Gait
Conditions
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
Interventions
DEVICEApplication Research of key points detection technology
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
Sponsors
Peking University Third Hospital
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
Yes
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Gait related parameters | 30mins | Step frequency/pace/gait cycle/step length |
Contacts
Primary ContactMouwang Zhou
Outcome results
None listed