Smartphone-Based Markerless Motion Capture for Orthopaedic Clinical Use

NCT05370534 | Withdrawn

• 2 other identifiers: 274321GM125503
• Study Type: observational
• Target: N/A
• Locations: 1 country
• Sites: 1

Brief Summary

The investigators propose to create a markerless smartphone-based MCA application using AR to measure joint motion and gait patterns to address this technology gap for a simple and inexpensive MCA.

Conditions

Musculoskeletal Diseases or Conditions

Keywords

Motion Capture; MCA; Markers; Markerless; biomechanics

Outcome Measures

Primary Outcomes (1)

• Hip, Knee and Spine Measurements

  angles

  1 hour

Study Arms (1)

Study Population

The investigators anticipate validating two specific actions: a box jump and walking gait. Both will be captured in two planes, coronal and sagittal. Healthy patients without musculoskeletal complaints will be voluntarily enrolled to undergo motion capture with both methods, completed during the same visit to the UAMS Human Biomechanics Laboratory. Each patient will perform a box jump and walking gait using each of the two modalities. We anticipate 4 hrs will be required for each patient: 1 hr for setup before the patient arrives, 1 hr for testing, and 2 hrs for data cleaning and initial processing. This work will be performed at the UAMS Human Biomechanics Laboratory (off campus on Aldersgate Road), which is equipped for this type of analysis.

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Study participants will be males and females between the ages of 18 years old to 65 years old that are healthy and without any active injuries limiting full participation, in particular no known spinal pathology, history of lower extremity surgery or significant cardiac history. There are no restrictions based on gender, race, or ethnicity.

You may qualify if:

• years old
• No known spinal pathology
• No previous lower extremity surgery
• No significant cardiac history

You may not qualify if:

• \<18 or \>65 years old
• Known spinal pathology
• Previous lower extremity surgery
• Significant cardiac history

Sponsors & Collaborators

• University of Arkansas: lead
• National Institutes of Health (NIH): collaborator

Study Sites (1)

University of Arkansas for Medical Sciences

Little Rock, Arkansas, 72205, United States

Location

Related Publications (15)

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  PMID: 34339317 BACKGROUND

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• Tanaka R, Takimoto H, Yamasaki T, Higashi A. Validity of time series kinematical data as measured by a markerless motion capture system on a flatland for gait assessment. J Biomech. 2018 Apr 11;71:281-285. doi: 10.1016/j.jbiomech.2018.01.035. Epub 2018 Feb 8.

  PMID: 29475751 BACKGROUND

MeSH Terms

Conditions

Musculoskeletal Diseases

Study Officials

• David B Bumpass, MD

  University of Arkansas

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 6, 2022
• First Posted: May 11, 2022
• Study Start: December 1, 2023
• Primary Completion: December 18, 2023
• Study Completion: December 18, 2023
• Last Updated: December 26, 2023

Record last verified: 2023-02

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)