Korean Journal of Acupuncture

  • 제42권1호
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  • Pages.1-18
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  • 2025
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  • 2287-3368(pISSN)
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  • 2287-3376(eISSN)
경락경혈학회 (Society for Meridian and Acupoint)
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안면마비 평가 도구에 관한 개발 현황 리뷰: 자동화 방식을 중심으로

A Review on Development Trends of Facial Palsy Grading System: Mainly on Automatic Method

  • 이자하 (동국대학교 한의과대학 침구과 대학원) ;
  • 문정현 (동국대학교 한의과대학 침구과 대학원) ;
  • 박경은 (동국대학교 한의과대학 침구과 대학원) ;
  • 성원석 (동국대학교 분당한방병원 침구과) ;
  • 김영수 (인테그로메디랩) ;
  • 김은정 (동국대학교 분당한방병원 침구과)
  • Ja-Ha Lee (Department of Acupuncture & Moxibustion, College of Korean Medicine, Dongguk University Graduate School) ;
  • Jeong-Hyun Moon (Department of Acupuncture & Moxibustion, College of Korean Medicine, Dongguk University Graduate School) ;
  • Gyoungeun Park (Department of Acupuncture & Moxibustion, College of Korean Medicine, Dongguk University Graduate School) ;
  • Won-Suk Sung (Department of Acupuncture & Moxibustion, Dongguk University Bundang Oriental Hospital) ;
  • Young-soo Kim (Integro Medi Lab Co., Ltd.) ;
  • Eun-Jung Kim (Department of Acupuncture & Moxibustion, Dongguk University Bundang Oriental Hospital)
  • 투고 : 2024.10.31
  • 심사 : 2025.01.16
  • 발행 : 2025.03.27
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초록

Objectives : Grading facial paralysis plays a crucial role in establishing treatment plans and determining prognosis. Both domestic and international efforts have actively focused on the development of objective automated grading systems. The purpose of this study is to investigate trends in Automated Facial Palsy Grading Systems through literature search. Methods : Using PubMed, OASIS, and other databases, related research papers published from 2000 to 2024 were analyzed. The studies were analyzed by dividing into Automated Grading Image Processing (2D, 3D, Video), Landmark Assignment and Standard Grading System for comparison. Results : A total of 13 studies were selected in this study. The first article was published in 2013. Studies were rapidly increased since 2019. The mostly used input data was photo. The other data were 3D photo and video. Studies using 68 landmark assignment system were the most prevalent, followed by OpenCV, Manual attachment, and other Machine Learning algorithms. There were 6 studies compared with House-Brackmann grading system, 4 studies compared with Sunny brook facial grading system, 3 studies compared with Nottingham scale and also studies involving Yanagihara grading system, eFACE, electroneurography (ENoG). Conclusions : The automated Grading systems were developed using various technologies, including image processing, automatic landmark assignment, OpenCV, machine learning, and applications. This automated grading systems demonstrated accuracy comparable to or exceeding that of conventional subjective evaluation methods. Moreover, it significantly reduced the time required for facial paralysis assessment, highlighting its potential as a viable alternative to subjective evaluation.

키워드

과제정보

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (grant number RS-2022-KH127664). Funder only provided the financial support and did not involve in this article including the review, editing, or the submission for publication.

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