[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100611086":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":12,"locations":10,"responsibleParty":18,"collaborators":10,"id":22,"slug":23,"hasResults":24,"nctId":25,"briefTitle":26,"officialTitle":26,"acronym":27,"eligibilityCriteria":28,"healthyVolunteers":29,"sex":30,"minAge":31,"maxAge":32,"enrollmentInfo":33,"targetDuration":36,"studyType":37,"phases":10,"briefSummary":38,"conditions":39,"keywords":41,"overallStatus":51,"whyStopped":10,"lastUpdateSubmitDate":52,"lastUpdatePostDateStruct":53,"startDateStruct":56,"completionDateStruct":58,"leadSponsor":60,"locationsCount":10},{"fullName":5,"class":6},"Vrije Universiteit Brussel","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Healthy subjects",null,"Age 18-65 years old",[13],{"name":14,"role":15,"phone":16,"phoneExt":10,"email":17},"Redona Brahimetaj, Doctor of Engineering Sciences","CONTACT","0032465597448","redona.brahimetaj@vub.be",{"type":19,"investigatorFullName":20,"investigatorTitle":21,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Bart Jansen","Prof.Dr.","100611086","training-and-testing-database-for-imu-based-gait-analysis-methods-100611086",false,"NCT07236008","Training and Testing Database for IMU Based Gait Analysis Methods","IMU-GAIT","Inclusion Criteria:\n\n* Healthy subjects with no motor impairments that disrupt the walking pattern.\n* No history of pain in the lower limbs in the past 6 months.\n* No history of lower limbs injuries\u002Fsurgeries in the past 6 months.\n* Language: Dutch and\u002For English and\u002For French speakers.\n* Age 18-65 years old\n* Subjects must be able to understand the instructions and to answer questions. Additionally, they should be able to; signal pain, fear, discomfort; give inform consent.\n\nExclusion Criteria:\n\n* Persons with comorbidity that could hinder the study (e.g.: unstable cardiovascular system disorders, lung disorders, severe osteoporosis).\n* Individuals with metal implants or skin conditions that would make sensor or marker placement difficult.",true,"ALL","18 Years","65 Years",{"count":34,"type":35},150,"ESTIMATED","1 Day","OBSERVATIONAL","The goal of this study is to establish a high-quality, synchronised dataset of gait events (GE) by simultaneously collecting inertial measurement unit (IMU) data and validated ground truth detections using a Vicon motion capture system. The primary objective is to address existing limitations in GE detection - such as poor generalisability, limited data diversity, and lack of precise synchronisation - through a rigorous protocol that ensures accuracy and transparency. The experiment is structured in three phases. First, Vicon-derived GE will be validated and refined using complementary modalities (force plates and video recordings). Next, deep learning (DL) algorithms will be developed and evaluated for GE detection directly from IMU data, with Vicon annotations serving as ground truth. Finally, the impact of differences in GE timing on spatiotemporal gait parameters (SGP) will be analysed to assess the feasibility of using IMU-only systems for reliable gait analysis.\n\nBy achieving these objectives, the study aims to improve the accuracy of GE detection from wearable sensors and enable more accessible, scalable, and reliable gait analysis outside the laboratory environment.",[40],"Healthy Subjects or Volunteers",[42,43,44,45,46,47,48,49,50],"Gait analysis","Gait events","Spatiotemporal gait parameters (SGP)","Inertial measurement units (IMU)","Wearable sensors","Motion capture (Vicon)","Deep learning","Machine learning","Healthy adults","NOT_YET_RECRUITING","2025-11-17",{"date":54,"type":55},"2025-11-19","ACTUAL",{"date":57,"type":35},"2025-12-01",{"date":59,"type":35},"2029-12-31",{"name":5,"class":6}]