Expert system to facilitate source localization of brain electrical activity

• US 9,247,890 B2
• Filed: 10/31/2012
• Issued: 02/02/2016
• Est. Priority Date: 10/31/2011
• Status: Active Grant

• Current Assignee: Case Western Reserve University
• Original Assignee: Case Western Reserve University
• Inventors: Turnbull, John, Kaffashi, Farhad, Luders, Hans, Loparo, Ken, Lhatoo, Samden, Hamaneh, Mehdi
• Primary Examiner(s): BERHANU, ETSUB D
• Application Number:
  US13/665,323
• Publication Number:
  US 20130109996A1
• Time in Patent Office: 1,189 Days
• Field of Search: 600/544
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0035 adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
• CPC Class Codes: A61B 5/0042 for the brain
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7425 Displaying combinations of multiple images regardless of image source, e.g. displaying a reference anatomical image with a live image geometric transforms for image registration G06T3/14; enhancement using image fusion G06T5/50; algorithms for registration of images G06T7/30
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A system or method can facilitate source localization of brain electrical activity. In one example, an expert system can be utilized to evaluate the source localization results and, based on the acceptability of the results, adjust a data preparation phase to provide for acceptable source localization.

Claims

1. A system to localize a source of electrical activity in a patient'"'"'s body, the system comprising:

a non-transitory computer-readable medium to store instructions; and

a processor to facilitate execution of the instructions to at least;

preprocess electrical data corresponding to electrical signals acquired from a patient by using a spectral analysis function to determine frequency characteristics of the electrical data and a filter function to filter the electrical data;

represent the source of electrical activity with an inverse model;

represent geometry and electrical characteristics of a spatial region of interest in the patient'"'"'s body based on the inverse model with a forward model;

compute a location for the source of electrical activity within the spatial region of interest based on the preprocessed electrical data, the inverse model and the forward model;

evaluate an acceptability of the computed location for the source of electrical activity;

selectively adjust the filter function based on the frequency characteristics based on the evaluation of the acceptability of the computed location for the source of electrical activity;

re-compute the location for the source of electrical activity based on the selective adjustment; and

generate an output comprising the location for the source of electrical activity.

2. The system of claim 1, wherein the processor further facilitates the execution of the instructions to:

evaluate the acceptability of the computed location for the source of electrical activity based on predefined criteria; and

perform the selective adjustment automatically based on preprogrammed rules applied to results of the evaluation of the acceptability.

3. The system of claim 2, wherein the selective adjustment further comprises

adjusting the preprocessing automatically based on the rules;

and

choosing at least one of the inverse model and the forward model based on the rules.

4. The system of claim 2, wherein if the results of the evaluation of the acceptability are unacceptable, the processor further facilitates the execution of the instructions to selectively adjust at least one of the preprocessing component, the inverse model and the forward model for each subsequent location of the source of electrical activity.

5. The system of claim 1, wherein the processor further facilitates the execution of the instructions to:

estimate relative noise of a plurality of channels that provide the electrical signals;

remove the electrical data corresponding to noisy channels based on the relative noise;

selectively control a channel control function to remove the noisy channels from the electrical data based on the acceptability of the computed location for the source of electrical activity; and

re-compute the location for the source of electrical activity without electrical data corresponding to the noisy channels.

6. The system of claim 1, wherein the processor further facilitates the execution of the instructions to modify the forward model and provide a modified forward model based on the acceptability of the computed location for the source of electrical activity, and re-compute the location for the source of electrical activity based on the modified forward model.

7. The system of claim 1, wherein the processor further facilitates the execution of the instructions to modify the inverse model and provide a modified inverse model based on the acceptability of the computed location for the source of electrical activity, and re-compute the location for the source of electrical activity based on the modified inverse model.

8. The system of claim 1, wherein the processor further facilitates the execution of the instructions to:

separate artifacts from cerebral electrical activity;

detect a artifacts separated from the cerebral electrical activity by the component analysis function, the detected artifacts being removed from the electrical signals acquired from the patient to provide artifact-removed electrical data, and

re-compute the location for the source of electrical activity based on the artifact-removed electrical data.

9. The system of claim 1, wherein the processor further facilitates the execution of the instructions to select an interval corresponding to the electrical activity that is to be localized, and compute the location for the source of electrical activity based on the electrical data residing in the selected interval.

10. The system of claim 1, wherein the output represents the location for the source of electrical activity in a graphical representation of the patient'"'"'s body.

11. The system of claim 1, wherein the spatial region of interest and the source of electrical activity reside in the patient'"'"'s brain, and the electrical activity being localized corresponds to a spike in brain electrical activity.

12. A non-transitory computer-readable medium having instructions which, when executed, cause a processor to:

prepare brain electrical data acquired from a patient and geometry data, wherein the preparation of the brain electrical data includes using a spectral analysis function to determine frequency characteristics of the electrical data and filtering the electrical data acquired for the patient using a filter;

perform source localization based on the prepared brain electrical data and geometry data to determine a location of a source of electrical activity;

implement an expert system to evaluate an acceptability of the source localization and to adjust at least one of the preparation of the brain electrical data and the geometry data if the acceptability of the source localization is not within a predetermined acceptability level, wherein the expert system is implemented to adjust at least one parameter of the filter to provide an adjusted filter based on the frequency characteristics based on the acceptability of the source localization of the brain electrical data, and the source localization is re-performed based on modified prepared electrical data that is generated based on filtering using the adjusted filter;

store output data corresponding to the location of the source of electrical activity if the acceptability of the source localization is within the predetermined acceptability level; and

generate an output comprising the location for the source of electrical activity.

13. The computer-readable medium of claim 12, wherein the expert system is further programmed to cause noisy channels to be removed from the brain electrical data based on a relative noise analysis of input channels for the brain electrical data, the source localization being re-performed based on the prepared electrical data and geometry data with the noisy channels removed from the brain electrical data.

14. The computer-readable medium of claim 12, wherein the preparation of the brain electrical data employs a forward model, the expert system is further programmed to modify the forward model and provide a modified forward model based on the acceptability of the source localization, the source localization being re-performed based on the modified forward model.

15. The computer-readable medium of claim 12, wherein the preparation of the brain electrical data employs an inverse model, the expert system is further programmed to modify the inverse model and provide a modified inverse model based on the acceptability of the source localization, the source localization being re-performed based on the modified inverse model.

16. The computer-readable medium of claim 12, wherein the geometry data comprises image data for the patient that is registered with electrode location data determined for each of a plurality of electrodes.

17. The computer-readable medium of claim 16, wherein the instructions are further operative to select a temporal interval of electrical signals acquired by the plurality of electrodes, the temporal interval of electrical signals containing electrical activity to be localized, the source localization being performed to compute a location for a source of the electrical activity based on the prepared brain electrical data and geometry data, an inverse model and a forward model.

18. The computer-readable medium of claim 12, wherein the preparation of the brain electrical data further comprises instructions to:

perform component analysis on the brain electrical data to separate artifacts from brain electrical activity; and

detect the artifacts separated from the brain electrical activity, the detected artifacts being removed from the brain electrical data acquired from the patient to provide artifact-removed electrical data, the source localization being re-performed based on the artifact-removed electrical data and the geometry data.