{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T16:03:51Z","timestamp":1770134631459,"version":"3.49.0"},"reference-count":12,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2015,10,21]],"date-time":"2015-10-21T00:00:00Z","timestamp":1445385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Facial nerve palsy induces a weakness or loss of facial expression through damage of the facial nerve. A quantitative and reliable assessment system for facial nerve palsy is required for both patients and clinicians. In this study, we propose a rapid and portable smartphone-based automatic diagnosis system that discriminates facial nerve palsy from normal subjects. Facial landmarks are localized and tracked by an incremental parallel cascade of the linear regression method. An asymmetry index is computed using the displacement ratio between the left and right side of the forehead and mouth regions during three motions: resting, raising eye-brow and smiling. To classify facial nerve palsy, we used Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), and Leave-one-out Cross Validation (LOOCV) with 36 subjects. The classification accuracy rate was 88.9%.<\/jats:p>","DOI":"10.3390\/s151026756","type":"journal-article","created":{"date-parts":[[2015,10,22]],"date-time":"2015-10-22T03:05:31Z","timestamp":1445483131000},"page":"26756-26768","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["A Smartphone-Based Automatic Diagnosis System for Facial Nerve Palsy"],"prefix":"10.3390","volume":"15","author":[{"given":"Hyun","family":"Kim","sequence":"first","affiliation":[{"name":"Interdisciplinary Program of Bioengineering, Seoul National University, Seoul 03080, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7361-4930","authenticated-orcid":false,"given":"So","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Head and Neck Surgery, Seoul National University,  Boramae Medical Center, Seoul 07061, Korea"}]},{"given":"Young","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Head and Neck Surgery, Seoul National University,  Boramae Medical Center, Seoul 07061, Korea"}]},{"given":"Kwang","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, College of Medicine, Seoul National University,  Seoul 03080, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2015,10,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1177\/019459988509300202","article-title":"Facial nerve grading system","volume":"93","author":"House","year":"1985","journal-title":"Otolaryngol. Head Neck Surg."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.cmpb.2009.11.007","article-title":"PC-based asymmetry analyzer for facial palsy study in uncontrolled environment: A preliminary study","volume":"99","author":"Park","year":"2010","journal-title":"Comput. Methods Prog. Biomed."},{"key":"ref_3","first-page":"2751","article-title":"Automatic recognition of facial movement for paralyzed face","volume":"24","author":"Wang","year":"2014","journal-title":"Biomed. Mater. Eng."},{"key":"ref_4","unstructured":"McGrenary, S., O'Reilly, B.F., and Soraghan, J.J. (2005, January 23\u201324). Objective grading of facial paralysis using artificial intelligence analysis of video data. 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Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., and Pantic, M. (2013, January 23\u201328). A semi-automatic methodology for facial landmark annotation. Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Portland, OR, USA.","DOI":"10.1109\/CVPRW.2013.132"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., and Pantic, M. (2013, January 2\u20138). 300 faces in-the-wild challenge: The first facial landmark localization challenge. Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops (ICCVW), Sydney, NSW, Australia.","DOI":"10.1109\/ICCVW.2013.59"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/10\/26756\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:50:35Z","timestamp":1760215835000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/10\/26756"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,10,21]]},"references-count":12,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2015,10]]}},"alternative-id":["s151026756"],"URL":"https:\/\/doi.org\/10.3390\/s151026756","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,10,21]]}}}