Earticle

초록

영어

Purpose: We aimed to propose and validate a novel method for measuring and analyzing cervical spine range of motion (ROM) using built-in smartphone cameras and artificial intelligence technology. Methods: The participants were 15 healthy men (average age: 22.40±1.30 y, height: 175.60±4.17 cm, weight: 74.07±8.05 kg). Cervical spine ROM during extension, flexion, lateral bending, and rotation was collected using a three-dimensional (3D) motion analysis system. An application with the Pose Detection feature of the Google ML Kit was used to capture and record body segment positions. ROM was calculated using Visual 3D software, and multivariate linear regression analysis was performed on the collected data. Results: Lateral flexion (left) had the highest determination coefficient (Adjusted R2=0.851), showing the most consistent biomechanical pattern, while extension had a lower determination coefficient (Adjusted R2=0.747). ROM estimates that regression models had a root mean square error between 4.43° and 5.85° and a normalized root mean square error between 9.90% and 18.03%. Conclusion: This study presents a data-driven approach to understanding cervical motions using smartphones, providing foundational data for clinical evaluation.

목차

Abstract
Ⅰ. 서론
Ⅱ. 연구방법
1. 연구대상자
2. 실험 절차
3. 자료처리
4. 통계분석
Ⅲ. 결과
1. 경부 동작 별 회귀 분석 결과
2. 경부 동작 별 실제 관절 가동범위와 회귀식을 통해 추정한 관절 가동범위 비교
Ⅳ. 논의
Ⅴ. 결론
참고문헌

키워드

저자

• Da-Hoon Park [ 박다훈 | Cheongju University, Department of Sports Rehabilitation, Researcher ]
• Young-KI Hong [ 홍영기 | Cheongju University, Department of Sports Rehabilitation, Professor ] 교신저자

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  정형스포츠물리치료학회지 [Archives of Orthopedic and Sports Physical Therapy]

• 간기

  반년간

• pISSN

  1738-5946

• 수록기간

  2005~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 517 DDC 613