System and method for EEG imaging of cerebral activity using small electrode sets

• US 7,809,434 B2
• Filed: 12/05/2005
• Issued: 10/05/2010
• Est. Priority Date: 12/03/2004
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Nellcor Puritan Bennett LLC (Medtronic Plc)
• Inventors: Greenwald, Scott D., Kofol, Tim, Devlin, Philip H.
• Primary Examiner(s): Nasser; Robert L
• Assistant Examiner(s): D'ANGELO, MICHAEL J
• Application Number:
  US11/294,321
• Publication Number:
  US 20060149160A1
• Time in Patent Office: 1,765 Days
• Field of Search: 600/544, 600/545
• US Class Current: 600/544
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16

Abstract

The invention provides a method of estimating cerebral sources of electrical activity from a small subset of EEG channels utilizing existing methods to provide a 3-dimensional, discrete, distributed, linear solution to the inverse problem using inputs consisting of a small number of EEG channels (e.g., 4 channels) augmented with synthetic EEG data for the other channels. The resultant image of cerebral electrical activity in the region of the EEG channels from which data is recorded is of comparable spatial resolution in the corresponding region to images of cerebral electrical activity obtained using a complete set of EEG channels (e.g., using 24 channels).

Claims

1. A method of estimating cerebral sources of electrical activity from a set of EEG channels comprising the steps of:

obtaining M channels of measured EEG signal data and N−

M channels of synthetic EEG signal data, where M<

N;

creating sets of N−

M channels of synthetic EEG signal data; and

calculating, using a processor, an inverse solution from a combination of said sets of N−

M channels of EEG signal data and said M channels of EEG signal data.

2. The method of estimating cerebral sources of electrical activity of claim 1 further comprising the step of calculating a final inverse solution by repeating said step of calculating an inverse solution from a combination of said sets of N−

M channels of synthetic EEG signal data and said M channels of measured EEG signal data.

3. The method of estimating cerebral sources of electrical activity of claim 1 further comprising the step of combining said M channels of measured EEG signal data with said sets of N−

M channels of synthetic EEG signal data.

4. The method of estimating cerebral sources of electrical activity of claim 3 wherein said step of combining comprises the steps of:

time shifting said sets of N−

M channels of synthetic EEG signal data to maximize the overall correlation between said M channels of measured EEG signal data and said N−

M channels of synthetic EEG signal data; and

correlating each of said M channels of measured EEG signal data and each of said N−

M channels of synthetic EEG signal data.

5. The method of estimating cerebral sources of electrical activity of claim 1 further comprising 4 channels of measured EEG signal data and 20 channels of synthetic EEG signal data.

6. The method of estimating cerebral sources of electrical activity of claim 1 further comprising generating an image of cerebral electrical activity in a brain region based at least in part on the inverse solution.

7. The method of estimating cerebral sources of electrical activity of claim 1 wherein creating sets of N−

M channels of synthetic EEG signal data comprises accessing a database of previously collected EEG signal.

8. A method of estimating cerebral sources of electrical activity from a set of EEG channels comprising the steps of:

obtaining M channels of measured EEG signal data and N−

M channels of synthetic EEG signal data, where M<

N;

creating sets of N−

M channels of synthetic EEG signal data;

calculating an inverse solution from a combination of said sets of N−

M channels of EEG signal data and said M channels of EEG signal data; and

generating an image of cerebral electrical activity in a brain region based at least in part on the inverse solution.

9. The method of estimating cerebral sources of electrical activity of claim 8 further comprising the step of calculating a final inverse solution by repeating said step of calculating an inverse solution from a combination of said sets of N−

M channels of synthetic EEG signal data and said M channels of measured EEG signal data.

10. The method of estimating cerebral sources of electrical activity of claim 8 further comprising the step of combining said M channels of measured EEG signal data with said sets of N−

M channels of synthetic EEG signal data.

11. The method of estimating cerebral sources of electrical activity of claim 10 wherein said step of combining comprises the steps of:

time shifting said sets of N−

M channels of synthetic EEG signal data to maximize the overall correlation between said M channels of measured EEG signal data and said N−

M channels of synthetic EEG signal data; and

correlating each of said M channels of measured EEG signal data and each of said N−

M channels of synthetic EEG signal data.

12. The method of estimating cerebral sources of electrical activity of claim 8 further comprising 4 channels of measured EEG signal data and 20 channels of synthetic EEG signal data.

13. The method of estimating cerebral sources of electrical activity of claim 8 wherein creating sets of N−

M channels of synthetic EEG signal data comprises accessing a database of previously collected EEG signal data.

14. A system for estimating cerebral sources of electrical activity from a set of EEG channel, the system comprising:

EEG sensors capable of obtaining M channels of measured EEG signal data and N−

M channels of synthetic EEG signal data, where M<

N;

A processor capable of;

creating sets of N−

M channels of synthetic EEG signal data; and

calculating an inverse solution from a combination of said sets of N−

M channels of EEG signal data and said M channels of EEG signal data.

15. The system of claim 14 further capable of calculating a final inverse solution by repeating said step of calculating an inverse solution from a combination of said sets of N−

M channels of synthetic EEG signal data and said M channels of measured EEG signal data.

16. The system of claim 14 further capable of combining said M channels of measured EEG signal data with said sets of N−

M channels of synthetic EEG signal data.

17. The system of claim 16 further capable of:

time shifting said sets of N−

M channels of synthetic EEG signal data to maximize the overall correlation between said M channels of measured EEG signal data and said N−

M channels of synthetic EEG signal data; and

correlating each of said M channels of measured EEG signal data and each of said N−

M channels of synthetic EEG signal data.

18. The system of claim 14 further comprising 4 channels of measured EEG signal data and 20 channels of synthetic EEG signal data.

19. The system of claim 14 further comprising a display capable of displaying an image of cerebral electrical activity in a brain region based at least in part on the inverse solution.

20. The system of claim 14 further capable of accessing a database of previously collected EEG signal to create the sets of N−

M channels of synthetic EEG signal data.