The Development of an Algorithm to Detect Sleep Structure With a Wearable EEG Monitor in an Elderly Population
The Development of an Algorithm to Detect Sleep Structure With a Wearable EEG Monitor in an Elderly Population
To evaluate whether it is able to perform sleep staging with EEG data recorded from 2 electrodes behind each ear.
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.
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