Estimating Jaw, Neck, and Shoulder Range of Motion Using an AI Model
ConditionOral Cancer
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age20-65
SponsorNational Taiwan University Hospital
About this trial
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
This trial accepts healthy volunteersQualifiers
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
Disqualifiers
Could not communicate
Had any disorder that could influence movement performance
Trial population
primary care clinic, community, university
Trial design
Design model
Other
Time perspective
Prospective
Treatments tested in this trial
observation alone
Behavioralobservation of maximal mouth opening, lateral excursion, and range of motion of shoulder abduction, neck joint
Treatment groups
40 Participants
are divided into 2 treatment groupsGroup A: oral cancer patients1 intervention
Group B: healthy adults1 intervention
Trial outcomes
Primary outcomes
1
maximal mouth opening
maximal mouth opening
Time frame
The date of enrollment2
maximal lateral excursion of mandible
maximal lateral excursion of mandible
Time frame
The date of enrollment3
range of motion of shoulder abduction
range of motion of shoulder abduction
Time frame
The date of enrollment4
range of motion of neck
lateral side bending and rotation of the neck
Time frame
The date of enrollmentSponsors and contacts
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Source ClinicalTrials.gov