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

November 10, 2020 updated by: University of Aarhus
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 Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Actual)

20

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Aarhus, Denmark, 8000
        • Aarhus University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 50 years (Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Device Feasibility
  • Allocation: Non-Randomized
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: 4 nights with PSG
For all subjects: 4 nights with polysomnography and ear-EEG
soft silicone electrode array placed in each ear (outer ear-canal and concha), connected to a battery powered EEG amplifier.
Other: 12 nights with ear-EEG

For a subset of the subjects in arm the '4 nights with PSG', a second phase follows in which each subject sleeps 12 nights with only ear-EEG.

If a night's recording is unsuccessful, for whatever reason, up to 6 additional nights may be attempted.

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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Cohens kappa
Time Frame: At study completion (average of 6 months)

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.

At study completion (average of 6 months)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Collaborators

Investigators

  • Principal Investigator: Preben Kidmose, Professor, University of Aarhus

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 23, 2018

Primary Completion (Actual)

November 9, 2020

Study Completion (Actual)

November 9, 2020

Study Registration Dates

First Submitted

March 16, 2018

First Submitted That Met QC Criteria

July 12, 2018

First Posted (Actual)

July 13, 2018

Study Record Updates

Last Update Posted (Actual)

November 12, 2020

Last Update Submitted That Met QC Criteria

November 10, 2020

Last Verified

May 1, 2019

More Information

Terms related to this study

Other Study ID Numbers

  • EarEEGSleep2018

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

After publication of results, anonymized recordings will be made available to the scientific community.

IPD Sharing Time Frame

We anticipate that data will be made available at some point in 2019.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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