI facial palsy photo and video standard set |
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