[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100387166":3},{"organization":4,"armGroups":7,"interventions":23,"overallOfficials":33,"centralContacts":38,"locations":47,"responsibleParty":67,"collaborators":69,"id":72,"slug":73,"hasResults":74,"nctId":75,"briefTitle":76,"officialTitle":77,"acronym":10,"eligibilityCriteria":78,"healthyVolunteers":79,"sex":80,"minAge":81,"maxAge":82,"enrollmentInfo":83,"targetDuration":10,"studyType":86,"phases":10,"briefSummary":87,"conditions":88,"keywords":92,"overallStatus":50,"whyStopped":10,"lastUpdateSubmitDate":101,"lastUpdatePostDateStruct":102,"startDateStruct":105,"completionDateStruct":107,"leadSponsor":109,"locationsCount":110},{"fullName":5,"class":6},"University of Pennsylvania","OTHER",[8,14,18],{"label":9,"type":10,"description":11,"interventionNames":12},"Cross-sectional-150 infants (atypical vs typical)",null,"Arm (Study)1: To assess the concurrent validity of a multimodal instrumented gym with existing clinical tools. Here, using 150 infants, we will focus on converting data from an instrumented gym into estimates of the standard clinical tests.",[13],"Diagnostic Test: PANDA Gym",{"label":15,"type":10,"description":16,"interventionNames":17},"Longitudinal cohort - 50 infants (atypical vs typical)","Arm (Study) 2: To discover the features related to long-term motor development. Here we will convert data collected longitudinally from 50 infants, using both instrumented gym and video recordings, into estimates standard clinical tests change over time and track features over developmental timescales.",[13],{"label":19,"type":10,"description":20,"interventionNames":21},"Cross-sectional-1500 infants (atypical vs typical)","Arm (Study) 3: To develop a computer vision-based algorithm to quantify infant motor performance from a single-camera video. Here using video data from 1200 infants, plus those gathered from Arm 1 and Arm 2, we will extract pose data from single-camera video recordings and convert these into kinematic features and relevant scores needed to classify infant movement.",[22],"Other: Mobile App",[24,29],{"type":25,"name":26,"description":27,"armGroupLabels":28,"otherNames":10},"DIAGNOSTIC_TEST","PANDA Gym","Infants will lie supine on a flat surface and will be placed in the PANDA gym where they either move by themselves or will interact with an instrumented toy. We will collect video, mat, and toy data from PANDA gym under two conditions: 1) infants playing supine without a toy and 2) infants reach, grasp and kick of the new PANDA toy. A test session will proceed as follows: The infant will be placed on his or her back at a predetermined position on the gym mat for the 2-minute no toy condition. Next, the toy will be given to the baby and adjusted for the infant to reach or kick. A caregiver will be seated at the head of the baby (out of a baby's sight) to provide comfort if needed. Testing will be done in NICU or at daycare or the rehabilitation robotics lab at University of Pennsylvania.",[9,15],{"type":6,"name":30,"description":31,"armGroupLabels":32,"otherNames":10},"Mobile App","The parent or legal guardian will be consented first via the virtual rounding mobile app. They will also be asked to fill out general surveys including, a demographic survey, and a case report form, and a user feedback survey that provides relevant information, on both the family's and infant's medical history and experience. (see the flow-chart for the app). Within the caregiver survey, we will request the pediatrician (or primary care physician) name. We believe that with the baby name, caregiver name, zip code, and physician name, we will be able to locate the physician if needed.\n\nParents or legal guardians or the research will be asked to collect video via the MOBILE app. They will be instructed to ensure that the infant lies supine in no more than one-layer of tight-fitting clothing (i.e. infant onesie) while calm and awake. In all cases, we will have video recordings of the baby. They will be asked to upload the video to the app.",[19],[34],{"name":35,"affiliation":36,"role":37},"Michelle J Johnson, PhD","The University of Pennsylvania","PRINCIPAL_INVESTIGATOR",[39,43],{"name":35,"role":40,"phone":41,"phoneExt":10,"email":42},"CONTACT","215-893-2665","johnmic@pennmedicine.upenn.edu",{"name":44,"role":40,"phone":45,"phoneExt":10,"email":46},"Laura Prosser, PhD","215-590-2495","ProsserL@email.chop.edu",[48],{"facility":49,"status":50,"city":51,"state":52,"zip":53,"country":54,"countryCode":55,"cosmosGeoPoint":56,"geoPoint":61,"contacts":62},"Childrens Hospital of Philadelphia","RECRUITING","Philadelphia","Pennsylvania","19104","United States","US",{"type":57,"coordinates":58},"Point",[59,60],-75.16362,39.95238,{"lat":60,"lon":59},[63],{"name":64,"role":40,"phone":65,"phoneExt":10,"email":66},"Noor Ruwaih","267-426-7032","ruwaihn@email.chop.edu",{"type":68,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[70],{"name":71,"class":6},"Children's Hospital of Philadelphia","100387166","panda-gym-automated-assessment-of-neurodevelopment-in-infants-at-risk-for-motor-disability-100387166",false,"NCT04321200","PANDA Gym: Automated Assessment of Neurodevelopment in Infants at Risk for Motor Disability","Automated Assessment of Neurodevelopment in Infants at Risk for Motor Disability","Infants, male and female, between 0-6 months (Infants older than 6 months before initial enrollment will be excluded).\n\n* Infants with early brain injury (EBI):\n\n  * Hydrocephalus\n  * Hypoxic-ischemic encephalopathy (HIE)\n  * Periventricular leukomalacia (PVL)\n  * Intraventricular hemorrhage (IVH)\n  * Stroke\n* Healthy infants (controls):\n\n  o No history of early brain injury (EBI)\n* Infants without EBI\u002Frisk for future disability:\n\n  * Infants without known brain injuries, but with a history of preterm birth less than 32-week gestation with significant medical problems, difficulty eating, or who lack head control at 4 months of age or later will be classified as moderate risk.",true,"ALL","0 Months","6 Months",{"count":84,"type":85},1700,"ESTIMATED","OBSERVATIONAL","Early childhood detection of motor delays or impairments provides the opportunity for early treatment which improves health outcomes. This study will use state of the art sensors combined with machine learning algorithms to develop objective, accurate, easy-to-use tools for the early scoring of deficits and lays the foundation for the early prediction of physical disability.",[89,90,91],"Pediatric ALL","Infant Development","Neurodevelopmental Disorders",[93,94,95,96,97,98,99,100],"Infants","Neurodevelopment","Developmental Delays","Electronics","Early Intervention","Sensory and Motor","NICU","Natural Play","2025-09-22",{"date":103,"type":104},"2025-09-23","ACTUAL",{"date":106,"type":104},"2020-11-01",{"date":108,"type":85},"2026-07-01",{"name":5,"class":6},1]