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

NCT ID: NCT06629038

Last Updated: 2025-09-25

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

40 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-12-05

Study Completion Date

2025-12-31

Brief Summary

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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

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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

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Oral Cancer

Study Design

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Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Study Groups

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oral cancer patients

oral cancer patients with trismus, neck, or shoulder problems

observation alone

Intervention Type BEHAVIORAL

observation of maximal mouth opening, lateral excursion, and range of motion of shoulder abduction, neck joint

healthy adults

healthy adults without history of trismus, neck, or shoulder problems

observation alone

Intervention Type BEHAVIORAL

observation of maximal mouth opening, lateral excursion, and range of motion of shoulder abduction, neck joint

Interventions

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observation alone

observation of maximal mouth opening, lateral excursion, and range of motion of shoulder abduction, neck joint

Intervention Type BEHAVIORAL

Eligibility Criteria

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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
Minimum Eligible Age

20 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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National Taiwan University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Yueh-Hsia Chen, PhD

Role: PRINCIPAL_INVESTIGATOR

School and Graduate Institute of Physical Therapy, College of Medicine, National Taiwan University

Locations

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School and Graduate Institute of Physical Therapy, College of Medicine, National Taiwan University

Taipei, , Taiwan

Site Status RECRUITING

Countries

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Taiwan

Central Contacts

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Yueh-Hsia Chen, PhD

Role: CONTACT

+886 921435981

Facility Contacts

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Yueh-Hsia Chen, PhD

Role: primary

References

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Badiola-Bengoa A, Mendez-Zorrilla A. A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical Exercise. Sensors (Basel). 2021 Sep 7;21(18):5996. doi: 10.3390/s21185996.

Reference Type BACKGROUND
PMID: 34577204 (View on PubMed)

Sandler ML, Lazarus CL, Ru M, Sharif KF, Yue LE, Griffin MJ, Likhterov I, Chai RL, Buchbinder D, Urken ML, Ganz C. Effects of jaw exercise intervention timing on outcomes following oral and oropharyngeal cancer surgery: Pilot study. Head Neck. 2019 Nov;41(11):3806-3817. doi: 10.1002/hed.25908. Epub 2019 Aug 12.

Reference Type BACKGROUND
PMID: 31407421 (View on PubMed)

van der Geer SJ, Reintsema H, Kamstra JI, Roodenburg JLN, Dijkstra PU. The use of stretching devices for treatment of trismus in head and neck cancer patients: a randomized controlled trial. Support Care Cancer. 2020 Jan;28(1):9-11. doi: 10.1007/s00520-019-05075-7. Epub 2019 Nov 7.

Reference Type BACKGROUND
PMID: 31701267 (View on PubMed)

Shao CH, Chiang CC, Huang TW. Exercise therapy for cancer treatment-induced trismus in patients with head and neck cancer: A systematic review and meta-analysis of randomized controlled trials. Radiother Oncol. 2020 Oct;151:249-255. doi: 10.1016/j.radonc.2020.08.024. Epub 2020 Sep 3.

Reference Type BACKGROUND
PMID: 32890607 (View on PubMed)

Cohen EE, LaMonte SJ, Erb NL, Beckman KL, Sadeghi N, Hutcheson KA, Stubblefield MD, Abbott DM, Fisher PS, Stein KD, Lyman GH, Pratt-Chapman ML. American Cancer Society Head and Neck Cancer Survivorship Care Guideline. CA Cancer J Clin. 2016 May;66(3):203-39. doi: 10.3322/caac.21343. Epub 2016 Mar 22.

Reference Type BACKGROUND
PMID: 27002678 (View on PubMed)

Watters AL, Cope S, Keller MN, Padilla M, Enciso R. Prevalence of trismus in patients with head and neck cancer: A systematic review with meta-analysis. Head Neck. 2019 Sep;41(9):3408-3421. doi: 10.1002/hed.25836. Epub 2019 Jun 19.

Reference Type BACKGROUND
PMID: 31215723 (View on PubMed)

Stenum J, Cherry-Allen KM, Pyles CO, Reetzke RD, Vignos MF, Roemmich RT. Applications of Pose Estimation in Human Health and Performance across the Lifespan. Sensors (Basel). 2021 Nov 3;21(21):7315. doi: 10.3390/s21217315.

Reference Type BACKGROUND
PMID: 34770620 (View on PubMed)

Chen YH, Liang WA, Lin CR, Huang CY. A randomized controlled trial of scapular exercises with electromyography biofeedback in oral cancer patients with accessory nerve dysfunction. Support Care Cancer. 2022 Oct;30(10):8241-8250. doi: 10.1007/s00520-022-07263-4. Epub 2022 Jul 11.

Reference Type BACKGROUND
PMID: 35821447 (View on PubMed)

Chen YH, Lin CR, Liang WA, Huang CY. Motor control integrated into muscle strengthening exercises has more effects on scapular muscle activities and joint range of motion before initiation of radiotherapy in oral cancer survivors with neck dissection: A randomized controlled trial. PLoS One. 2020 Aug 6;15(8):e0237133. doi: 10.1371/journal.pone.0237133. eCollection 2020.

Reference Type BACKGROUND
PMID: 32760097 (View on PubMed)

Chen YH, Huang CY, Liang WA, Lin CR, Chao YH. Effects of Conscious Control of Scapular Orientation in Oral Cancer Survivors With Scapular Dyskinesis: A Randomized Controlled Trial. Integr Cancer Ther. 2021 Jan-Dec;20:15347354211040827. doi: 10.1177/15347354211040827.

Reference Type BACKGROUND
PMID: 34412536 (View on PubMed)

Beshara P, Chen JF, Read AC, Lagadec P, Wang T, Walsh WR. The Reliability and Validity of Wearable Inertial Sensors Coupled with the Microsoft Kinect to Measure Shoulder Range-of-Motion. Sensors (Basel). 2020 Dec 17;20(24):7238. doi: 10.3390/s20247238.

Reference Type BACKGROUND
PMID: 33348775 (View on PubMed)

Shepherd J, Hansjee S, Divall P, Raval P, Singh HP. How do digital range of motion measurement devices 'measure-up' to traditional goniometry in assessing shoulder range of motion? A systematic review and meta-analysis. Shoulder Elbow. 2024 Jul;16(4):363-381. doi: 10.1177/17585732231195554. Epub 2023 Aug 31.

Reference Type BACKGROUND
PMID: 39318409 (View on PubMed)

Takigami S, Inui A, Mifune Y, Nishimoto H, Yamaura K, Kato T, Furukawa T, Tanaka S, Kusunose M, Ehara Y, Kuroda R. Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model. Sensors (Basel). 2024 May 2;24(9):2912. doi: 10.3390/s24092912.

Reference Type BACKGROUND
PMID: 38733018 (View on PubMed)

van den Hoorn W, Lavaill M, Cutbush K, Gupta A, Kerr G. Comparison of Shoulder Range of Motion Quantified with Mobile Phone Video-Based Skeletal Tracking and 3D Motion Capture-Preliminary Study. Sensors (Basel). 2024 Jan 15;24(2):534. doi: 10.3390/s24020534.

Reference Type BACKGROUND
PMID: 38257626 (View on PubMed)

Other Identifiers

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202403103RINA

Identifier Type: -

Identifier Source: org_study_id

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