Ignite Creation Date:
2025-12-25 @ 1:03 AM
Ignite Modification Date:
2025-12-30 @ 12:19 PM
Study NCT ID:
NCT05443893
Status:
UNKNOWN
Last Update Posted:
2022-07-05
First Post:
2022-06-03
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Artificial Intelligence in Kinematics Analysis
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 30}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2022-07-10', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-07', 'completionDateStruct': {'date': '2022-08-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2022-07-01', 'studyFirstSubmitDate': '2022-06-03', 'studyFirstSubmitQcDate': '2022-07-01', 'lastUpdatePostDateStruct': {'date': '2022-07-05', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-07-05', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-07-29', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Gait related parameters', 'timeFrame': '30mins', 'description': 'Step frequency/pace/gait cycle/step length'}]}, 'conditionsModule': {'conditions': ['Gait']}, 'descriptionModule': {'briefSummary': "1. Establish data sets. The private data set includes relevant parameters including video of the subject's gait and standard methods for kinematic analysis;\n2. Develop new models. Based on public and private data sets, the kinematic analysis model of human key point detection is further developed.\n3. 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", 'detailedDescription': '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'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Normal gait subjects and abnormal gait subjects', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* 1\\. Abnormal gait.\n* Can walk 6m or more independently.\n* Older than 18.\n\nExclusion Criteria:\n\n* 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.\n* The mental and psychological state cannot cooperate with the completion of the experiment.\n* High risk of falls (Berg score ≤20）\n* Gait kinematics analysis equipment cannot be used together.'}, 'identificationModule': {'nctId': 'NCT05443893', 'briefTitle': 'Artificial Intelligence in Kinematics Analysis', 'organization': {'class': 'OTHER', 'fullName': 'Peking University Third Hospital'}, 'officialTitle': 'Application Research of Key Points Detection Technology of Artificial Intelligence in Kinematics Analysis', 'orgStudyIdInfo': {'id': 'M2021231'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Normal subjects', 'description': 'Gait analysis with artificial intelligence and traditional methods', 'interventionNames': ['Device: Application Research of key points detection technology']}, {'label': 'Subjects with abnormal gait', 'description': 'Gait analysis with artificial intelligence and traditional methods', 'interventionNames': ['Device: Application Research of key points detection technology']}], 'interventions': [{'name': 'Application Research of key points detection technology', 'type': 'DEVICE', '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', 'armGroupLabels': ['Normal subjects', 'Subjects with abnormal gait']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Mouwang Zhou', 'role': 'CONTACT', 'email': 'zhoumouwang@outlook.com', 'phone': '13910092892'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Peking University Third Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Zhou Mouwang', 'investigatorAffiliation': 'Peking University Third Hospital'}}}}