1. From spasms to smiles: how facial recognition and tracking can quantify hemifacial spasm severity and predict treatment outcomes.
- Author
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Menabbawy AA, Ruhser L, Refaee EE, Weidemeier ME, Matthes M, and Schroeder HWS
- Subjects
- Humans, Male, Female, Retrospective Studies, Middle Aged, Treatment Outcome, Adult, Aged, Smiling physiology, Facial Recognition physiology, Severity of Illness Index, Video Recording methods, Hemifacial Spasm surgery, Quality of Life
- Abstract
Purpose: Currently available grading and classification systems for hemifacial spasm either rely on subjective assessments or are excessively intricate. Here, we make use of facial recognition and facial tracking technologies towards accurately grouping patients according to severity and characteristics of the spasms., Methods: A retrospective review of our prospectively maintained preoperative videos database for hemifacial spasm was done. Videos were analyzed using an Apple AR kit-based App. A facial mesh is automatically allocated to specific biometric facial points. Videos are analyzed using Blender software for measuring the amplitude and frequency of the spasms. Classification of the patients into groups was done using both divisive k-means and agglomerative hierarchical clustering. Correlation-Analysis with preoperative quality of Life (Qol) using SF-36 questionnaire and HFS-8 score was performed. Additionally, correlation with postoperative outcome was calculated., Results: 79 preoperative videos were included. Both up-bottom and bottom-up clustering approaches grouped the patients into 3 different clusters according to 4 variables (eye closure, mouth distance change, rate, and repetition of the spasms). Correlation of the groups with the Qol was done for 46/79 patients (58.2%). Spasms could be classified into mild, moderate clonic and severe tonic spasms. Patients with mild spasms showed better Qol scores. Moderate clonic spasms experienced best outcomes following microvascular decompression., Conclusion: This novel classification using facial-tracking and augmented-reality is easy to use and apply. It quantifies the severity and type of the spasms and relates it to the quality of life of patients, postoperative outcome, and could guide our management strategy., Competing Interests: Declarations. Ethics approval: All procedures performed in this study involving human participants were in accordance with the ethical standards of the local institutional research committee (Ethical committee of the University Medicine Greifswald) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Ethical committee approval number BB 101/16. Informed consent was obtained from all patients including using their videos for research purposes. Consent for publication: “The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where—ever it may be located; and, vi) licence any third party to do any or all of the above.” Consent to participate: Although no data in this study could lead to public identification of the patients, all the participating patients signed consent to publication of their data. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)
- Published
- 2025
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