[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117756-en":3,"doc-seo-117756-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117756,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",7,"Healthcare","Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis - A Feasibility Study","Surface electromyography (EMG) enables detection of muscle activity across nine intrinsic and extrinsic ear muscles during facial movements. In patients with postparalytic facial synkinesis (PFS), synkinetic EMG activity affects ear muscles, motivating an algorithmic approach to recognize specific facial expressions. The study established a machine-learning method using surface EMG recordings from auricular muscles to detect eyelid closure and smiling. Sixteen PFS patients underwent standardized eye-closure and smiling tasks.","diagnostics  \nArticle  \nMachine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis:  \nA Feasibility Study  \nJakob Hochreiter 1,2, Eric Hoche 3, Luisa Janik 3, Gerd Fabian Volk 3,4,5, Lutz Leistritz 6, Christoph Anders 7 and Orlando Guntinas-Lichius 3,4,5, *  \nCitation: Hochreiter, J.; Hoche, E.; Janik, L.; Volk, G.F.; Leistritz, L.; Anders, C.; Guntinas-Lichius, O. Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study. Diagnostics 2023, 13, 554. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)diagnostics13030554  \nAcademic Editors: Azhar Zam and Esa Prakasa  \nReceived: 27 October 2022  \nRevised: 27 January 2023  \nAccepted: 31 January 2023  \nPublished: 2 February 2023  \nCopyright: © 2023 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://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 Department of Medical Engineering, University of Applied Sciences Upper Austria, 4020 Linz, Austria  \n2 MED-EL Elektromedizinische Geräte GmbH, 6020 Innsbruck, Austria  \n3 Department of Otorhinolaryngology, Jena University Hospital, 07743 Jena, Germany  \n4 Facial-Nerve-Center, Jena University Hospital, 07747 Jena, Germany  \n5 Center for Rare Diseases, Jena University Hospital, 07747 Jena, Germany  \n6 Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital, 07743 Jena, Germany  \n7 Division for Motor Research, Pathophysiology and Biomechanics, Department for Trauma-, Hand-and Reconstructive Surgery, Jena University Hospital, 07743 Jena, Germany  \n* Correspondence: [orlando.guntinas@med.uni-jena.de](orlando.guntinas@med.uni-jena.de); Tel.: +49-3641-9329301; Fax: +49-3641-9329302  \nAbstract: Surface electromyography (EMG) allows reliable detection of muscle activity in all nine intrinsic and extrinsic ear muscles during facial muscle movements. The ear muscles are affected by synkinetic EMG activity in patients with postparalytic facial synkinesis (PFS) . The aim of the present work was to establish a machine-learning-based algorithm to detect eyelid closure and smiling in patients with PFS by recording sEMG using surface electromyography of the auricular muscles. Sixteen patients (10 female, 6 male) with PFS were included. EMG acquisition of the anterior auricular muscle, superior auricular muscle, posterior auricular muscle, tragicus muscle, orbicularis oculi muscle, and orbicularis oris muscle was performed on both sides of the face during standardized eye closure and smiling tasks. Machine-learning EMG classification with a support vector machine allowed for the reliable detection of eye closure or smiling from the ear muscle recordings with clear distinction to other mimic expressions. These results show that the EMG of the auricular muscles inpatients with PFS may contain enough information to detect facial expressions to trigger a future implant in a closed-loop system for electrostimulation to improve insufficient eye closure and smiling in patients with PFS.  \nKeywords: auricular muscles; facial muscles; human; facial palsy; electrophysiology; ear wiggling; muscle trigger; support vector machine  \n1. Introduction  \nThe auricle of humans contains three extrinsic and six intrinsic muscles [1] . All ear muscles are innervated by the facial nerve [1] . Berzin and Fortinguerra showed EMG activity in the three external muscles (anterior, superior, and posterior auricular) during smiling and yawning [2] . Recently, Rüschenschmidt et al. established a standardized protocol for a reliable surface EMG examination of all ","cbCaihf47NxMYRDO","https://ap.wps.com/l/cbCaihf47NxMYRDO","pdf",1929703,1,12,"English","en",105,"# Abstract\n# Introduction\n## Auricular muscle EMG in facial movements\n## Synkinesis-related activation patterns\n# Materials and Methods","[{\"question\":\"What goal does the study pursue in PFS patients?\",\"answer\":\"To build a machine-learning-based algorithm that detects eyelid closure and smiling in patients with postparalytic facial synkinesis using surface EMG from auricular muscles.\"},{\"question\":\"Which signals and muscles were recorded for detection?\",\"answer\":\"Surface EMG was recorded bilaterally from multiple ear/face-relevant muscles, including anterior, superior, and posterior auricular muscles, as well as muscles contributing to eye closure and smiling tasks.\"},{\"question\":\"How does the machine-learning model perform expression recognition?\",\"answer\":\"A support vector machine classifier enables reliable detection of eye closure or smiling from ear muscle recordings, with clear separation from other mimic expressions.\"}]","Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis - A Feasibility Study | PDF",1785679409,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-based-detecting-of-eyelid-closure-and-smiling-using-surface-electromyography-of-auricular-muscles-in-patients-with-postparalytic-facial-synkinesis-a-feasibility-study","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-based-detecting-of-eyelid-closure-and-smiling-using-surface-electromyography-of-auricular-muscles-in-patients-with-postparalytic-facial-synkinesis-a-feasibility-study/117756/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What goal does the study pursue in PFS patients?","Question",{"text":75,"@type":76},"To build a machine-learning-based algorithm that detects eyelid closure and smiling in patients with postparalytic facial synkinesis using surface EMG from auricular muscles.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which signals and muscles were recorded for detection?",{"text":80,"@type":76},"Surface EMG was recorded bilaterally from multiple ear/face-relevant muscles, including anterior, superior, and posterior auricular muscles, as well as muscles contributing to eye closure and smiling tasks.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the machine-learning model perform expression recognition?",{"text":84,"@type":76},"A support vector machine classifier enables reliable detection of eye closure or smiling from ear muscle recordings, with clear separation from other mimic expressions.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,118,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":116,"slug":117},40,"healthcare",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":29,"slug":121},8,"Research & Report","research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]