Online source reconstruction for eeg/meg and ecg/mcg

Abstract

In one embodiment, the present invention includes an EEG system comprising of sensors which are utilized to gather an electromagnetic signal from a patient; a signal processing system; and a computer system. The computer system is configured to support multiple threads of execution. The computer system initiates a first thread of execution, a measurement module, where the data is filtered and in some cases averaged. Typically, the data is filtered for a particular latency period. Once the data has been filtered and averaged, the result is given to a second thread of execution, the source reconstruction module, which then proceeds to generate a source reconstruction for the trial. The measurement module then acquires and processes new electromagnetic data from a new trial while the source reconstruction is being performed on the most recent trial.

1 . A method comprising:
 acquiring a first electromagnetic physiological signal;   filtering the signal for a latency range;   performing a source reconstruction for the signal; and   acquiring a second electromagnetic physiological signal while the source reconstruction is being performed on the first electromagnetic signal.   
     
     
         2 . The method of  claim 1 , wherein the step of performing the source reconstruction includes computing a single equivalent current dipole. 
     
     
         3 . The method of  claim 1 , wherein the step of performing the source reconstruction includes computing a moving dipole. 
     
     
         4 . The method of  claim 1 , wherein the step of performing the source reconstruction includes computing a rotating dipole. 
     
     
         5 . The method of  claim 1 , wherein the step of performing the source reconstruction includes computing a regional dipole. 
     
     
         6 . The method of  claim 1 , wherein the step of performing the source reconstruction includes computing a fixed dipole. 
     
     
         7 . The method of  claim 1 , wherein the step of performing the source reconstruction includes using a concentric sphere volume conductor model. 
     
     
         8 . The method of  claim 1 , wherein the step of performing the source reconstruction includes using a Boundary Element Method (BEM) volume conductor model. 
     
     
         9 . The method of  claim 1 , wherein the step of performing the source reconstruction includes using a Finite Element Method (FEM) model. 
     
     
         10 . The method of  claim 1 , and further comprising the step of averaging the filtered data. 
     
     
         11 . The method of  claim 1 , and further comprising the step of applying a dipole onto an anatomical image. 
     
     
         12 . The method of claims, and further comprising creating a scatter plot of dipole locations. 
     
     
         13 . The method of  claim 1 , and further comprising a signal to noise analysis of the required neurophysiological data. 
     
     
         14 . An apparatus comprising:
 a sensor for acquiring an electromagnetic physiological signal;   a signal processing circuit in communication with the sensor; and   a processor in communication with the signal processing circuit and configured to support multiple threads of execution with one thread being a measurement module and a second thread being a source reconstruction module.   
     
     
         15 . The apparatus of  claim 14 , and further comprising a display showing source reconstruction results overlayed onto anatomical data. 
     
     
         16 . The apparatus of  claim 14 , wherein the sensor acquires MEG data. 
     
     
         17 . The apparatus of  claim 14 , wherein the sensor acquires EEG data. 
     
     
         18 . The apparatus of  claim 14 , wherein the sensor acquires ECG data. 
     
     
         19 . The apparatus of  claim 14 , wherein the sensor acquires MCG data. 
     
     
         20 . A method of testing comprising:
 acquiring an electromagnetic physiological signal through a test setup;   determining the latency of the signal;   performing a source reconstruction of the data within a predetermined latency range; and   using the source reconstruction to modify the test setup.