Evaluation of the COGNISION(TM) System as an Event-related Potential (ERP) Collection System.

This study has been completed.
Sponsor:
Collaborator:
University of Kentucky
Information provided by:
Neuronetrix, Inc.
ClinicalTrials.gov Identifier:
NCT00582127
First received: December 19, 2007
Last updated: December 22, 2010
Last verified: December 2010

December 19, 2007
December 22, 2010
January 2008
November 2010   (final data collection date for primary outcome measure)
Signal to noise ratio (SNR) of ERPs [ Time Frame: 9 months ] [ Designated as safety issue: No ]
Complete ERP tests along with automated classifier training with all subjects. [ Time Frame: 9 months ] [ Designated as safety issue: No ]
Complete list of historical versions of study NCT00582127 on ClinicalTrials.gov Archive Site
Patient tolerance of the COGNISION(TM) system. [ Time Frame: 9 months ] [ Designated as safety issue: No ]
To perform statistically significant classifications for the 2 cohorts. [ Time Frame: 9 months ] [ Designated as safety issue: No ]
Not Provided
Not Provided
 
Evaluation of the COGNISION(TM) System as an Event-related Potential (ERP) Collection System.
Evaluation of a Handheld Evoked Response Potentials (ERP) System as an Effective Method to Diagnose Alzheimer's Disease

This study will evaluate a handheld event-related potential (ERP) testing device from Neuronetrix, Inc. as a method to collect ERP data in an outpatient setting.

An ERP system records electrical signals at the scalp that are produced by the brain when performing cognitive tasks. By doing this study, we hope to evaluate various performance parameters of the COGNISION(TM) system.

Patients who have a current diagnosis of mild-moderate dementia and suspected of having Alzheimer's disease (AD) along with cognitively normal age-matched controls will be recruited for this study. The Alzheimer's subjects either will have had a complete clinical and neuropsychiatric workup or will have those tests performed during the study.

Both groups, AD and controls will be asked to listen to a series of sounds and press a button on a handheld control box when a target sound is heard. The COGNISION(TM) headset on each subject's head will then record the electrical signals during this task.

Four important features of the COGNISION(TM) will be investigated:

  1. Patient tolerance
  2. Ease of use
  3. Data quality
  4. Network architecture
Observational
Observational Model: Case Control
Time Perspective: Cross-Sectional
Not Provided
Not Provided
Non-Probability Sample

Patients and family from the University of Kentucky Sanders Brown Center for Aging

Alzheimer's Disease
Not Provided
  • 1
    Mild-moderate Alzheimer's Disease
  • 2
    Age-matched Controls
Polikar R, Topalis A, Green D, Kounios J, Clark CM. Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease. Comput Biol Med. 2007 Apr;37(4):542-58. Epub 2006 Sep 20.

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Completed
50
November 2010
November 2010   (final data collection date for primary outcome measure)

Inclusion Criteria for AD:

  • Age 60 to 85
  • Mild to moderate diagnosis of Alzhiemer's disease

Inclusion Criteria for Control:

  • Age 60 to 85
  • Cognitively healthy with no complaints

Exclusion Criteria:

  • Subjects with advanced AD and severe impairment (CDR > 2, MMSE less than 15)
  • Neurological disorders such as stroke, Parkinson's disease, Huntington's disease, multiple sclerosis, brain tumor, delirium, or psychiatric disorder other than depression (e.g. schizophrenia)
  • Subjects with life threatening illnesses and subjects with significant hearing or visual impairments
  • Subjects with a current prescription for psychoactive pharmaceuticals
Both
60 Years to 85 Years
Yes
Contact information is only displayed when the study is recruiting subjects
United States
 
NCT00582127
VAL-UK-01
No
Charles D. Smith, M.D., University of Kentucky
Neuronetrix, Inc.
University of Kentucky
Principal Investigator: Charles D Smith, M.D. University of Kentucky
Neuronetrix, Inc.
December 2010

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP