A Novel Technique for Estimating Maximal Jaw Movement, Neck and Shoulder Joint Range of Motion Using an Artificial Intelligence Model
Status: Recruiting
Location: See location...
Intervention Type: Behavioral
Study Type: Observational
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
Participation Requirements
Sex: All
Minimum Age: 20
Maximum Age: 65
Healthy Volunteers: t
View:
• 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
Locations
Other Locations
Taiwan
School and Graduate Institute of Physical Therapy, College of Medicine, National Taiwan University
RECRUITING
Taipei
Contact Information
Primary
Yueh-Hsia Chen, PhD
yuehhsiachen@ntu.edu.tw
+886 921435981
Time Frame
Start Date: 2024-12-05
Estimated Completion Date: 2025-12-31
Participants
Target number of participants: 40
Treatments
oral cancer patients
oral cancer patients with trismus, neck, or shoulder problems
healthy adults
healthy adults without history of trismus, neck, or shoulder problems
Related Therapeutic Areas
Sponsors
Leads: National Taiwan University Hospital