Artificial Intelligence in Kinematics Analysis

• Conditions: Gait
• Interventions: Device: Application Research of key points detection technology

• Registration Number: NCT05443893
• Lead Sponsor: Peking University Third Hospital

Brief Summary

1. Establish data sets. The private data set includes relevant parameters including video of the subject's gait and standard methods for kinematic analysis;

2. Develop new models. Based on public and private data sets, the kinematic analysis model of human key point detection is further developed.

3. Test the new model. By comparing the parameters with the standard method, the accuracy of the model was verified, and the kinematics analysis model of artificial intelligence with accuracy above 98% was obtained

Detailed Description

Artificial intelligence human key point detection model mainly has traditional algorithm, "top-down" algorithm and "bottom-up" algorithm three methods, three methods have advantages. This project will comprehensively use the above three methods to conduct algorithm and parameter debugging in the public data set and test in the private data set, so as to obtain the most suitable human key point recognition method for gait analysis

Study Timeline

• Study First Submitted: 2022-06-03
• Status Verified: 2022-07
• Study First Submitted QC: 2022-07-01
• Last Update Submitted: 2022-07-01
• Study First Posted: 2022-07-05
• Last Update Posted: 2022-07-05
• Study Start: 2022-07-10
• Primary Completion: 2022-07-29
• Study Completion: 2022-08-30

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 30

Inclusion Criteria

• 1. Abnormal gait.
• Can walk 6m or more independently.
• Older than 18.

Exclusion Criteria

• Fracture may be aggravated by walking in the acute stage or early postoperative stage. Have heart, lung, liver and kidney And other serious diseases, heart function grading greater than GRADE I (NYHA), respiratory failure and other symptoms and signs or Check the results.
• The mental and psychological state cannot cooperate with the completion of the experiment.
• High risk of falls (Berg score ≤20）
• Gait kinematics analysis equipment cannot be used together.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Normal subjects	Application Research of key points detection technology	Gait analysis with artificial intelligence and traditional methods
Subjects with abnormal gait	Application Research of key points detection technology	Gait analysis with artificial intelligence and traditional methods

Primary Outcome Measures

Name	Time	Method
Gait related parameters	30mins	Step frequency/pace/gait cycle/step length