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RecruitingNCT06629038

Estimating Jaw, Neck, and Shoulder Range of Motion Using an AI Model

A Novel Technique for Estimating Maximal Jaw Movement, Neck and Shoulder Joint Range of Motion Using an Artificial Intelligence Model

Status
Recruiting
Phase
Study type
Observational
Enrollment
40 (estimated)
Sponsor
National Taiwan University Hospital · Academic / Other
Sex
All
Age
20 Years – 65 Years
Healthy volunteers
Accepted

Summary

This observational study aims to develop an AI-based system for tracking mandibular and shoulder movements using deep learning techniques. It will compare AI-generated pose estimations with gold standard measurements to assess accuracy, particularly in patients with functional impairments from oral cancer treatment, such as trismus, spinal accessory nerve dysfunction, neck dystonia, and radiation fibrosis.

Detailed description

Due to the involvement of various structures, patients with oral cancer may experience functional impairments after treatment, such as trismus, spinal accessory nerve dysfunction, neck dystonia, radiation fibrosis, and fatigue. This observational study aims to develop an AI-based system for tracking mandibular and shoulder movements using deep learning techniques. AI-generated pose estimations will be compared with gold standard measurements: maximal mouth opening will be compared with caliper measurements, and Therabilte scale, while shoulder abduction range of motion will be compared with universal goniometer measurements. We will recruit 20 healthy adults and 20 oral cancer patients. Data on maximal mouth opening and shoulder abduction will be collected through video recordings, calipers, Therabilte scale, and universal goniometers. The videos will be analyzed using deep learning to estimate mouth opening and shoulder abduction angles. These estimates will then be compared with the gold standard measurements. The Intraclass Correlation Coefficient (ICC), Mean Absolute Error (MAE), and Coefficient of Variation (CV) will be used as performance indicators to assess and compare the reliability, accuracy, and consistency of the models.

Conditions

Interventions

TypeNameDescription
BEHAVIORALobservation aloneobservation of maximal mouth opening, lateral excursion, and range of motion of shoulder abduction, neck joint

Timeline

Start date
2024-12-05
Primary completion
2026-12-31
Completion
2026-12-31
First posted
2024-10-08
Last updated
2026-02-11

Locations

1 site across 1 country: Taiwan

Source: ClinicalTrials.gov record NCT06629038. Inclusion in this directory is not an endorsement.

Estimating Jaw, Neck, and Shoulder Range of Motion Using an AI Model (NCT06629038) · Clinical Trials Directory