Medical devices for mapping cardiac tissue

Abstract

Medical devices and methods for making and using medical devices are disclosed. A method of mapping electrical activity of a heart may comprise sensing a plurality of signals with a plurality of electrodes positioned within the heart. The method may further comprise separating the plurality of signals into a first group of signals and a second group of signals, and generating a data set that includes at least one known data point and one or more unknown data points. In some examples, the at least one known data point is generated based on the first group of signals.

What is claimed is: 
     
         1 . A method of mapping electrical activity of a heart, the method comprising:
 receiving a plurality of signals sensed by a plurality of electrodes positioned within the heart;   separating the plurality of signals into a first group of signals and a second group of signals, wherein the first group of signals includes a characteristic signal; and   generating a data set that includes at least one known data point and one or more unknown data points, wherein the at least one known data point is generated using the first group of signals and the one or more unknown data points are generated using the second group of signals.   
     
     
         2 . The method of  claim 1 , further comprising identifying the characteristic signal. 
     
     
         3 . The method of  claim 1 , further comprising reducing or removing one or more features of the plurality of electrograms. 
     
     
         4 . The method of  claim 3 , wherein reducing or removing one or more features of the plurality of signals comprises performing at least one of the following on the plurality of signals:
 performing a wavelet transform on the plurality of signals;   rectifying the plurality of signals; and   low-pass filtering the plurality of signals.   
     
     
         5 . The method of  claim 4 , wherein the wavelet transform is a Haar wavelet transform. 
     
     
         6 . The method of  claim 1 , wherein separating the plurality of signals into a first group of signals and a second group of signals comprises performing statistical analysis on the plurality of signals. 
     
     
         7 . The method of  claim 6 , wherein performing statistical analysis of the plurality of signals comprises clustering the results of the statistical analysis, wherein the clustering produces the first group of signals and the second group of signals. 
     
     
         8 . The method of  claim 7 , wherein clustering the results of the statistical analysis comprises one of:
 performing a distribution-based clustering of the results of the statistical analysis; or   performing a density-based clustering of the results of the statistical analysis.   
     
     
         9 . The method of  claim 8 , wherein performing a distribution-based clustering of the results of the statistical analysis comprises performing a Gaussian mixture model analysis of the results of the statistical analysis. 
     
     
         10 . The method of  claim 6 , wherein the statistical analysis comprises principal component analysis. 
     
     
         11 . A medical system for mapping electrical activity of a heart, the system comprising:
 a catheter comprising a catheter shaft and a plurality of electrodes coupled to the catheter shaft, wherein each of the plurality of electrodes are configured to sense physiological signals; and   a processor communicatively coupled to the plurality of electrodes, wherein the processor is configured to:
 receive a plurality of signals sensed by a plurality of electrodes positioned within the heart; 
 separate the plurality of signals into a first group of signals and a second group of signals, wherein the first group of signals includes a characteristic signal; and 
 generate a data set that includes at least one known data point and one or more unknown data points, wherein the at least one known data point is generated using the first group of signals and the one or more unknown data points are generated using the second group of signals. 
   
     
     
         12 . The medical system of  claim 11 , wherein the processor is further configured to identify the characteristic signal. 
     
     
         13 . The medical system of  claim 11 , wherein the processor is further configured to reduce or remove one or more features of the plurality of electrograms. 
     
     
         14 . The medical system of  claim 13 , wherein to reduce or remove one or more features of the plurality of electrograms, the processor is configured to perform at least one of the following:
 perform a wavelet transform on the plurality of signals;   rectify the plurality of signals; and   low-pass filter the plurality of signals.   
     
     
         15 . The medical system of  claim 14 , wherein the wavelet transform is a Haar wavelet transform. 
     
     
         16 . The medical system of  claim 11 , wherein to separate the plurality of signals into a first group of signals and a second group of signals, the processor is configured to perform statistical analysis on the plurality of signals. 
     
     
         17 . The medical system of  claim 16 , wherein to perform statistical analysis on the plurality of signals, the processor is configured to cluster the results of the statistical analysis, wherein the clustering produces the first group of signals and the second group of signals. 
     
     
         18 . The medical system of  claim 17 , wherein to cluster the results of the statistical analysis, the processor is configured to:
 perform a distribution-based clustering of the results of the statistical analysis; or   perform a density-based clustering of the results of the statistical analysis.   
     
     
         19 . The medical system of  claim 18 , wherein to perform distribution-based clustering of the results of the statistical analysis, the processor is configured to perform a Gaussian mixture model analysis of the results of the statistical analysis. 
     
     
         20 . The medical system of  claim 16 , wherein the statistical analysis comprises principal component analysis.