Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24', 'removedCountries': ['Israel']}, 'conditionBrowseModule': {'meshes': [{'id': 'D012640', 'term': 'Seizures'}], 'ancestors': [{'id': 'D009461', 'term': 'Neurologic Manifestations'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'description': 'no Biospecimen'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 15}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2007-10'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2007-07', 'completionDateStruct': {'date': '2010-10', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2011-06-14', 'studyFirstSubmitDate': '2007-07-06', 'studyFirstSubmitQcDate': '2007-07-06', 'lastUpdatePostDateStruct': {'date': '2011-06-15', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2007-07-09', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2010-10', 'type': 'ACTUAL'}}, 'oversightModule': {'oversightHasDmc': True}, 'conditionsModule': {'keywords': ['motor seizures', 'accelerometer', 'algorithm', 'detection', 'alert'], 'conditions': ['Motor Seizures']}, 'descriptionModule': {'briefSummary': 'An accelerometer with transmitting ability is worn on the wrist. Data of movements during seizures will be analyzed to upgrade algorithm that will identify seizures.', 'detailedDescription': 'Patients undergoing Video-EEG telemetry will wear movement sensor on their wrist. The sensor will transmit continuous data to a laptop. Seizures\' data (tonic or clonic) will be analyzed and transformed into an algorithm (up-graded existing preliminary algorithm).\n\nIn the second phase the algorithm will need to identify seizure events within one minute of the onset.\n\nBoth specificity ("false positive") and sensitivity ("false negative) will be than calculated.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'maximumAge': '65 Years', 'minimumAge': '1 Day', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients admitted to Video-LTM Unit with motor seizures.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients undergoing Long Term Monitoring for motor seizures\n\nExclusion Criteria:\n\n* Invasive recording\n* Psychogenic seizures'}, 'identificationModule': {'nctId': 'NCT00497835', 'briefTitle': 'Study of Algorithm for Epilepsy Alert Device', 'organization': {'class': 'INDUSTRY', 'fullName': 'Biolert'}, 'officialTitle': 'Epilepsy Alert Device - Epilert Performance', 'orgStudyIdInfo': {'id': 'Biolert LTD'}}, 'contactsLocationsModule': {'overallOfficials': [{'name': 'Swetlana Kiperwasser, M.D.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Tel-Aviv Sourasky Medical Center'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Biolert', 'class': 'INDUSTRY'}, 'responsibleParty': {'oldNameTitle': 'Prof. Uri Kramer. Chief scientist', 'oldOrganization': 'Biolert LTD'}}}}