AI-based Physiotherapy Evaluation System for Range of Motion in Oral Cancer Patients

This study is a cross-sectional measurement study designed to evaluate the reliability and concurrent validity of an AI-based physiotherapy evaluation system for assessing oromandibular and neck-shoulder range of motion (ROM). Participants will be healthy adults aged 20 to 70 years who meet predefined inclusion and exclusion criteria. After providing informed consent, participants will perform standardized movements, including mouth opening and cervical and shoulder ROM tasks.

Each participant will undergo three repeated measurements for each movement. ROM will be assessed using three methods: (1) an AI-based system utilizing real-time keypoint tracking and automated angle calculation, (2) manual measurement by Rater 1, and (3) independent manual measurement by Rater 2 using a goniometer or TheraBite ROM scale.

To minimize measurement bias and fatigue effects, the order of the three assessment methods will be randomized for each participant. Raters will be blinded to each other's measurements and to the AI-generated results.

The primary outcomes include inter-rater reliability and intra-rater reliability of the AI system, as well as agreement between AI-based and manual measurements. Reliability will be assessed using intraclass correlation coefficients (ICC), while agreement will be evaluated using Bland-Altman analysis and mean absolute error (MAE).

This study is expected to provide evidence supporting the clinical applicability of AI-based physiotherapy assessment tools, particularly for standardized and scalable musculoskeletal evaluations.

Inclusion criteria

• Healthy adults aged 20 to 70 years
• No trismus
• No history of head, neck, or shoulder injury or surgery
• No history of head and neck cancer-related radiotherapy or chemotherapy

Exclusion criteria

• Inability to communicate or follow instructions
• Any condition that may affect movement performance