Evaluation of the Ear-EEG System for Sleep Monitoring in Healthy Subjects

University of Aarhus20 enrolled

Overview

Subjects sleep multiple nights in their own home, wearing actigraph, PSG (PolySomnoGraphy) and ear-EEG sensors. The object of the study is to determine the applicability of ear-EEG for sleep monitoring.

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

DEVICE_FEASIBILITY

Masking

NONE

Enrollment

Conditions

Sleep Monitoring

Interventions

ear-EEGDEVICE

soft silicone electrode array placed in each ear (outer ear-canal and concha), connected to a battery powered EEG amplifier.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 50 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: Informed consent obtained and letter of authority signed before any study related activities Age 18-50 years \- Exclusion Criteria: 1. BMI (body mass index) \> 30 2. Previous stroke or cerebral haemorrhage and any other structural cerebral disease 3. Known or suspected abuse of alcohol or any other neuro-active substance 4. Use of hearing aid or cochlear implants 5. Allergic contact dermatitis caused by metals or generally prone to skin irritation 6. Narrow or malformed ear canals 7. Obstructive sleep apnea 8. History of sleep disorders or neurological diseases 9. Chronic pain 10. People judged incapable, by the investigator, of understanding the participant instruction or who are not capable of carrying through the investigation. 11. Use of medication known to influence the user's sleep (antidepressants, sedatives, antipsychotic-, and pain relieving medication) 12. Teeth grinding (bruxism) 13. Pregnancy

Locations (1)

Aarhus University

Aarhus, Denmark

Outcomes

Primary Outcomes

Cohens kappa

The test outcome is a set of matched polysomnography and ear-EEG sleep measurements. From this will be generated an algorithm for automatic sleep scoring based on ear-EEG (using leave-one-subject-out cross validation). The primary outcome measure of the test is the correlation between the automatically generated hypnograms and those generated manually from the scalp recordings. The accuracy is quantified using Cohen's kappa, which is a number between -1 and 1. An average (across all recordings) above 0.4 would be a success for the test. As the training of the sleep scoring algorithm requires large amounts of data, it is necessary to use a large number of subjects (20) to estimate the viability of automatic sleep scoring from ear-EEG recordings. This also means that kappa values are calculated for all recordings at once when the measurements are done. This method for creating sleep scoring algorithms and quantifying their success is in line with standard procedure in this field.

Time frame: At study completion (average of 6 months)

Data from ClinicalTrials.gov

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