The Development of an Algorithm to Detect Sleep Structure With a Wearable EEG Monitor in an Elderly Population

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

100 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-01-21

Study Completion Date

2023-01-30

Brief Summary

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To evaluate whether it is able to perform sleep staging with EEG data recorded from 2 electrodes behind each ear.

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Detailed Description

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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.

Conditions

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Sleep

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Each patient will be evaluated with routine polysomnography and additionally 2 EEG signals will be recorded behind each air.

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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EEG evaluation

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)

Group Type EXPERIMENTAL