The Use of Artificial Intelligence (AI) for Gait Analysis

Gait Clinical Trial

Official title:

Possibility of Using a Mobile Application for Three-plane Gait Analysis.

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06289231
• Other study ID #: AWFiS/2023_5_PE
• Status: Not yet recruiting
• Start date: May 2024
• Est. completion date: August 2024

Study information

• Verified date: February 2024
• Source: Gdansk University of Physical Education and Sport
• Contact: Paulina W Ewertowska, PhD
• Phone: 500157143
• Email: paulina.ewertowska[@]awf.gda.pl
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Description:

The study will involve 50 healthy, physically active people aged 20-25. The participants will be subjected to movement analysis using the Vicon three-plane gait analysis system using reflective markers. Each of them will make 6 walks at their natural pace along a 10 m long path, during which a three-plane image of their walking will be recorded by the Vicon system. Additionally, during the examination, 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. First, the values generated by the Vicon system and the application from the sagittal plane recording will be compared. Then, the consistency of the values generated by the application from the recordings in the sagittal plane on both sides for the same lower limb will be checked. The last step will be to compare the compliance of the angular values from the Vicon system with the data generated in the application from recordings at angles of 60, 45, 30 and 0 degrees.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 50
• Est. completion date: August 2024
• Est. primary completion date: July 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 20 Years to 25 Years

Eligibility

Inclusion Criteria:

• healthy people aged 20-25 years

Exclusion Criteria:

• 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

Related Conditions & MeSH terms

• Gait

Locations

Country	Name	City	State
Poland	Gdansk University of Physical Education and Sport	Gdansk	Pomorskie

Sponsors (1)

Lead Sponsor	Collaborator
Gdansk University of Physical Education and Sport

Country where clinical trial is conducted

Poland, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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
Primary	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