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Recruiting NCT07509619

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

Observational Oral Cancer AI (Artificial Intelligence)

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
This is an observational study: the protocol does not assign a study treatment.
Who it may be relevant to
Registry conditions: Oral Cancer, AI (Artificial Intelligence). Basic parameters: 20 years — 70 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Taiwan
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Validity and Reliability of an AI-based Physiotherapy Evaluation System for Oromandibular and Neck-Shoulder Range of Motion in Oral Cancer Patients

Overview

This study aims to evaluate the validity and reliability of a novel AI-based physiotherapy evaluation system for measuring oromandibular and neck-shoulder range of motion (ROM). Traditional ROM assessments rely on manual measurements, which may be influenced by rater experience and variability. The proposed AI system uses automated keypoint tracking to provide objective and standardized measurements. In this cross-sectional study, healthy adult participants will perform standardized ROM tasks. Measurements obtained from the AI system will be compared with those from two independent raters using conventional clinical tools. Repeated measurements will be conducted to assess intra-rater and inter-rater reliability. The agreement between the AI system and human raters will be evaluated to determine the system's clinical applicability.

Detailed description

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.

Primary outcome measures

  • Agreement Between AI and Manual Measurements [Time frame: Baseline]
Secondary outcome measures (5)
  • Mean Absolute Error (MAE) [Time frame: Baseline]
  • Intra-rater reliability of human raters [Time frame: Baselinte]
  • Inter-rater reliability among all raters [Time frame: Baseline]
  • Intra-rater reliability of AI system [Time frame: Baseline]
  • Systematic measurement bias [Time frame: Baseline]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model
Case-only

Study locations

Taiwan · 1 center
  • School and Graduate Institute of Physical Therapy, College of Medicine, National Taiwan Un — Taipei

Publications

  • Deb S, Islam MF, Rahman S, Rahman S. Graph Convolutional Networks for Assessment of Physical Rehabilitation Exercises. IEEE Trans Neural Syst Rehabil Eng. 2022;30:410-419. doi: 10.1109/TNSRE.2022.3150392. Epub 2022 Feb 23. PMID 35139022
  • Agarwal P, Shiva Kumar HR, Rai KK. Trismus in oral cancer patients undergoing surgery and radiotherapy. J Oral Biol Craniofac Res. 2016 Nov;6(Suppl 1):S9-S13. doi: 10.1016/j.jobcr.2016.10.004. Epub 2016 Oct 22. PMID 27900243

Identifiers

NCT: NCT07509619 · 202603023RIND

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗