Evaluation of Cognitive State in Senior Subjects Using Neurosteer EEG System

NCT ID: NCT04683835

Last Updated: 2023-11-13

Study Results

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Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

80 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-10-15

Study Completion Date

2021-10-01

Brief Summary

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This is an observational study. Patients who fulfill all inclusion criteria and none of the exclusion criteria will be enrolled in the study, be neurologically evaluated and will go through EEG recordings while listening to an auditory cognitive assessment tool. EEG recordings will be analyzed using proprietary computational analyses.

Detailed Description

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One of the major problems in the prevention and treatment of neurological disorders, is the lack of cost effective and reliable tools to assess neurodegeneration on a large scale at a very early stage. Although current imaging methods give a clear image of the brain atrophy involved in neurodegenerative disorders, there are deficiencies prohibiting their usage for prevention-scanning of large high-risk population such as high price, long set-up time and the need for trained personnel to conduct the test. Therefore, the development of a reliable tool to assess brain neurodegeneration, associated with cognitive decline independent of personal interpretation and/or variance between clinicians and between medical facilities would be highly valuable. This tool would allow the healthcare team to make appropriate treatment decisions that could aid in neurodegenerative disease prevention.

The Neurosteer system provides objective neurological biomarkers using a wearable easy-to-use affordable system. The system facilitate the capture and interpretation of EEG data with only a single patch of electrodes, attached on the subject's forehead. Neurosteer examination includes completing auditory tasks while measuring brain activity with the device. The data is analyzed using machine learning methods to produce biomarkers, enabling a report of the patient's activity in real time and offline. The examination is easy to preform and can be conducted in every clinic or in patients' homes.

In this study, clinical staff will identify potential subjects and will examine the eligibility of subject according to inclusion and exclusion criteria. Research staff will inform the patient on study's objective and design. Patients will sign the Informed Consent Form (ICF). Research staff will set up an initial session using the Neurosteer system. In this session the patient will perform auditory cognitive assessment tasks. The patient will be re-examined in the same experimental setting over the next 7 days and at least 1 day later. Level of cognition will be assessed by the Neurosteer technology.

Conditions

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Mild Cognitive Impairment

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients

Patients who are assessed by the clinical staff using Mini-Mental State Exam (MMSE)

Neurosteer Aurora system

Intervention Type DEVICE

The system is composed of hardware and software modules that facilitate the capture and interpretation of electrophysiological data as well as enable viewing the processed data in real time and offline. An electrode patch is attached on the subject's forehead to capture the electrophysiological signal. The signal is sent via low energy Bluetooth to an EEG Monitor. The signal is then sent via Wi-Fi to the cloud where the data is stored on a HIPAA compliant server. Data analysis performed in the cloud transforms the electrophysiological signal into easily readable data of brain activity, which is accessible via any web interface

Interventions

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Neurosteer Aurora system

The system is composed of hardware and software modules that facilitate the capture and interpretation of electrophysiological data as well as enable viewing the processed data in real time and offline. An electrode patch is attached on the subject's forehead to capture the electrophysiological signal. The signal is sent via low energy Bluetooth to an EEG Monitor. The signal is then sent via Wi-Fi to the cloud where the data is stored on a HIPAA compliant server. Data analysis performed in the cloud transforms the electrophysiological signal into easily readable data of brain activity, which is accessible via any web interface

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Men and women over the age of 50.
* MMSE ≥ 24.
* Patient is able to collaborate.
* No other cognitive comorbidity.
* No seizure events.

Exclusion Criteria

* MMSE \< 24.
* Any verbal or non-verbal form of objection from patient or form patient's family member or significant other.
* Presence of several cognitive comorbidity.
* Damage to integrity of scalp and/or skull.
* Skin irritation in the facial and forehead area.
* Significant hearing impairments.
* History of drug abuse.
Minimum Eligible Age

50 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Neurosteer Ltd.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Ady Sasson, Dr.

Role: PRINCIPAL_INVESTIGATOR

Dorot, Geriatric Medical Center

Locations

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Dorot - Netanya Geriatric Medical Center

Netanya, , Israel

Site Status

Countries

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Israel

References

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Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. doi: 10.1016/0022-3956(75)90026-6. No abstract available.

Reference Type BACKGROUND
PMID: 1202204 (View on PubMed)

Guerrero-Berroa E, Luo X, Schmeidler J, Rapp MA, Dahlman K, Grossman HT, Haroutunian V, Beeri MS. The MMSE orientation for time domain is a strong predictor of subsequent cognitive decline in the elderly. Int J Geriatr Psychiatry. 2009 Dec;24(12):1429-37. doi: 10.1002/gps.2282.

Reference Type BACKGROUND
PMID: 19382130 (View on PubMed)

Meir-Hasson Y, Kinreich S, Podlipsky I, Hendler T, Intrator N. An EEG Finger-Print of fMRI deep regional activation. Neuroimage. 2014 Nov 15;102 Pt 1:128-41. doi: 10.1016/j.neuroimage.2013.11.004. Epub 2013 Nov 15.

Reference Type BACKGROUND
PMID: 24246494 (View on PubMed)

Meir-Hasson Y, Keynan JN, Kinreich S, Jackont G, Cohen A, Podlipsky-Klovatch I, Hendler T, Intrator N. One-Class FMRI-Inspired EEG Model for Self-Regulation Training. PLoS One. 2016 May 10;11(5):e0154968. doi: 10.1371/journal.pone.0154968. eCollection 2016.

Reference Type BACKGROUND
PMID: 27163677 (View on PubMed)

Goldway N, Ablin J, Lubin O, Zamir Y, Keynan JN, Or-Borichev A, Cavazza M, Charles F, Intrator N, Brill S, Ben-Simon E, Sharon H, Hendler T. Volitional limbic neuromodulation exerts a beneficial clinical effect on Fibromyalgia. Neuroimage. 2019 Feb 1;186:758-770. doi: 10.1016/j.neuroimage.2018.11.001. Epub 2018 Nov 5.

Reference Type BACKGROUND
PMID: 30408596 (View on PubMed)

Keynan JN, Cohen A, Jackont G, Green N, Goldway N, Davidov A, Meir-Hasson Y, Raz G, Intrator N, Fruchter E, Ginat K, Laska E, Cavazza M, Hendler T. Electrical fingerprint of the amygdala guides neurofeedback training for stress resilience. Nat Hum Behav. 2019 Jan;3(1):63-73. doi: 10.1038/s41562-018-0484-3. Epub 2018 Dec 10.

Reference Type BACKGROUND
PMID: 30932053 (View on PubMed)

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

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092020

Identifier Type: -

Identifier Source: org_study_id

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