[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100627389":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":19,"centralContacts":23,"locations":28,"responsibleParty":44,"collaborators":7,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":7,"eligibilityCriteria":53,"healthyVolunteers":49,"sex":54,"minAge":55,"maxAge":56,"enrollmentInfo":57,"targetDuration":7,"studyType":60,"phases":7,"briefSummary":61,"conditions":62,"keywords":65,"overallStatus":31,"whyStopped":7,"lastUpdateSubmitDate":70,"lastUpdatePostDateStruct":71,"startDateStruct":74,"completionDateStruct":76,"leadSponsor":78,"locationsCount":79},{"fullName":5,"class":6},"Fu Jen Catholic University","OTHER",null,[9,13,16],{"type":10,"name":11,"description":12,"armGroupLabels":7,"otherNames":7},"DEVICE","electronic stethoscope","digital device amplifying and recording cardiopulmonary sounds",{"type":10,"name":14,"description":15,"armGroupLabels":7,"otherNames":7},"fingertip pulse oximeter","a small device placed on the finger to measure blood oxygen saturation (SpO₂) and pulse rate noninvasively.",{"type":10,"name":17,"description":18,"armGroupLabels":7,"otherNames":7},"pressure-sensing mattresses","using ballistocardiography (BCG) for monitoring respiration and heart rate",[20],{"name":21,"affiliation":5,"role":22},"Ke-Yun Chao, PhD","PRINCIPAL_INVESTIGATOR",[24],{"name":21,"role":25,"phone":26,"phoneExt":7,"email":27},"CONTACT","+886-905-301-879","C00152@mail.fjuh.fju.edu.tw",[29],{"facility":30,"status":31,"city":32,"state":7,"zip":33,"country":34,"countryCode":35,"cosmosGeoPoint":36,"geoPoint":41,"contacts":42},"Fu Jen Catholic University Hospital, Fu Jen Catholic University","RECRUITING","New Taipei City","24352","Taiwan","TW",{"type":37,"coordinates":38},"Point",[39,40],121.45703,25.06199,{"lat":40,"lon":39},[43],{"name":21,"role":25,"phone":26,"phoneExt":7,"email":27},{"type":22,"investigatorFullName":45,"investigatorTitle":46,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"Ke-Yun, Chao","Assistant Professor","100627389","multimodal-deep-learning-model-for-predicting-the-apnea-hypopnea-index-in-obstructive-sleep-100627389",false,"NCT07447999","Multimodal Deep Learning Model for Predicting the Apnea-Hypopnea Index in Obstructive Sleep","A Multisensor Deep Neural Framework Combining Digital Auscultation, Oxygen Saturation, and Motion Data to Estimate the Apnea-Hypopnea Index in Obstructive Sleep Apnea","Inclusion Criteria:\n\n* age 30-75 years\n* clinically suspected obstructive sleep apnea and scheduled for polysomnography\n* willing and able to provide written informed consent\n\nExclusion Criteria:\n\n* intolerance to the electronic stethoscope or fingertip pulse oximeter\n* significant structural airway abnormalities\n* arrhythmia\n* neuromuscular disorders\n* pregnancy\n* hospitalization within the past 1 month\n* inability to provide informed consent or requiring legal guardian consent","ALL","30 Years","75 Years",{"count":58,"type":59},150,"ESTIMATED","OBSERVATIONAL","This study aims to develop a multimodal deep learning model that integrates noninvasive signals to predict the severity of obstructive sleep apnea. By establishing a clinically viable and user-friendly monitoring tool, the study seeks to enhance early screening accessibility and support the development of home-based sleep care systems.",[63,64],"Obstructive Sleep Apnea (OSA)","Polysomnography",[66,67,68,11,69],"obstructive sleep apnea","polysomnography","ballistocardiography","oxygen saturation","2026-03-03",{"date":72,"type":73},"2026-03-05","ACTUAL",{"date":75,"type":73},"2025-09-05",{"date":77,"type":59},"2026-07-31",{"name":5,"class":6},1]