Biometric Recognition and Rehabilitation Assessment of Lower Extremity Sports Injury Based on Gait Touch Information

Osteoarthritis, Knee Clinical Trial

Official title:

Biometric Recognition and Rehabilitation Assessment of Lower Extremity Sports Injury Based on Gait Touch Information

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04462913
• Other study ID #: OR001
• Status: Recruiting
• Start date: July 28, 2017
• Est. completion date: December 30, 2022

Study information

• Verified date: June 2020
• Source: Peking University Third Hospital
• Contact: Hongshi Huang, Doctor
• Phone: +8613910093298
• Email: huanghs[@]bjmu.edu.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The current common clinical methods cannot truly reflect the biomechanical status of the knee joint. Based on the foot-knee coupling mechanism, the simple and practical dynamic gait touch information provided by the 3D force platform are closely related to the knee biomechanics. The purpose of this study is to investigate the disease feature recognition, computer-aided diagnosis and rehabilitation assessment based on the gait touch information related to lower limb injuries.

Description:

Background:

The current common clinical methods cannot truly reflect the biomechanical status of the knee joint. The three-dimensional gait analysis is the gold standard, but it is difficult to apply clinically. There is an urgent need for a clinically practical method to quantitatively evaluate the biomechanics of the knee joint under dynamic weight bearing.

Methods:

50 healthy volunteers, 450 sports injuries patients (including hip, knee, and ankle joint diseases) and 50 patients with degenerative osteoarthritis were recruited.

55 passive reflective markers were placed bilaterally on the body. Lower extremity kinematics and dynamic plantar pressure during walking, jogging were collected.

Outcome evaluation indicators and statistical methods: The following indicators use repeated measurement two-factor analysis of variance: the left and right sides, different rehabilitation times are used as repeated measurement variables, to analyze the biomechanical changes of the lower limb joint biomechanics and gait touch information. A variety of machine learning methods (such as PCA, SVM, CNN, etc.) are used to analyze, and select the appropriate algorithm and parameters according to the learning effect. Finally, this study will establish a machine learning models for computer-aided diagnosis, treatment, and rehabilitation assessment.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 550
• Est. completion date: December 30, 2022
• Est. primary completion date: December 1, 2022
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• patients with a certain sports injury (soft tissue injury or degenerative osteoarthritis) of a joint of the lower limb (hip or knee or ankle or foot).

Exclusion Criteria:

• Cognitive impairment

• other injuries affecting movement performance.

Related Conditions & MeSH terms

• Athletic Injuries
• Osteoarthritis, Knee
• Sport Injury
• Wounds and Injuries

Intervention

Other:
• no intervention
This is an observation study, with no intervention

Locations

Country	Name	City	State
China	Peking University Third Hospital	Beijing

Sponsors (1)

Lead Sponsor	Collaborator
Peking University Third Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	walking speed	Three-dimensional gait analysis system and plantar pressure were used during walking.	On the day of enrollment.
Primary	ground reaction force	Three-dimensional gait analysis system and plantar pressure were used during walking.	On the day of enrollment.
Primary	knee flexion angle	Three-dimensional gait analysis system and plantar pressure were used during walking.	On the day of enrollment.
Primary	the moment of knee extension in the gait cycle	Three-dimensional gait analysis system and plantar pressure were used during walking.	On the day of enrollment.
Secondary	The International Knee Documentation Committee (IKDC) score	The International Knee Documentation Committee (IKDC) score was used to evaluate the knee health.The patients completed score by themselves. The lowest score is 0 and the highest score is 100.	On the day of enrollment.