INVESTIGATING NEUROLOGICAL FUNCTION

• US 20090318825A1
• Filed: 07/09/2007
• Published: 12/24/2009
• Est. Priority Date: 07/07/2006
• Status: Abandoned Application

• Current Assignee: Diagnostic Potentials Limited
• Original Assignee: Diagnostic Potentials Limited
• Inventors: Kilborn, Kerry
• Application Number:
  US12/307,804
• Publication Number:
  US 20090318825A1
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/378 Visual stimuli
• CPC Class Codes: A61B 5/4088 Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia

Abstract

This invention relates to a method and apparatus for identifying degenerative disorders and particularly to the early and accurate diagnosis of Alzheimer'"'"'s Disease.

Claims

1. A method for diagnosing a neurological disorder which comprises:

a cognitive task;

collecting electroencephalogram (EEG) signals from a person conducting said cognitive task;

and conducting an analysis of said EEG signals to form an algorithm which is capable of being used to determine if the person conducting the cognitive task has a neurological disorder.

2. The method according to claim 1, wherein signals relevant to diagnosis of the neurological disorder are taken from the hippocampus region.

3. A method according to claim 1, wherein the neurological disorder is Alzheimer'"'"'s Disease.

4. A method according to claim 1, wherein the method provides early and accurate detection of Alzheimer'"'"'s Disease.

5. A method according to claim 1, wherein the cognitive task is a cognitive probe task which is computerised and is a two-part choice task in which patients are asked to decide whether each test stimulus has been presented before or not.

6. A method according to claim 5, wherein the stimuli consist of coloured line drawings in combination with clearly spoken words.

7. A method according to claim 1, wherein the cognitive task provides stimulus pairs consisting of a picture and a spoken word.

8. A method according to claim 7, wherein pre-determined stimulus pairs are presented at least once again in a short time interval or a long time interval and a patient decides whether the image and spoken word has been presented for the first time or has been presented before.

9. A method according to claim 1 wherein the EEG data is obtained from a multichannel EEG apparatus.

10. A method according to claim 1, wherein a dense array EEG apparatus is applied in the form of a geodesic sensor net over a patient'"'"'s head.

11. A method according to claim 10, wherein the dense array EEG detects a patient'"'"'s brain electrical activity for each stimulus of an image and a spoken word.

12. A method according to claim 9, wherein the collected signals of EEG are detected in the form of event-related potentials (ERPs).

13. A method according to claim 9, wherein an EEG collecting apparatus is a 64-channel, 128-channel or 256 channel system design.

14. A method according to claim 13, wherein specific channels of the EEG collecting apparatus are utilised to provide improved results such as channels 17, 18, 22 and 23 of a 128 channel sensor as shown in FIG. 2, or similar regions from other sensor arrays which show a large and reliable difference which serves as a clinically useful electrophysiological marker which differentiates between healthy controls and patients diagnosed with Alzheimer'"'"'s Disease.

15. A method according to claim 1, wherein particular channels in an EEG collecting apparatus are selected to collate EEG data.

16. A method according to claim 1, wherein a mean event-related potential is chosen over which data is measured to determine if a patient has a neurological disorder such as Alzheimer'"'"'s Disease.

17. A method according to claim 1, wherein obtained data is formatted into an algorithm which is plotted on a graph of behavioural measure obtained from signal detection theory against mean event-related potentials.

18. A method according to claim 17, wherein the algorithm is in the form of a sloped straight line whereupon on one side of the line substantially all persons have, for example, Alzheimer'"'"'s Disease and on the other side substantially all of the persons have no neurological disease such as Alzheimer'"'"'s Disease.

19. A method according to claim 17, wherein the algorithm for Alzheimer'"'"'s Disease has an estimated logit of:

5.78−

1.88×

Memory d′

−

0.41×

Mean Event-Related Potential>

0.

20-21. -21. (canceled)

22. Apparatus for diagnosing a neurological disorder comprising:

computerised means for displaying a visual stimulus and means for emitting an audible signal;

a response box comprising two input buttons, such as a ‘

new’ and

‘

old’

button; and

an apparatus capable of obtaining an EEG from a subject.

23. The apparatus according to claim 22, wherein the apparatus capable of obtaining an EEG from a subject is in the form of a multichannel sensor array designed to be worn over the head comprising sensors for detecting brain signals all over the head and in particular from the hippocampus region.