Abstract:
A method for analyzing signals, including: sensing a time-varying intracardiac potential signal and finding a fit of the time-varying intracardiac potential signal to a predefined oscillating waveform. The method further includes estimating an annotation time of the signal responsive to the fit.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention relates generally to signal analysis, and specifically to analysis of signals generated during a medical procedure. 
       BACKGROUND OF THE INVENTION 
       [0002]    Electrical signals generated from a patient&#39;s body organs, such as the heart, are typically noisy. The signals are typically measured during a medical procedure on the patient, and noise on the signals is usually caused by multiple factors. Some of the factors are artifacts such as movement or changing contact of an electrode with a section of an organ, interference due to other signals being created in proximity to the region being measured, the relatively high impedance of body organs, and inherent changes in the signals being generated. 
         [0003]    A process to reduce the effect of noise on signals from body organs is consequently advantageous. 
       SUMMARY OF THE INVENTION 
       [0004]    An embodiment of the present invention provides a method for analyzing signals, including: 
         [0005]    sensing a time-varying intracardiac potential signal; 
         [0006]    finding a fit of the time-varying intracardiac potential signal to a predefined oscillating waveform; and 
         [0007]    estimating an annotation time of the signal responsive to the fit. 
         [0008]    In a disclosed embodiment the time-varying intracardiac potential signal includes a unipolar signal. Typically, the predefined oscillating waveform includes a single complete oscillation having a single local maximum, a single local minimum, and a single inflection separating the local minimum and maximum. 
         [0009]    In an alternative embodiment the predefined oscillating waveform includes a first differential of a Gaussian function. Typically, the first differential is skewed by an asymmetry factor. 
         [0010]    In another disclosed embodiment the time-varying intracardiac potential signal includes a bipolar signal. The predefined oscillating waveform may include a difference between a first single complete oscillation and a second single complete oscillation. Typically, the first single complete oscillation includes a first single local maximum, a first single local minimum, and a first inflection separating the first local maximum and minimum, and the second single complete oscillation includes a second single local maximum, a second single local minimum, and a second inflection separating the second local maximum and minimum. 
         [0011]    The first single complete oscillation and the second complete oscillation may be separated by a temporal difference. The temporal difference may be a function of a spatial separation of electrodes generating the bipolar signal. Alternatively or additionally, the temporal difference may be a function of an electrode orientation relative to a propagation direction of an activation wave. 
         [0012]    In a further disclosed embodiment the predefined oscillating waveform includes a difference between a first Gaussian function first differential and a second Gaussian function first differential. Typically, the first Gaussian function first differential is skewed by a first asymmetry factor and the second Gaussian function first differential is skewed by a second asymmetry factor. 
         [0013]    In a yet further disclosed embodiment the time-varying intracardiac potential signal includes three or more unipolar signals having temporal differences therebetween, and wherein a propagation direction of an activation wave is a function of the temporal differences. Typically, respective electrodes having respective positions generate the three or more unipolar signals, and the respective positions may be parameters of the function. 
         [0014]    There is further provided, according to an embodiment of the present invention, apparatus for analyzing signals, including: 
         [0015]    a sensor configured to sense a time-varying intracardiac potential signal; and 
         [0016]    a processor configured to: 
         [0017]    find a fit of the time-varying intracardiac potential signal to a predefined oscillating waveform, and estimate an annotation time of the signal responsive to the fit. 
         [0018]    The present disclosure will be more fully understood from the following detailed description of the embodiments thereof, taken together with the drawings, in which: 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0019]      FIG. 1  is a schematic illustration of an electrocardiograph (ECG) analysis system, according to an embodiment of the present invention; 
           [0020]      FIG. 2  shows schematic graphs of typical ECG signals processed by the ECG analysis system, according to an embodiment of the present invention; 
           [0021]      FIGS. 3 and 4  show schematic graphs produced by equations used for fitting to ECG signals, according to embodiments of the present invention; 
           [0022]      FIG. 5  is a flowchart showing steps in analyzing intracardiac signals, according to an embodiment of the present invention; and 
           [0023]      FIG. 6  shows schematic graphs illustrating results obtained by the system of  FIG. 1 , according to an embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS 
     Overview 
       [0024]    An embodiment of the present invention provides a method for processing a “raw” or filtered intracardiac signal, which may be unipolar or bipolar. Typically the processing comprises fitting the intracardiac signal to a predetermined waveform, and deriving an annotation time of the signal from the fitted signal, rather than from the raw signal. 
         [0025]    Typically, a unipolar signal is fitted to an equation representative of a single complete oscillation. A bipolar signal may be fitted to an equation representative of a difference of two single complete oscillations, typically separated by a temporal difference. In some embodiments the single complete oscillation corresponds to a differential of a Gaussian function. An asymmetry factor may be applied to the differential, and in some embodiments the asymmetry factor corresponds to a Gaussian function. 
         [0026]    The inventors have found that fitting raw or filtered signals to a predetermined equation, and measuring an annotation time from the fitted signals, reduces variation of the annotation times, as compared to annotation times determined directly from the raw or filtered signals. 
       System Description 
       [0027]    Reference is now made to  FIG. 1 , which is a schematic illustration of an electrocardiograph (ECG) analysis system  20 , according to an embodiment of the present invention. System  20  receives at least one, and typically a plurality, of electrical signals from one or more electrodes positioned within an organ of a human patient. Typically, the signals are received from a multiplicity of electrodes placed on one or more probes in the organ. For example, during an invasive procedure on a heart, a first probe with one or more electrodes may be positioned in a reference region of the heart, and used to sense a reference ECG signal from the region. A second probe having multiple electrodes may be used to detect and record other ECG signals from other regions of the heart. 
         [0028]    For simplicity and clarity, the following description, except where otherwise stated, assumes an investigative procedure that senses electrical signals from a heart  34 , using a single probe  24 . Furthermore, a distal end  32  of the probe is assumed to have two substantially similar electrodes  22 A.  22 B. Electrodes  22 A,  22 B, may be referred to herein as electrodes  22 . Those having ordinary skill in the art will be able to adapt the description for multiple probes having one or more electrodes, as well as for signals produced by organs other than a heart. 
         [0029]    Typically, probe  24  comprises a catheter which is inserted into the body of a subject  26  during a mapping procedure performed by a user  28  of system  20 . In the description herein user  28  is assumed, by way of example, to be a medical professional. During the procedure subject  26  is assumed to be attached to a grounding electrode  23 . In some embodiments, electrodes  29  may be attached to the skin of subject  26 , in the region of heart  34 . 
         [0030]    System  20  may be controlled by a system processor  40 , comprising a processing unit  42  communicating with a memory  44 . Processor  40  is typically mounted in a console  46 , which comprises operating controls  38 . Controls  38  typically include a pointing device  39 , such as a mouse or a trackball, that professional  28  uses to interact with the processor. The processor uses software, including a probe navigation module  30  and an ECG module  36 , stored in memory  44 , to operate system  20 . ECG module  36  comprises a reference ECG sub-module  37  and a map ECG sub-module  41 , whose functions are described below. Results of the operations performed by processor  40  are presented to the professional on a display  48 , which typically presents a graphic user interface to the operator, a visual representation of the ECG signals sensed by electrodes  22 , and/or an image of heart  34  while it is being investigated. The software may be downloaded to processor  40  in electronic form, over a network, for example, or it may, alternatively or additionally, be provided and/or stored on non-transitory tangible media, such as magnetic, optical, or electronic memory. 
         [0031]    ECG module  36  is coupled to receive electrical signals from electrodes  22 . The module may also be coupled to receive signals from one or more of electrodes  29 . The ECG module is configured to analyze the signals and may present the results of the analysis in a standard ECG format, typically a graphical representation moving with time, on display  48 . 
         [0032]    Probe navigation module  30  tracks sections of probe  24  while the probe is within subject  26 . The navigation module typically tracks both the location and orientation of distal end  32  of probe  24 , within the heart of subject  26 . In some embodiments module  30  tracks other sections of the probe. The navigation module may use any method for tracking probes known in the art. For example, module  30  may operate magnetic field transmitters in the vicinity of the subject, so that magnetic fields from the transmitters interact with tracking coils located in sections of the probe being tracked. The coils interacting with the magnetic fields generate signals which are transmitted to the module, and the module analyzes the signals to determine a location and orientation of the coils. (For simplicity such coils and transmitters are not shown in  FIG. 1 .) The Carto® system produced by Biosense Webster, of Diamond Bar, Calif., uses such a tracking method. Alternatively or additionally, navigation module  30  may track probe  24  by measuring impedances between electrode  23 , electrodes  29  and electrodes  22 , as well as the impedances to other electrodes which may be located on the probe. (In this case electrodes  22  and/or electrodes  29  may provide both ECG and tracking signals.) The Carto3® system produced by Biosense Webster uses both magnetic field transmitters and impedance measurements for tracking. 
         [0033]      FIG. 2  shows schematic graphs of typical ECG signals processed by system  20 , according to an embodiment of the present invention. Graphs  100 ,  102  show exemplary potential vs. time plots of “raw” (i.e., unprocessed) bipolar intracardiac ECG signals. The signals are assumed to be derived from the potential differences between electrode  22 A and electrode  22 B while the electrodes contact a wall of the heart. As is known in the art, intracardiac ECG signals are noisy, the noise typically being generated by a number of factors, such as line radiation, the proximity of other electrical equipment, and other electrical sources derived from patient  26 , such as patient muscular contraction (apart from heart muscles). The noise typically causes problems in making quantitative measurements of annotation times from the raw signals. 
         [0034]    For example, an annotation time, T p , comprising the time of the “R” peak of the signal, may be required, the time being measured from the onset of the signal. Graph  100  illustrates that T p  is measured to be approximately 30 ms, whereas graph  102  illustrates that T p  is measured to be approximately 25 ms. As is illustrated in the graphs, the measured value of T p  varies. 
         [0035]    As stated above, graphs  100 ,  102  illustrate bipolar graphs generated by difference signals between electrode  22 A and  22 B. The signal on each electrode  22 A or  22 B, when measured relative to a common reference electrode, is a unipolar signal, so that the bipolar signal may be considered as a difference between two unipolar signals. The reference electrode may be any convenient electrode, such as grounding electrode  23 , and/or one or more of skin electrodes  29 , and/or one or more other electrodes in contact with the heart. 
         [0036]      FIGS. 3 and 4  show schematic graphs produced by equations used for fitting to ECG signals, according to embodiments of the present invention. Embodiments of the present invention fit a predetermined equation to signals such as the ECG signals illustrated in  FIG. 2 . The equation corresponds to a predetermined oscillating waveform, typically a waveform that is in the form of a single complete oscillation, i.e., a waveform that has beginning and end points that have a substantially zero signal level, and that encompasses all the electrical activity between the two points. Typically, the graph of a single complete oscillation has a single local minimum and a single local maximum. The local maximum and local minimum may be separated by a single inflection. 
         [0037]    In some embodiments, and as exemplified herein, the predetermined equation fitted to the signals is derived from the first differential of a Gaussian function, skewed by an asymmetry factor. 
         [0038]    Thus, for unipolar ECG signals received from electrodes  22 A or  22 B, processor  40  fits an equation having the general form given by equation (1) below to the signals: 
         [0000]    
       
         
           
             
               
                 
                   
                     
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         [0039]    where V unipolar (t) represents the varying unipolar potential signal measured at the electrode at a time t; 
         [0040]    t i  is a temporal displacement of the signal, with respect to the time t=0. t i  corresponds to the time when an activation wave passes through the electrode position; 
         [0041]    A is an amplitude of the signal; 
         [0042]    t s  is a parameter defining an asymmetry of the signal; and 
         [0043]    w is a parameter defining a width of the signal. 
         [0044]    Inspection of equation (1) shows that the asymmetry factor provided by the equation corresponds to a Gaussian function. Thus, equation (1) sums a Gaussian function and a first differential of a Gaussian function. 
         [0045]    In the description below, parameters t i1 , A 1 , t s1 , and w 1 , are also referred to collectively as the unipolar fitting parameters of equation (1). 
         [0046]    Graphs  110 ,  112 , and  114  ( FIG. 3 ) illustrate the effects of values of parameters t s  and w on the waveform generated by equation (1). For simplicity, the units of the ordinate and the abscissa of each graph are assumed to be arbitrary. As shown by graph  110 , for t s =0, the graph has two-fold symmetry, having a center of symmetry at (3, 0). (In other words, under a rotation of 180° in the plane of the graph the graph transforms into itself.) Graph  112  shows that for a positive value of t s =3, the graph becomes asymmetric. The asymmetry increases with increasing t s . 
         [0047]    As shown by graph  114 , the value of w changes the overall width of the graph, so that increasing the value of w reduces the width. 
         [0048]    If the ECG signal is a bipolar signal, it may be assumed to be generated by the difference between a unipolar signal V unipolar (t) 1  on electrode  22 A and a unipolar signal V unipolar (t) 2  on electrode  22 B. For bipolar signals such as these the processor fits an equation (2), derived from equation (1), to the signal: 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       
                         
                           
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         [0049]    where V bipolar (t) represents the varying bipolar potential signal measured at the electrode at a time t; 
         [0050]    V unipolar (t) 1 , V unipolar (t) 2 , also termed V 1  and V 2 , are as defined above for equation (1); 
         [0051]    t i1 , t i2  are temporal displacements of V 1 , V 2 ; 
         [0052]    A 1 , A 2  are amplitudes of V 1 , V 2 ; 
         [0053]    t s1 , t s2  define asymmetries of V 1 , V 2 ; and 
         [0054]    w 1 , w 2  define widths of V 1 , V 2 . 
         [0055]    For a bipolar signal there is a temporal difference, Δt i =t i1 −t i2 , equal to a difference between the temporal displacements of the two unipolar signals V unipolar (t) 1  and V unipolar (t) 2 . The temporal difference between the two unipolar signals is typically a function of the spatial separation of the two electrodes generating the bipolar signal, and of an electrode orientation relative to a propagation direction of the activation wave. Thus, in the case of two electrodes, at least a component of the propagation direction of the activation wave may be determined from the temporal difference of the unipolar signals. It will be appreciated that for more than two electrodes, the temporal differences between the respective unipolar signals detected by the more than two electrodes, as well as the positions of the electrodes, typically allow multiple components of the propagation direction to be found. From the multiple components, the propagation direction (not just a component) of the activation wave may be estimated. 
         [0056]    In the description below, parameters t i1 , t i2 , A 1 , A 2 , t s1 , t s2 , and w 1 , w 2  are also referred to collectively as the bipolar fitting parameters of equation (2). 
         [0057]    Graphs  120 ,  122 , and  124  ( FIG. 4 ) illustrate the application of equation (2). Graphs  120  and  122  are graphs of two unipolar equations of voltage vs. time, respectively having temporal displacements (in arbitrary units) of t=3 and t=4.5, and widths of 4 and 2. Graph  124  is the graph of the difference of the two expressions, illustrating a bipolar voltage vs. time function having a temporal difference of Δt=4.5−3=1.5. 
         [0058]    Generated intracardiac unipolar and bipolar signals depend, inter alia, on the positions of the electrodes used to measure the signals. The generated signals also depend on the condition of the heart being measured, i.e., whether the heart is functioning in a healthy or unhealthy manner. 
         [0059]    If a heart is unhealthy because of a specific defect, it also produces standard intracardiac signals, different from those of a healthy heart (similar differences may be used in diagnoses using skin ECG signals, i.e., body surface signals). In the case of a specific defect, the unhealthy heart generates standard deficient unipolar or bipolar signals, the deficiency in the signals being caused by the respective heart defect. 
         [0060]      FIG. 5  is a flowchart  200  showing steps performed by processor  40  in analyzing intracardiac signals, according to an embodiment of the present invention. In the following description the signals are assumed to comprise bipolar signals. Those having ordinary skill in the art will be able to adapt the description, mutatis mutandis, for unipolar signals. 
         [0061]    In an initial step  202 , professional  28  inserts probe  24  into heart  34 , so that electrodes  22 A and  22 B are in contact with a section of the heart wall. Processor  40  acquires intracardiac bipolar ECG signals from the electrodes, each ECG signal comprising ordered pairs of potentials V and times t: {(V,t)}. 
         [0062]    In a heartbeat selection step  204 , one complete heartbeat is selected. Thus, if the duration of the selected heartbeat is T, and the acquisition in step  202  is performed at a sample rate SampleRate, there are approximately T/SampleRate samples of bipolar signals in the selected heartbeat. 
         [0063]    In an analysis step  206 , the processor fits equation (2) to the selected heartbeat to derive a set of values of the fitting parameters of equation (2) that give a best fit to the selected heartbeat. 
         [0064]    In a comparison step  208 , the processor uses navigation module  30  to check if electrodes  22 A and  22 B are in the same position with respect to the heart. If the comparison returns a positive result, so that the electrodes are in the same position, then in an averaging step  210  the processor averages the fitting parameters for all the heartbeats at the position, to generate a set of averaged fitting parameters. The flowchart then continues at an annotation time step  212 . 
         [0065]    If the comparison returns a negative result, so that the electrodes have moved, then no averaging is performed, and the flowchart continues directly to step  212 . 
         [0066]    In annotation time step  212 , the fitting parameters derived either in step  210  (if averaging has occurred) or in step  206  (if there has been no averaging) are used to estimate an annotation time. The annotation time is a reference time of occurrence of a characteristic of the ECG signal. The annotation time may be defined with respect to the body surface ECG, or with respect to an intracardiac reference ECG, for example from a catheter placed in the coronary sinus. Typical signal characteristics used to define the reference annotation time include, but are not limited to, the time at which the R-peak maximum of the QRS complex occurs, the time at which the minimum derivative of the QRS complex occurs, the time at which a center of energy of the complete signal occurs, or the time at which a first indication of the complete signal occurs. The reference annotation time is typically dependent on the position in the heart at which the signal is measured. Definitions for the reference annotation times and their values are stored in reference ECG sub-module  37 . 
         [0067]    In a map building step  214 , the processor constructs a point of an electro-anatomical map of heart  34 . To construct the map point, the processor incorporates the difference of annotation times estimated in step  212  and the relevant reference annotation time (stored in sub-module  37 ) into a map of the heart (using navigation module  30 ) ( FIG. 1 ). Sub-module  41  is also used in this step. 
         [0068]    The repetition of steps  202 - 214  is indicated by a continuation condition  216  returning a positive result. If condition  216  returns a negative result, typically by professional  28  deciding to stop the mapping procedure of step  214 , the flowchart ends. 
         [0069]    As stated above, steps  202 - 214  can be typically performed for different situations comprising different positions of the electrodes in healthy hearts and in unhealthy hearts with known defects. 
         [0070]      FIG. 6  shows schematic graphs illustrating the results of applying the methods described above, according to an embodiment of the present invention. Intracardiac ECG signals were recorded from several different cases, to create a data pool. Approximately 5,900 heartbeats were extracted from the data pool. All heartbeats were organized into eleven groups, each group containing a heartbeat with an amplitude less than a pre-determined threshold. 
         [0071]    The threshold is a measure of the noise of the signal, so that signals having lower thresholds have higher noise levels. For each heartbeat in a specific group the time of occurrence t Rk  of the R-peak maximum, and the time of occurrence t Ck  of the passing of the activation wave, were estimated. k is an index representing a number of the heartbeat being measured. t Ck  was estimated using a fitting analysis similar to that described for flowchart  200 , herein also referred to as a fit annotation method. The method for estimating t Rk  is also referred to herein as the maximum annotation method. 
         [0072]    Within each group, the following differences in times were calculated: 
         [0000]      Δ t   R   =t   Rk   −t   R(k-1)  
 
         [0000]      Δ t   C   =t   Ck   −t   C(k-1)   (3)
 
         [0073]    From equations (3) the following variability coefficients were calculated: 
         [0000]    
       
         
           
             
               
                 
                   
                     
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         [0074]    where σ(Δt) is a standard deviation of all Δt values, and 
         [0075]    M(Δt) is a mean of all the Δt values. 
         [0076]    The expressions of equations (4) give a measure of the variability of the annotation times by the maximum annotation method or by the fit annotation method of heartbeats within a given group. 
         [0077]    A graph  300  plots the variability VAR R  vs. the threshold of a group, and a graph  302  is a linear regression of graph  300 . A graph  310  plots the variability VAR C  vs. the threshold of a group, and a graph  312  is a linear regression of graph  310 . By comparison of the two sets of graphs, it is apparent that for low values of the threshold, i.e., for signals with high noise values, the variability of the signals processed according to methods described herein, i.e., using the fit annotation method, is less than the variability of signals that have not been processed with these methods. 
         [0078]    It will be appreciated that the embodiments described above are cited by way of example, and that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and subcombinations of the various features described hereinabove, as well as variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not disclosed in the prior art.