Ignite Creation Date:
2025-12-24 @ 9:08 PM
Ignite Modification Date:
2025-12-25 @ 6:59 PM
Study NCT ID:
NCT04755504
Status:
COMPLETED
Last Update Posted:
2024-07-03
First Post:
2021-02-08
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
The Development of an Algorithm to Detect Sleep Structure With a Wearable EEG Monitor in an Elderly Population
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP', 'interventionModelDescription': 'Each patient will be evaluated with routine polysomnography and additionally 2 EEG signals will be recorded behind each air.'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 100}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2021-01-21', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-07', 'completionDateStruct': {'date': '2023-01-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-07-02', 'studyFirstSubmitDate': '2021-02-08', 'studyFirstSubmitQcDate': '2021-02-15', 'lastUpdatePostDateStruct': {'date': '2024-07-03', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-02-16', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-01-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Sleep algorithm', 'timeFrame': '1 night', 'description': 'To develop an algorithm to characterize sleep architecture based on EEG measurement by 2 electrodes behind each ear.\n\nTo classify the sleep stages, a deep learning algorithm will be used. The algorithm will learn a complex function, transforming an input to an output, based on several examples. In this specific case, the input are 30s EEG epochs and the output are sleep stages. To classify the measured signal in the correct sleep stage, the deep learning algorithm will learn to extract useful features from the data.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Sleep']}, 'descriptionModule': {'briefSummary': 'To evaluate whether it is able to perform sleep staging with EEG data recorded from 2 electrodes behind each ear.', 'detailedDescription': 'The Sensor Dot wearable device measures electroencephalography (EEG). It records from 2 electrodes behind each ear. The device was designed as a wearable for seizure detection in epilepsy patients. The purpose of this study is to test its ability to capture the information necessary for sleep monitoring in elderly patients. Trained electrophysiologists are unable to stage sleep on data from novel wearable devices, since AASM sleep scoring rules are only defined for standardized recording positions on the head. Therefore, we need an automated algorithm to perform sleep staging with data from the Sensor Dot device. We will train this algorithm using manual annotations made with the polysomnography simultaneously acquired with the wearable EEG.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '60 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Subjects planned to undergo a diagnostic polysomnography\n* \\> 60y old\n\nExclusion Criteria:\n\n* Patients unable to provide informed consent'}, 'identificationModule': {'nctId': 'NCT04755504', 'briefTitle': 'The Development of an Algorithm to Detect Sleep Structure With a Wearable EEG Monitor in an Elderly Population', 'organization': {'class': 'OTHER', 'fullName': 'Universitaire Ziekenhuizen KU Leuven'}, 'officialTitle': 'The Development of an Algorithm to Detect Sleep Structure With a Wearable EEG Monitor in an Elderly Population', 'orgStudyIdInfo': {'id': 'S64190'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'EEG evaluation', 'description': 'All patients will be evaluated during 1 night by standard polysomnography and additionally EEG will be evaluated by 2 electrodes behind each ear connected to a recording device (Sensor Dot)', 'interventionNames': ['Diagnostic Test: EEG behind the ear']}], 'interventions': [{'name': 'EEG behind the ear', 'type': 'DIAGNOSTIC_TEST', 'description': '2 additional electrodes behind each ear will record EEG', 'armGroupLabels': ['EEG evaluation']}]}, 'contactsLocationsModule': {'locations': [{'zip': '3000', 'city': 'Leuven', 'country': 'Belgium', 'facility': 'UZ Leuven', 'geoPoint': {'lat': 50.87959, 'lon': 4.70093}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Universitaire Ziekenhuizen KU Leuven', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}