Method of and system for signal separation during multivariate physiological monitoring

Abstract

Multiple electrode contacts make electrical connections to the anterior and/or posterior chest for multivariate characterization of the electrical activation of the heart. A central processing unit derives synthetic composite electrographic signals as well as flag signals for specific purposes. A preferred embodiment uses this system to trigger or gate magnetic resonance imaging, eliminating or reducing problems from small or inverted R-waves, lead detachment, noise, flow signal, gradient changes, and rhythm changes, more reliably flagging the onset of electrical activation of the ventricles. Additional derived data are ST-segment shifts, filling times, and respiratory cycle. Filling times may be used for greatly improved imaging in the presence of rhythm disturbances, such as atrial fibrillation. Respiratory cycle may be used as a respiratory trigger to control for the effects of breathing on the heart position and image quality.

1 : A method of outputting an indication of the timing and morphology of a monitored signal from at least a part of a biological organ comprising the steps of:
 acquiring a multivariate signal via a plurality of sensors as observations, including a desired signal attributable to at least a part of a biological organ signal source and one or more superimposed other signals where at least one pair of the signals from the multivariate signal exhibits partial correlation;   extracting the desired signal from the acquired physiologic signal, wherein the desired signal is a periodically recurring set of features of interest not limited to independent components from the observations;   monitoring the timing of an occurrence and reoccurrences of at least one of the features of interest; and   generating an output signal relative to the time period between the occurrence and the reoccurrences of the at least one of the features of interest.   
   
   
       2 : The method as in  claim 1  further comprising the steps of:
 inputting the acquired multivariate signal into a data processor that performs the steps of:
 converting the acquired multivariate signal into signal data upon which mathematical operations are performed by representing the acquired signal data as an observation data set O(t) whose values are representative of the signals acquired by the corresponding sensors; 
 accessing a separability operator S that includes separation coefficients; 
 applying the separability operator S to the observation data set O(t) to produce an output; 
 extracting one or more output signals from the output to determine a condition associated with the at least a part of a biological organ; and 
 enabling monitoring of the condition associated with the at least a part of a biological organ; 
   wherein the separation coefficients collectively specify a model of the conditions of signal sources encountered during data acquisition.   
   
   
       3 : The method of  claim 1 , further comprising the steps of:
 inputting the acquired multivariate physiologic signal into a data processor that performs the steps of:
 identifying categories of waveforms; 
 characterizing biologic organ status by a sequence of signal activation cycles; and 
 generating output signals corresponding to the timing and occurrence of one or more of the categories to modify the quality of images or data dependent on timing. 
   
   
   
       4 : The method of  claim 1  wherein the step extracting comprises the steps of:
 extracting a series of cycle lengths of cardiac activation cycles; and   analyzing the series of cycle lengths to define triggering based on pre-selected criteria applied to a current cycle length from the series and one or more cycle lengths preceding the current cycle length.   
   
   
       5 : The method of  claim 4  wherein said step of analyzing includes the step of:
 generating output information serving to regularize the timing used for dependent data collection to compensate for the occurrences of one or more irregular cycle lengths.   
   
   
       6 : The method of  claim 2 , further comprising the steps of:
 separating signal contributions from different parts of a source of interest; and   deriving a representation of isolated signals from one or more portions of the source of interest.   
   
   
       7 : The method of  claim 1 , further comprising the steps of:
 determining a position and orientation of the at least a part of a biological organ from the desired signal attributable to the at least a part of a biological organ; and   reducing variability of waveforms related to the position or orientation of at least a part of a biological organ.   
   
   
       8 : The method of  claim 1 , further comprising the step of:
 wherein the at least a part of a biological organ is the heart and the output provides for extended coverage of the thorax not limited to standard 12-lead positions.   
   
   
       9 : The method of  claim 8 , further comprising the step of:
 computing a representation of total deviations from normal for one or more specified measurements from the output signals.   
   
   
       10 : A system of outputting an indication of at least one of the timing and morphology of a monitored physiologic signal produced by at least a part of a biological organ, comprising the steps of:
 a plurality of sensors adapted to be located at different positions relative to the at least a part of a biological organ for acquiring a multivariate signal via the plurality of sensors, including a desired signal attributable to at least a part of a biological organ signal and one or more superimposed contaminant signals, wherein at least one pair of the signals from the multivariate physiologic signal exhibits partial correlation;   a data processor in data communication with the plurality of sensors and executing the steps of:
 extracting the desired signal from the acquired physiologic signal, wherein the desired signal is comprised of a periodically recurring set of features of interest; 
 monitoring occurrences of at least one of the features of interest; and 
 outputting an indicator of at least one of the features of interest and variations thereof. 
   
   
   
       11 : The system of  claim 10  further comprising:
 a separability operator that includes separation coefficients;   wherein the separation coefficients collectively specify a model of the conditions of one or more signal sources encountered during data acquisition,   wherein the signals acquired on each of the sensors reflects the respective sensitivity of the particular signal sensor to multiple signal sources, and   wherein the data processor further executes the steps of:
 converting the acquired multivariate signal into signal data upon which mathematical operations are performed by representing the acquired signal data as an observation data set O(t) whose values are representative of the physiologic signals acquired by the corresponding sensors; 
 applying the separability operator S to the observation data set O(t) to produce an output; 
 extracting one or more output signals from the output to determine a condition associated with the at least a part of a biological organ; and 
 enabling monitoring of the condition associated with the at least a part of a biological organ. 
   
   
   
       12 : The system of  claim 10 , wherein the data processor further executes the steps of:
 inputting the acquired multivariate signal;   identifying categories of waveforms; and   generating output signals corresponding to the timing and occurrence of one or more of the categories to modify the quality of images or data dependent on signal timing.   
   
   
       13 : The system of  claim 10 , wherein the data processor further executes the step of:
 extracting a series of cycle lengths of cardiac activation cycles; and   analyzing the series of cycle lengths to define triggering based on pre-selected criteria applied to one or more consecutive cycle lengths.   
   
   
       14 : The system of  claim 11 , wherein the data processor further executes the steps of:
 separating signal contributions from different parts of a source of interest; and   deriving a representation of isolated signals from one or more portions of the source of interest.   
   
   
       15 : The system of  claim 10 , wherein the data processor further executes the steps of:
 determining a position and orientation of the at least a part of a biological organ from the desired signal attributable to the at least a part of a biological organ; and   reducing variability of waveforms related to position or orientation of the at least a part of a biological organ.   
   
   
       16 : The system of  claim 10 , wherein said data processor further executes the step of:
 wherein the at least a part of a biological organ is the heart and the output provides for extended coverage of the thorax not limited to standard 12-lead positions.   
   
   
       17 : The system of  claim 16 , wherein said data processor further executes the step of:
 computing a representation of total deviations from normal for one or more specified measurements from the output signals.   
   
   
       18 : The method of  claim 9  wherein the specified measurement is ST segment deviation. 
   
   
       19 : The system of  claim 17  wherein the specified measurement is ST segment deviation. 
   
   
       20 : The method as in  claim 1  further comprising the steps of:
 determining a position and orientation of the at least a part of a biological organ from a signal attributable to the at least a part of a biological organ; and   applying heart position and orientation to map a representation of output signals to a model of the at least part of the biologic organ.