Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 50}}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2016-05'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2016-06', 'completionDateStruct': {'date': '2017-05', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2016-06-06', 'studyFirstSubmitDate': '2016-05-26', 'studyFirstSubmitQcDate': '2016-05-26', 'lastUpdatePostDateStruct': {'date': '2016-06-08', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2016-06-01', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2017-05', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Time invariant components of EEG signals', 'timeFrame': 'One month'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['electroencephalogram (EEG),Human brain,Brain-Computer Interface'], 'conditions': ['EEG Data Analysis', 'Healthy Subjects']}, 'descriptionModule': {'briefSummary': "This study aims to identify various time-variant and time-invariant components of EEG signals using advanced signal processing techniques, such as machine learning. The investigators' ultimate goal is to develop universal or customised brain-computer interface that are stable across days or even years."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '40 Years', 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Healthy volunteers that understands Mandarin instructions.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Exclusion criteria:\n\n1. Severe vision disorders which prevent volunteers to recognize instructions on the screen\n2. Severe psychiatric disorders\n3. Severe sleep disorders which keep volunteers awake for two hours\n4. Volunteers with claustrophobia\n5. Patients who underwent stroke and brain surgery\n6. Patients with neuromuscular diseases'}, 'identificationModule': {'nctId': 'NCT02787200', 'briefTitle': 'Identification of Time-invariant EEG Signals for Brain-Computer Interface', 'organization': {'class': 'OTHER', 'fullName': 'National Taiwan University Hospital'}, 'officialTitle': 'Identification of Time-invariant EEG Signals for Brain-Computer Interface', 'orgStudyIdInfo': {'id': '201604024RIND'}}, 'contactsLocationsModule': {'locations': [{'zip': '10002', 'city': 'Taipei', 'state': 'Taipei', 'status': 'RECRUITING', 'country': 'Taiwan', 'contacts': [{'name': 'Tsung-Ren Huang', 'role': 'CONTACT', 'email': 'trhuang@ntu.edu.tw', 'phone': '886-2-3366-3104'}], 'facility': 'National Taiwan University Hospital'}], 'centralContacts': [{'name': 'Tsung-Ren Huang', 'role': 'CONTACT', 'email': 'trhuang@ntu.edu.tw', 'phone': '886-23366-3104'}, {'name': 'Meng-Huan Wu', 'role': 'CONTACT', 'email': 'mhjasonwu@gmail.com', 'phone': '886-3-3250462'}], 'overallOfficials': [{'name': 'Tsung-Ren Huang', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'National Taiwan University'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National Taiwan University Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}