Estimating Jaw, Neck, and Shoulder Range of Motion Using an AI Model
Trial Parameters
Brief 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.
Eligibility Criteria
Inclusion Criteria: * Healthy adults without a history of head, neck or shoulder injury or surgery, and without HNC-related radiotherapy or chemoradiotherapy * Oral cancer patients with trismus, clinical signs of neck or shoulder joint impairment after oral cancer surgery or radiotherapy * Age between 20 and 65 years Exclusion Criteria: * Could not communicate * Had any disorder that could influence movement performance