The Use of Artificial Intelligence (AI) for Gait Analysis
Possibility of Using a Mobile Application for Three-plane Gait Analysis.
1 other identifier
observational
50
1 country
1
Brief Summary
The main purpose of this study will be to assess the consistency and reliability of measurements made using the Vicon three-plane gait analysis device (Vicon Motion Capture System Ltd, Oxford, UK) and a mobile application based on image recognition technology with the help of artificial intelligence.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for all trials
Started May 2024
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 19, 2024
CompletedFirst Posted
Study publicly available on registry
March 1, 2024
CompletedStudy Start
First participant enrolled
May 1, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 1, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
August 1, 2024
CompletedMarch 4, 2024
February 1, 2024
2 months
February 19, 2024
March 1, 2024
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Gait analysis by the Vicon system
To perform gait analysis, it is necessary to attach reflective markers to the subject at specific anthropometric points. Participants will be asked to walk barefoot in a relaxed manner at a self-selected comfort speed through a 10-meter path (6 repetitions of walking). Each passage through the path will be recorded using the Vicon three-plane gait assessment system, which generates angular values of the ankle, knee and hip joints (degree).
45 minutes
Gait analysis by the mobile image recognition application
During the gait analysis using the Vicon system, video recording of the full gait cycle in the sagittal plane from both sides, in the front plane from both sides and at an angle of 30, 45 and 60 degrees will be made using a smartphone camera. The recorded gait cycle using the camera will be analyzed in an image recognition application, which will generate angular values of the lower limb joints (degree).
45 minutes
Eligibility Criteria
Students of the Academy of Physical Education and Sport in Gdańsk,
You may qualify if:
- healthy people aged 20-25 years
You may not qualify if:
- orthopaedic disease
- neurological disease
- rheumatological disease
- pain in lower limbs in the last 6 months
- pain in lumbar spine in the last 6 months
- surgeries of lower limbs in the last 6 months
- surgeries of spine in the last 6 months
- musculoskeletal injuries in the lower limbs in the last 6 months
- musculoskeletal injuries in the lumbar spine in the last 6 months
- overweight and obesity, determined on the basis of the BMI value
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Gdansk University of Physical Education and Sport
Gdansk, Pomeranian Voivodeship, 80-336, Poland
Study Officials
- STUDY CHAIR
Paulina W Ewertowska, PhD
Gdansk University of Physical Education and Sport
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
February 19, 2024
First Posted
March 1, 2024
Study Start
May 1, 2024
Primary Completion
July 1, 2024
Study Completion
August 1, 2024
Last Updated
March 4, 2024
Record last verified: 2024-02