Abstract:
A system and method for detecting a patient&#39;s susceptibility to arrhythmias and cardiac tissue abnormality is disclosed. The method consists of using a computer, a display, software loaded onto the computer that generates graphical user interfaces (GUIs), an electronic interface, and a plurality of electrodes. The electronics interface is in electronic communication with the computer, and further in electronic communication with the electrodes that are placed by self-adhesion at predetermined locations on a test subject. According to one aspect of the invention, the method enables a user, typically a medical professional, to initiate, with minimal input, certain diagnostic tests involving observing and analyzing a series of QRS complexes, some of which are biased by passively altering the impedance of the patient&#39;s body, and others of which are unbiased. The signals are then compared, and the differences are analyzed to detect a patient&#39;s susceptibility to arrhythmias and cardiac tissue abnormality.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation of application Ser. No. 09/487,557, filed Jan. 19, 2000 now U.S. Pat. No. 6,445,947 which claims priority under 35 U.S.C. §119(e), to previously filed U.S. Provisional Application No. 60/116,396, filed Jan. 19, 1999 and U.S. Provisional Application No. 60/133,983, filed May 13, 1999, and co-pending application Ser. No. 09/126,864, filed Jul. 31, 1998 now U.S. Pat. No. 6,129,678 issued Oct. 10, 2000; and is also a continuation-in-part of Ser. No. 09/126,864, filed Jul. 31, 1998, the subject matter of which is incorporated herein by reference. 
    
    
     FIELD OF INVENTION 
     The invention relates to the detection of patients&#39; susceptibility to arrhythmias and, more particularly, to various techniques for improving the detection of signals to achieve this goal. 
     BACKGROUND OF THE INVENTION 
     There are various devices known in the art for monitoring heart function. Many of these devices typically function by analyzing signals such as an electrocardiogram signal, which can be representative of heart function. There is a need to identify patients at high risk for life-threatening arrhythmias. 
     Various means have been proposed for detecting patient susceptibility to arrhythmias. U.S. Pat. No. 5,117,834 discloses one method by which pulses of electromagnetic energy are injected into a patient and the changes in the patient&#39;s electrocardiographic signals caused by the injection are recorded. U.S. Pat. No. 5,351,687 is similar in concept to U.S. Pat. No. 5,117,834, but it describes the use of a magnetic sensor for use in detecting the cardiographic signals. U.S. Pat. No. 5,555,888 discloses various means for adapting and automatically facilitating the assessment techniques and means similar to that shown in the above patents for determining patient susceptibility to arrhythmias. 
     Other techniques which are used to analyze cardiac signals for somewhat similar purposes include those known as t-wave alternans and signal-averaged electrocardiograms. Each of these techniques is limited in its application and utility by various factors which are overcome through use of the below-described inventions. 
     SUMMARY OF THE INVENTION 
     The present invention provides a system and method of determining, through noninvasive means, a patient&#39;s susceptibility to arrhythmia. More specifically, this invention comprises various improvements to known innovations for optimizing detection of a patient&#39;s susceptibility to arrhythmias. This invention embodies numerous software and sequence improvements for applying this basic technology. 
     Another purpose of this invention is to provide hardware and signal analysis means for detecting, amplifying, or improving recognition of relevant signals. 
     Another purpose of this invention is to provide for improved performance lead sets and the software to promote ease of attachment and removal from the patient and ease of connection of the lead system to the hardware. 
     A further object of this invention is to provide new combinations of electrode placement and use to promote better arrhythmia susceptibility diagnosis. 
     A further object of this invention is to provide a reduction in the size of necessary components to allow for hand-held system dimensions. 
     A further object of this invention is to provide a means for distinguishing between the signals from the X, Y, and Z directions as well as previously unused directional components of very low-level signal data. 
     Another object of this invention is to supply means for displaying of a patient&#39;s waveforms and other data derived from the detected signals, as well as to provide various interfaces to communicate the data between the patient and physician or health care professional. 
     It is a further object of this invention to provide signal artifact reduction, and to provide a single point connector for the set of leads. 
     Another object of this invention is to provide improved lead materials for improved performance, as well as an improved lead effect modeling (LEM). 
     It is yet another object of this invention to provide amplifier circuitry that minimizes amplifier saturation and optimizes fast recovery. 
    
    
     BRIEF DESCRIPTIONS OF THE DRAWINGS 
     FIG. 1 depicts the broad overview of the invention, showing the patient electronic interface computer. 
     FIG. 2 is an exemplary depiction of a patient showing possible electrode patient locations. 
     FIG. 3 is a more close-up view of the lead system, showing the connector and attached electrodes. 
     FIG. 4 depicts the principal graphical user interface (GUI) generated by the computer and the software portion of the invention. 
     FIG. 5 is the principal GUI generated by the computer and software portion of the invention, with the testing menu engaged. 
     FIG. 6 is the “New Subject” GUI. 
     FIG. 7 is the “Acquisition” GUI. 
     FIG. 8 is the “Perform All Standard Protocols” GUI. 
     FIG. 9 is the “Ready to Verify Sensing” GUI. 
     FIG. 10 is the “Acquisition Active” GUI generated by the computer and software portion of the invention. 
     FIG. 11 is the “Sensing Problem” GUI generated by the computer and software portion of the invention. 
     FIG. 12 is the “Repeat Sensing Verification” GUI generated by the computer and software portion of the invention. 
     FIG. 13 is the principal GUI generated by the computer and software portion of the invention, depicting a pulse graph. 
     FIG. 14 is the “Ready to Begin Testing Execution” GUI generated by the computer and software portion of the invention. 
     FIG. 15 is the “Acquisition Active” GUI generated by the computer and software portion of the invention, depicting realtime R-wave acquisition. 
     FIG. 16 is the “Halted Data Acquisition” GUI generated by the computer and software portion of the invention. 
     FIG. 17 is the “Resume with Protocol” GUI generated by the computer and software portion of the invention. 
     FIG. 18 is the principal GUI generated by the computer and software portion of the invention, depicting the “View” drop-down menu engaged. 
     FIG. 19 is the “Options” GUI generated by the computer and software portion of the invention. 
     FIG. 20 is the “Simulator” GUI generated by the computer and software portion of the invention. 
     FIG. 21 is the “QRS Status” GUI generated by the computer and software portion of the invention. 
     FIG. 22 is the “Simulator” GUI generated by the computer and software portion of the invention, depicting a further display option. 
     FIG. 23 is the “Simulator” GUI generated by the computer and software portion of the invention, depicting a further display option. 
     FIG. 24 is the “Simulator” GUI generated by the computer and software portion of the invention. 
     FIG. 25 is the “Simulator” GUI generated by the computer and software portion of the invention. 
     FIG. 26 is the principal GUI generated by the computer and software portion of the invention, depicting the “Data” drop-down menu engaged. 
     FIG. 27 is the “Accessing Stored Subject Data” GUI generated by the computer and software portion of the invention. 
     FIG. 28 is the “Open” GUI generated by the computer and software portion of the invention. 
     FIG. 29 is the “Protocol Steps” GUI generated by the computer and software portion of the invention. 
     FIG. 30 is the “Select Protocol Step” GUI generated by the computer and software portion of the invention. 
     FIG. 31 is an exemplary EKG signal. 
     FIG. 32 is a block diagram of switching and clamping circuit of the electronic interface. 
     FIG. 33 is a flow chart showing the overall interaction of the invention. 
     FIG. 34 is a more detailed view of the connector and attached leads, showing pin layout. 
     FIG. 35 is a block diagram of the isolated driver and shunting switch, a portion of the electronics interface. 
     FIG. 36 is an exemplary series of QRS complexes. 
     FIG. 37 is a high-level block diagram of the electronics interface. 
     FIGS. 38 a  and  38   b  are a wire-level depiction of the electronics interface. 
     FIG. 39 is a flow chart/block diagram of the isolated fast recovery EKG amplifier. 
     FIGS. 40 a  - 40   c  are a schematic of the fast-recovery EKG amplifier. 
     FIG. 41 is a block diagram/flow chart of the isolated driver section of the electronics interface. 
     FIGS. 42 a  and  42   b  are, a schematic of the isolated driver section of the electronics interface. 
     FIG. 43 is a high-level flow chart of the operation of the software. 
     FIG. 44 is a lower-level flow chart of the test control and acquisition portion of the software. 
     FIGS. 45 a  and  45   b  are, a lower-level flow chart of the post-processing software operation. 
     FIG. 46 is a lower-level flow chart of the realtime enter of controls implemented by the software. 
     FIG. 47 is a data set of observed data. 
     FIG. 48 is a data set of observed data. 
     FIG. 49 is a data set of observed data. 
     FIG. 50 is a data set of observed data. 
     FIG. 51 is a data set of observed data. 
     FIG. 52 is a data set of observed data. 
     FIG. 53 is a data set of observed data. 
     FIG. 54 is a data set of observed data. 
     FIG. 55 is a data set of observed data. 
     FIG. 56 is a data set of observed data. 
     FIG. 57 is a data set of observed data. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     The invention provided is an improved method and system for detecting patients&#39; susceptibility to arrhythmia and cardiac tissue abnormality in a noninvasive fashion. In FIG. 1, computer  27  is operably coupled to monitor  23 , which is further closely coupled with electronic interface  18  via wire  31 . Lead system  12  is connected between patient  35  and electronic interface  18 . 
     FIG. 2 is a front and rear view of patient  35 . In one preferred embodiment, lead system  12  consists of nine (9) lead wires. Advantageously, the lead system can be connected as shown in FIG. 2 for efficient and consistent setup of the invention. Typically, the lead system is preassembled with a predetermined number of leads having predetermined lengths. Although it is contemplated by this invention that the lead system can be preassembled with leads of different lengths to accommodate different room sizes and patent locations, among other factors, a general consideration is that the sensing leads and energy delivery leads are less than 9 feet in length to reduce possible induced noise. Further, the leads in lead system  12  are constructed from a low-impedance material, such as tin, sodium, silver, silver chloride, or other low-impedance material recognized as such by those skilled in the art. This construction assists in efficient delivery of subpacing energy for stimulation leads and increased sensitivity for sensing leads. The electrodes involved with energy delivery are advantageously shaped and sized for placement on the patient&#39;s body habitus to minimize signal quality reduction by avoiding muscle tissue. 
     FIG. 3 shows a more detailed view of one preferred embodiment of single-point connector  15  with 9 lead wires electronically coupled thereto. In this embodiment, each of the 9 lead wires is connected to one of 9 self-adhesive electrodes. The adhesive used on any specific electrode can differ depending on various factors, including where on patient  35  the electrode or patch is to be affixed and whether the electrode is reusable or disposable. In one preferred embodiment, electrode  1  is to be connected in the correspondingly-numbered position indicated in FIG.  2 . Thus, for example, electrodes  1  and  2  are connected on patient  35  at the corresponding left and right mid-axillary lines, on a horizontal plane, at the level where the fifth intercostal space intersects the sternum. Electrode  3  is placed on the sternum. In this embodiment of the invention, electrode  4  is placed on patient  35  at the fifth intercostal space. Electrode  5  is a neck electrode and is attached generally at the back of the neck, as indicated on back view  2 . 2  of FIG.  2 . Lead  6  is a left leg lead that will attach generally in the location on patient  35 , as shown on front view  2 . 1  of FIG.  2 . The larger, rectangular electrodes, electrodes  7  and  8 , are attached in the pectoral area and back, respectively, as shown in FIG.  2 . In one preferred embodiment, the generally pectorally-placed electrode  7 , or patch, has a skin contact surface area of at least 20 cm 2 , and typically less than about 70 cm 2 . The patches of lead system  12  can be constructed with different electrical characteristics to facilitate energy transfer and sensing. 
     Single-point connector  15  is configured to electronically mate with electronic interface  18 . A top-level block diagram of electronic interface  18  is shown in FIG.  37 . In one embodiment, single-point connector  15  advantageously couples  9  electroleads into one plug assembly. As can be seen in FIG. 3, one preferred embodiment is a stacked lead receptacle having at least two rows of lead connections that are identified with respect to each lead (also see FIG.  42 ). This advantageously provides for a more compact connector, and provides for rapid and efficient coupling and decoupling to electronics interface  18 . In one preferred embodiment, the connector  15  is designed to be easily and rapidly coupled and decoupled with the electronics interface  18  by the use of only one hand. Advantageously, this allows for efficient setup and takedown of the invention. Patches  1  through  9  are premarked, as indicated on FIG. 3, to provide for simpler and more convenient placement on patient  35 . Further, the lead system  12  comprises a reference lead  9 . It is anticipated that the lead system  12  can be a single-use system or a disposable system to provide for a safe and sterile means by which to perform the tests provided by this invention. Further, reusing the lead system may create a higher impedance in the system, which may make the lead system  12  more susceptible to noise. In one preferred embodiment of the invention, a means is provided for determining whether the lead system has been previously used. This can be done by using a single-use-type adhesive. Another means for detecting previous use is creating a deformable tab on connector  15  that deforms on its first mating with electronic interface  18 , and thereafter is not usable. Creating fusible links or breakable tabs to indicate the lead system has been previously used are an additional means, among others. 
     The electronics interface  18 , by coupling with computer  27 , allows for the injection of low-level electromagnetic energy into patient  35  to alter at least one cardiac signal. The energy is delivered at a subpacing threshold and is typically introduced externally, through the patient&#39;s  35  chest and into cardiac tissue. The subpacing energy is delivered just before a QRS complex event, as determined by the data gathered by the hardware and electronic interface  18 , and as analyzed by the software. Electronic interface  18  and attached computer  27  function to process received signals, among other functions. The energy delivery leads are typically leads  7  and  8 ; however, it is anticipated that circumstances may arise where more or less than two energy delivery leads may be needed. In such cases, greater or fewer leads may be configured to delivery energy. Further, the number of sensing leads may be variable as well, depending on the needs and judgment of the medical professional administering the testing. 
     FIG. 31 depicts an exemplary QRS complex and related signals. P-wave  153  is the signal that typically precedes the actual QRS complex  130 . The interval between the start of the P-wave and the beginning of QRS complex  130  is known as the PR interval  150 . QRS complex  130  is typically made up of three distinct components: Q  117 , which is typically the first negative signal; R  113 , which is typically the first positive signal; and S  121 , which is the first negative signal subsequent to R  113  signal. T segment  133  is typically defined as the more-or-less flat signal, or absence of signal, subsequent to recovery of the S  121  portion of QRS complex  130 , prior to commencement oft-wave  146 . The QT interval is typically defined as the portion of the signals commencing at the beginning of QRS complex  130  and ending after t-wave  146 . J Joint  137  is typically defined as the end of the QRS complex and the beginning of the ST segment  133 . The T-P interval (not indicated) is the time period from the end of the T-wave to the beginning of the next P-Wave. The entire cardiac cycle is P-Q-R-S-T. 
     The slight transcutaneous biosync or subpacing current is typically introduced by the invention at odd numbers of QRS complex normal sinus beats. Resulting QRS complexes are then compared to the even-numbered unbiased beats. By computer-implemented software, the distinguishable signal differences can then be calculated and displayed. Generally, differences are found between the biased and unbiased QRS complexes in patients with ventricular tachycardia and other indices of arrhythmia or cardiac tissue abnormality. It is anticipated that these input potentials would be extremely small, for example, less than 100 uV, and typically of a duration of less than about 100 mS. Such a current might involve visualization of a possible analog of late potentials throughout the QRS complex. 
     Computer  27  operates a graphical user interface (GUI) based software, which generally includes a tool bar, a status bar, a display area, and various drop-down menus. The principal GUI is depicted in FIG.  4 . The GUI consists of display area  39 , status bar  37 , tool bar  42 , and drop-down menus  46 . Tool bar  42  contains button icons that represent shortcuts to many of the functions described below in association with drop-down means  46 . Status bar  37  depicts the general status  13  of the software on the left-hand side, technical data  10  regarding the lead sensors and input current in the middle section, and frequency and protocol information  28  generally on the right-hand side. FIG. 4 illustrates a GUI in Microsoft Corporation&#39;s Windows 95® operating system format. The GUI is generated by computer  27 , which typically consists of mouse  40 , CPU  25 , display  23 , a keyboard (not shown) operably attached to computer  27 , and peripheral input/output devices  26 , as well as storage media  21 . 
     FIG. 5 depicts “Testing” drop-down menu  48  engaged. As revealed in FIG. 5, “Testing” drop-down menu  48  provides a series of options to perform testing provided for by this invention. If the “Performed Test Sequence”  50  is selected, the GUI of FIG. 6 is generated on display  23 . Using mouse  40  or keyboard input, a preexisting patient may be selected from display area  39  of this GUI, or “New Patient” button  52  may be selected. Mouse  40  or keyboard input may be used to select all operable functions of the GUIs involved in this invention. If “OK”  36  is selected from the GUI of FIG. 36, subject information  41  is retrieved for the highlighted subject. “Cancel”  30  returns the operator to the view of the GUI of FIG.  4 . 
     FIG. 7 depicts the informational GUI that appears if “New Patient” button  52  is selected. In the upper portion of the GUI represented in FIG. 7, subject information may be entered in box  44  which includes identification number (ID)  55  to associate with the patient, patient&#39;s Name  58 , patient&#39;s Birthdate  64 , Gender  66  of the patient, Race  80  of the patient, and any miscellaneous notes  85  that might be helpful during or after the patient&#39;s diagnostic sessions. 
     The lower portion of the GUI depicted in FIG. 7 includes six boxes where testing parameters are entered. The test duration box  90  is configured by the medical professional to indicate how many QRS complex signals will comprise the test. The options under the sensitivity input box  68  are low, medium, and high. This advantageously allows the sensitivity to be adjusted to correct over- or under-sensing caused by subject-to-subject variation in QRS amplitude and morphology. The next variable parameter is the deviation limit  87 , which is entered in milliseconds in the correspondingly marked box. Deviation limit  87  allows the operator to eliminate inaccurately-positioned stimulations from post-processing. This can happen due to the predictive nature of pre-R-wave stimulation and the normal R-R interval variation (see FIG.  36 ). The operator identifies the allowable tolerance. Any pulses that are greater than this tolerance are eliminated from further processing. Also in FIG. 7 is pulse configuration box  33 . In pulse configuration box  33 , the low-current pulse can be configured to account for the different circumstances of the patient to be tested. The parameters or variables are current strength  72 , width of the pulse  82  (in milliseconds), and temporal location  92  of the pulse with respect to the QRS complex. A one-millisecond Pulse Ramp Up  78  option is also available by checking the corresponding box on the GUI. 
     FIG. 8 depicts a GUI option screen where a simplified selection can be made for all available testing standard protocols. There, selection of “Yes”  11  invokes all currently defined standard protocols. These protocols are set up initially and invoke from this screen. This option advantageously allows testing without requiring the operator to set the specific parameters for each subject being tested. “No”  17  returns the user to the previously displayed GUI. 
     FIG. 9 is a GUI that appears on screen  23  to determine whether the professional is ready to verify the sensing of the electrodes attached to patient  35 . “Yes”  36  will commence the sensor verification. “Cancel”  30  will return the operator to the previous screen. If default protocols are to be used on the patient, then the operator need not define the test parameters. The system will get these standard parameters from the internal disk (not shown) of computer  27 . 
     If “Cancel”  30  is selected on the GUI of FIG. 7, any changes will be discarded and the performed test function will cease. If “OK”  36  is selected on the GUI of FIG. 7, the GUI of FIG. 8 will appear. The medical professional will select “Yes”  11  if the system is to use the standard protocol stored internally. 
     In a particular embodiment of the subject invention, prior to acquiring test data for a particular test, the computer-implemented software will acquire data for a 10-second interval, displaying and indicating detected R-waves or QRS complexes (see FIG.  31 ). This process allows the operator to confirm the placement of lead system  12 , and the sensitivity settings that appear in the GUI of FIG.  7 . If the test data is not completely satisfactory to the operator, the steps represented in FIGS. 7,  8 ,  9 , and  10  may be reiterated to allow the medical professional to reposition the leads, if necessary, to provide for optimal sensing and signal amplitude. During data acquisition, a window depicting the data being acquired appears. An exemplary display of this graphical depiction of acquired signal  47  appears in FIG.  10 . After the typical 10-second acquisition time, the GUI of FIG. 11 or FIG. 12 may appear. The GUI of FIG. 12 gives the operator the opportunity for another approximately 10-second data acquisition period. If software-detected problems occur during data acquisition, a GUI such as the one displayed in FIG. 11 may appear, notifying the operator of potential problems. These features give the operator more control over the testing procedure, and advantageously provide for error control. 
     Typically, in one preferred embodiment of the invention, an auditory beeping occurs with R-wave acquisition. If no R-wave beeping occurs or if poor signal amplitude is noted, adjustments in the leads may again be required, and sensing verification should be repeated via the GUI of FIG.  12 . 
     In situations where the operator is not performing standard protocols, the system will allow the operator to interactively set the pulse position. FIG. 13 is a graphical depiction of pulse  59  on display area  39 . Under these circumstances, the operator may use the cursor keys on the keyboard (not shown), coupled to computer  27  (not shown in FIG.  13 ), to position the pulse location using an average of the QRS complex signals received during sensing verification. 
     In one preferred embodiment, the final step in the performance of the test sequence function involves performing and recording the test. Prior to performing and recording the test, the software will represent the GUI prompt of FIG.  14 . This will allow the operator to control the timing of the test to ensure that both patient  35  and the operator are ready to proceed. 
     When the “OK”  36  selection is made from the GUI of FIG. 14, the GUI of FIG. 15 is generated, graphically depicting the R-wave  34  in realtime. If “Cancel”  30  is selected, the operator is returned to the previous screen. The system is configured to emit an audible beep synchronously with each R-wave sensed. As indicated on the GUI of FIG. 15, pressing any key of the computer keyboard will halt the performance test sequence. If a key is depressed during the test sequence, the GUI notification screen of FIG. 16 appears, notifying the operator what has occurred. 
     This invention anticipates that several other events may occur that would halt acquisition, and similar GUIs to the GUI depicted in FIG. 16 will report such termination of the test procedure. For example, if R-wave sensing is indicated at a rate greater than 180 beats per minute, the test will automatically be halted. Further, if the invention is having difficulty sensing the R-wave, or the R-wave is in any way irregular, the test will be halted. If the test is interrupted during the execution of a test sequence, the sequence may be restarted at the beginning of the interrupted test by selecting “Yes”  11  from the GUI notification screen of FIG. 17, which will be displayed after the test sequence is halted. Selecting “No”  17  from the GUI of FIG. 17 causes the system to return to the main menu screen of FIG.  4 . If any of the remaining menu items in drop-down menu  48  are selected, a shortcut to a previously-described procedure is executed. If “Quit”  19  (see FIG. 5) from Testing drop-down menu  48  is selected, the software program is closed. 
     FIG. 18 shows the View drop-down menu  55  engaged. View drop-down menu  55  provides access to functions required to select viewing options for data acquired or loaded from disk. Each test performed by the subject of the invention records 3 channels of data. The placement of electrodes (see FIG. 2) allows these signals to record far-field ECG in roughly orthogonal directions. It is recognized that the terms “ECG” and “ECG data” encompass electrocardiograms and similar data measured, generated, or reported by all means, including by use of the devices and methods disclosed herein. Referring again to the electrode placement, this advantageously provides for a data representation that defines the signal in three dimensions. Axes have been labeled X, Y, and Z. The X signal is recorded, for example, from left lead  1  to right lead  2 , with left lead  1  being the positive direction. The Y signal may be recorded from neck lead  5  to leg lead  6 , with neck lead  5  being the positive direction. The Z signal may be recorded from back lead  4  to sternum lead  3 , with back lead  4  being the positive direction. Other configurations may be possible, depending upon the judgment and needs of the patient and operator. In addition to the three required signals, at least two additional signals are preferably calculated. The X, Y, and Z signals are combined to produce a magnitude and direction signal. A magnitude signal can be used to detect signal variation independent of direction. A direction signal can be used to detect signal variation independent of magnitude. The upper portion of View drop-down menu  55  contains selectable options for each of the signals X  100 , Y  102 , and Z  104 . The options appear checked on the GUI when they are selected. These selections allow the medical professional to select which signals are displayed during certain viewing modes. The lower portion of the pull-down menu contains the viewing modes. Each mode allows the user to view the current data set in a different way. The viewing modes, as they appear on dropdown menu  55 , are “View Full Resolution,”  119 , which displays the X, Y, and Z signals at high resolution on monitor  23 ; “View 2 Minute Screen”  123 , which displays a selected signal compressed into two minutes per screen; and “View QRS Change”  125 , which displays the selected signals with normal average, biased average, and difference depictions. Selection of “Vector Angle”  139  displays the angular velocity and direction change of the average signal. “Position Bias Pulse”  111  displays the average of the selected signals, along with an indicator of pulse position. This advantageously allows interactive positioning of stimulation by the medical professional performing the diagnostics. 
     “Signal Averaged ECG”  135  displays signal-averaged ECG information for normal, biased, and difference signals. Typically, in the application of signal-averaged ECG  135 , of primary importance to the medical professional is the flat area immediately following the QRS complex, ST segment  133 . ST Segment  133  is targeted because of its lack of signal in normal people (see FIG.  31 ). This lack of signal allows the recognition of the presence of very small-amplitude signals that can occur in people with conduction problems indicative of a susceptibility to arrhythmia or other cardiac tissue abnormality. Further, abnormal signals may also exist within the QRS and be masked by the higher-amplitude signal present there. Since this invention has the ability to perform comparative analysis between stimulated and non-stimulated beats, a much greater sensitivity may be achieved in areas where a higher natural signal is also present. Additionally, by examining various areas of the QRS complex, information regarding size and position of conduction alteration may also be evident. 
     If “Options”  128  menu selection is made from View drop-down menu  55 , the GUI of FIG. 19 is displayed. “Option”  128 , which is selectable by the GUI, is represented in FIG.  19 . This function allows for better interpretation of the data accumulated. The “High-Pass Cutoff” option  60  of the GUI in FIG. 19 can be set to use a fast-fourier transform (FFT), to filter out frequencies lower than those indicated prior to averaging. A zero setting disables high-pass filtering altogether. Low-pass cutoff  94  uses an FFT to filter out frequencies higher than those indicated prior to averaging. A setting of 1,000 disables low-pass filtering. Advantageously, lead effective modeling (LEM) can be selected in the GUI represented in FIG.  19 . If LEM box  96  is checked, in a preferred embodiment, a 20 millisecond model of the impulse artifact is constructed, based on the first four simulations. This model is subtracted from subsequent simulations to reduce artifact in the displayed information. Any voltage shifts created during stimulation are also modeled and removed. LEM and this correction algorithm greatly reduce artifact created by stimulation. A muscle response correction algorithm may also be implemented by the invention to advantageously correct for signal artifacts during stimulation and acquisition cycles. Using this technique, stimulation is provided to the patient within an LEM time period between the T and P-waves, at the beginning and periodically throughout the stimulation and acquisition process. Response to the stimulations is determined up to about 50 milliseconds for each stimulation. LEM is then created by combining the response of the stimulations during this period to generate a response signal, whereafter the signal is used to mathematically attribute noise generated by electrical artifact and muscle activity. Also GUI selectable is a “60-Hz Notch FFT Filtering”  86  option, which advantageously filters out frequencies at the 60-Hz rate prior to averaging. Accumulation Start time  88  and End time  89  can also be input on the GUI indicated in FIG.  19 . Accumulation Start time  88  controls the starting range for the accumulated difference measurement on the average screen. The Accumulation End setting  89  controls the ending range for the accumulated difference on the average screen. An exemplary result of selecting “View Full Resolution” mode  119  is depicted in FIG.  20 . Signal characteristics X  167 , Y  173 , and Z  177  are graphed independently. Again, status bar  37  indicates the various selected parameters previously discussed. 
     Individual QRS status may be determined from the GUI of FIG.  21 . The various options in the QRS Status window  97  are as follows: if the status indicated is “Biased,” that means that the QRS complex has a stimulation associated with it. If it is “Normal,” the QRS does not have an associated stimulation. The parameter “Valid” in status window  97  means that the QRS has past selection criteria which is included in the averaging. If the LEM stimulation is indicated (not shown), this means that the QRS complex is used for LEM. If “low correlation” is indicated (not shown) in status window  97 , the QRS complex was too low and, therefore, was not used in the averaging. If there is a “Bad Interval” indication (not shown), then the preceding or following interval changed by greater than 300 milliseconds. If a “high-rate” status indication is indicated (not shown), the pulse rate exceeded 180 beats per minute and the QRS complex was not used in the averaging. If “manual exclusion” is indicated (not shown), that means that the QRS complex was manually excluded by the operator. If “Bad pulse Positioning” is indicated (not shown), the pulse position exceeded the tolerance set by the medical professional or the default tolerance. Further, it is possible to manually include or exclude a particular QRS from the averaging statistics by using the “Include”  162  and “Exclude”  168  selection buttons on the GUI of FIG. 21. A previous QRS complex may be viewed by selecting the “prior QRS” button  142 . The next QRS complex can be viewed by the selection of the “Next QRS” button  143 . 
     An exemplary result of selecting “View 2 Minute Screen”  123  is depicted in FIG.  22 . The 2 Minute Screen mode allows the medical professional to view a selected channel in an overview mode. In this mode, a two-minute portion of the selected channel  138  is displayed on display area  39 . R-wave correlation points and stimulation points are indicated on the display area of FIG.  20 . R-wave correlation points are longer, white indications (not shown) above the waveform. Stimulation points are red indications (now shown) below the waveform. Note that both Full Resolution  119  and View 2 Minute Screen  123  modes display the current start and end time for the displayed portion of the test on status bar  37  at the bottom of the relevant GUI. Advantageously, as the operator scrolls through the data, these values change to indicate the portion of data currently being displayed. 
     An exemplary result of selecting “View QRS Change”  125  mode is depicted in FIG.  23 . In FIG. 23, the upper graph  61  shows the average of all nonbiased QRS complexes. The middle graph  65  shows the average of all biased or stimulated QRS complexes. The lower graph  67  is the difference graph that shows the difference between the normal and biased waveforms. Statistics identifying the accumulated area under each curve are displayed on the right. A double-end arrow  33  on the lower graph indicates the range over which the statistics were generated. The end points can be adjusted in the view options window. The Difference graph contains cumulative Difference results along the bottom of each 10 millisecond region, based on the magnitude signal. FIG. 24 depicts the Vector Angle GUI. Vector Angle mode displays angular information  151  not reflected in the magnitude signal. The Vector angle mode displays changes in the direction of the electrical signal, whereas the Magnitude mode displays changes in the amount of electrical signal. 
     When the Signal Averaged ECG menu selection is made from View drop-down menu  55 , the GUI of FIG. 25 is displayed on computer screen  23 . The various graphs represent the Signal Averaged information for the Normal  43  and Biased  44  QRS complexes, along with the Difference  45  between the two. Standard QRS, LAS  40  and RMS  40  calculations can be made. Noise threshold is displayed along with the standard deviation of the noise, as can be seen on the GUI of FIG.  25 . 
     Another drop-down menu  46  is the Data drop-down menu  58 . Data drop-down menu  58  provides access to functions required for loading previously acquired data from storage, such as a hard disk located in computer  27 , or from removable storage, such as a Zip™ disk or other removable storage media. Configuration of protocol steps is also supported here, along with typical backup and restore functions. 
     FIG. 27 is a GUT depiction of an exemplary menu for stored data. The date  16  and time  20  of acquisition, the identification  38 , name  32 , age  53 , gender  54 , bias information  63 , R-wave sensitivity, and valid count  71  are all identified for reference, as can be noted in the upper area  14  as depicted in FIG.  27 . Selecting “Load From Internal Disk” option  126  from drop-down menu  58  reveals the GUI depicted in FIG.  28 . The GUI of FIG. 28 depicts a variety of test data  57  that can be selected. 
     If “Load Protocol Step”  131  is selected from the drop-down menu, the GUI of FIG. 29 is displayed. This function loads an identified protocol step  69  into the current test configuration. The GUI dialog box allows the operator to identify the protocol step to load. Current patient information is not changed. To select a test configuration as a protocol step, the GUI of FIG. 30 is used. The protocol step is entered into “Select Protocol Step” window  158  of the GUI, and “OK”  36  is selected to save the step. 
     Selection of “Restore”  114  from Data drop-down menu  58  restores data from an external media, such as a Zip™ disk, back to the internal hard drive of computer  27 . Further, using the “Export”  195  command, data can be exported to certain spreadsheet software programs. 
     The “Append To Stats” option  163  can be selected to append the statistics of the current configuration parameters to the file. Advantageously, this option allows all test data sets in the current drive and directory to be processed using the current processing parameters and appended to the selected text, or .TXT, file. This useful option allows for batch processing and results based on altered settings. 
     Another menu  46  is Help drop-down menu  60 . Full index and search capabilities of Help information is available. Further, on-line help, such as information gatherable through the Internet, is also anticipated. 
     A high-level operator flow chart for the software described above appears in FIG. 43. A typical embodiment of the method of using the software begins at the Attach Leads To Patient stage  280 . As described above, the operator will then Invoke Testing  282  and Input Patient Information  284 . If only a single test is desired, path  287  is taken, wherein the operator has a chance to Define Test Parameters  291 . Otherwise, the operator has the choice of selecting All Tests Desired  289  and proceeding directly to Verify Sensing  293 . If Verify Sensing  293  is Bad  295 , then the lead positioning can be adjusted  297 , and the verified sensing retried  294 . Once the sensing is Good  198 , the test parameters are loaded and the test is performed  288 . Once the test is completed  292 , there is a chance for the operator to see if more tests need to be performed  296 . If “Yes”  290 , then the next predefined tests are loaded  286 , and the operator is returned to Test Parameters Loaded and Test is Performed  288 . If no further tests are to be formed at the  296  state, the “No” path  299  is selected and the test is completed and leads are disconnected  300 . 
     FIG. 44 is a depiction of the test control and data acquisition software flow chart. Raw data received from lead system  12  is received at the Realtime Test Control and Monitor Software  310 , along with Realtime R-Wave Indicators  306 . Realtime Test Control and Monitor Software  310  then controls and relays this information to generate GUIs to make a realtime display  312  on monitor  23 . Inputs from the control system can control other test features, as well, such as User Abort Control  304  and the user&#39;s ability to perform Test Configuration  308 . Realtime Test Control and Monitor Software  310  can also send the Raw Data  303  to storage  313 , and save Subject &amp; Test Information  315 . 
     FIG. 45 depicts the software flow charts of the post-processing software. Annotation and post-processing control  332  controls View Options  325  as described above, and subject and test information retrieval from storage  320 . Raw data from storage  326  is retrieved and analyzed for R-wave detection  332 . If LEM generation  330  is requested, then LEM Correction  334  will be performed, and Correlated QRS Alignment  336  performed. Then, one to typically four processing options may be selected. Average Processing  340  can be selected for the data to be analyzed after being filtered through filtering process  338 . Then the options of displaying  350  or saving  355  the data are available. If variance processing  342  is selected, the results may be displayed  350  or saved  355 . Similarly, if Power Spectrum Processing  344  is selected, the results may be displayed  350  and/or saved  355 . Also, Direction Vector Processing  346  may be selected and, again, the resulting information can be displayed  350  and/or saved  355 . 
     FIG. 46 displays the lower-level flow diagram, more particularly, the stimulation timing software and the switch, shunt, relay, and stimulation control features that allow for efficient subpacing stimulation signals to be timely and efficiently administered, as well as to facilitate the ability of the invention to make fast recovery to prepare for the next QRS complex event. Raw Data Stream  370  is filtered by Filters  368  and is sent to Realtime LEM Generator  360 , and any realtime LEM correction is made at  366 . Realtime R-wave detection is determined at step  364 ; and, if detected, the realtime R-wave indications are passed on at  362 . Realtime R-Wave Detection  364  is also linked with the Stimulation Timing Software  352  that determines the timing of the subpacing electrical pulse. Stimulation Timing Software  352  interacts with the switch on the relay and the stimulation control portion of the software  358 . The computer interconnects to the electronic interface as shown at  372 . 
     FIG. 36 depicts an exemplary series of QRS complexes  130 , or R-wave events. As can be seen, interval  144  is defined by that interval from the beginning of one QRS complex to the beginning of the next QRS complex. During the testing provided by this invention, a Pulse-Delivery Point  110  is determined by the invention, and a subpacing current is delivered, typically as shown in FIG.  36 . There is then the anticipated R-wave  115 , based upon two previous R-waves. In one preferred embodiment, the response to the stimulation is determined for a period of up to about 50 ms after the stimulation. Any change in the characteristics of the QRS complex  130  following delivery of the subpacing pulse at delivery point  110  can be used in the diagnosis of a patient&#39;s susceptibility for arrythmia and cardiac tissue abnormality. A desired pulse position with respect to a detected R-wave is configured by the operator. When the intended position and time with respect to a detected R-wave is at or following the R-wave, then the device delivers a pulse after an appropriate-length delay following the most recently detected R-wave. When the intended position and time with respect to a detected R-wave are before the R-wave, then the device uses the previous R-interval  144  to determine an estimated time for delay by subtracting the desired amount from the R to R interval  144 . The device then delivers the pulse after the determined delay following the most recently detected R-wave. The computer software is controlled with simulation and data acquisition during testing. During each test, the software delivers stimulation to alternating QRS complexes, based on realtime R-wave detection. Signals are recorded from lead system  12 , along with the stimulation and R-wave detection locations. This is monitored and is terminated when the appropriate number of pulses have been delivered in the region identified in the test parameters. 
     Another process for arrythmia detection is that of t-wave alternan analysis. This process involves looking for alternations from beat to beat in the signal produced during the t-wave portion of the heart signal. The t-wave is the portion of the heart signal that follows the QRS “contraction” (see FIG. 31) of the heart. The QRS area is called depolarization. The t-wave is called repolarization because the cells are electrically preparing for the next depolarization. T-wave analysis involves computing the ‘power’ of each t-wave and looking for alternations in this power from beat to beat. This phenomenon tends to increase in people prone to arrhythmia. The use of t-wave alternan analysis with the previously-described technique of subthreshold stimulation is anticipated by this invention. 
     An overview of the operation of this invention can be seen in FIG.  33 . Sensing Leads  202  pass received Signals  248  to the fast-recovery amplifier, at which time the Signals  248  are passed to the Analog to Digital converter  208 . Thereafter, Data  250  is used to determine R-wave Detection  237  and for LEM modeling  215 . Data  250  is also capable of going to Storage  218 , and is further used for Post-Processing  240 , where data  250  is eventually displayed to computer monitor  23 . During the fast-recovery amplifier stage  254 , Blanking Control  212 , through Control  253 , is used to compensate for blanking. This blanking control is initiated through the Software and Hardware Control Logic  234  via Control  253 . Control  259  controls the R-wave detection  235  as it is passed to the Software and Hardware Control Logic  234 . Software and Hardware Control Logic  234  further controls a Shunt Control  225  via Control  254 ; and Control  257  controls Current Controlled Driver  221 . Hardware and Software Control Logic  234  passes Data  250  to the Digital to Analog Conversion  228 , thereafter passing those Signals  255  to the Current Controlled Driver  221 . At the appropriate time, Signal  255  is delivered to Stimulation Leads  206 . Post-Processing  240  also performs LEM modeling  215 , Digital Filtering  243 , and Statistical Calculations  246 , described in more detail below. 
     A significant part of the subject invention is the amplifier and driver circuitry located in electronic interface  18 . Electronic interface  18  provides amplification of signals received from lead system  12  and amplifies those signals to a level of impedance readable by the computerized data acquisition/control system, such as computer  27 . Electronic interface  18  also takes control signals from the computerized data acquisition/control system, such as computer  27 , and provides stimulation into lead system  12 , as described above. The amplifier circuitry is designed to record lead signals that occur immediately following the injection of energy into the lead system. The recording typically occurs within only several milliseconds of the injection of energy. Fast recovery is important to the system because of the need to sense electrical information very shortly after a stimulation. In one preferred embodiment shown in FIG. 37, each vector X, Y, and Z has its own amplifier, X amplifier  155 , Y amplifier  165 , and Z amplifier  175 . Stimulator  180  controls subpacing pulse delivery in conjunction with computer  27 ; and the software Power Conditioning Circuit  182  powers amplifiers  155 ,  165 , and  175  supplying Stimulator  180  with subpacing current. FIG. 38 is a wire-level diagram of FIG. 37, illustrating this advantageous design. 
     To provide for such fast recovery, several methods are employed. The sensing leads are comprised of fast-recovery material, such as tin, sodium, silver and silver chloride, or other such material know to those skilled in the art, to facilitate rapid dissipation of any energy induced by the system. Further, electronics interface  18  uses a multistage amplification scheme as known to those persons skilled in the implementation of amplifiers, with improvements for fast recovery. FIG. 38 shows a wire-level block diagram of this embodiment of electronic interface  18 . In one preferred embodiment, electronic switches are placed between amplification stages, which are used to decouple stages within the amplifier. The amplifier must be switched into its high-impedance mode, with appropriate time allowances for all electrical switching to be completed prior to the application of any energy to the stimulation leads. Similarly, when switching back to normal impedance mode, appropriate timings must be used to ensure that all stimulation energy is completely terminated prior to lowering the amplifier impedance. This timing must account for any engaging or disengaging delay in both the amplifier and energy delivery circuits. When the amplifier is in its normal- or low-impedance mode, it has a capacity to store up charge in a very short period of time. Therefore, application of stimulation energy, however short, in this mode will greatly increase undesirable artifact. Therefore, timing is critical in decoupling the amplifier to reduce artifact. Advantageously, switch timing is software-controlled in one preferred embodiment of this invention. Other timing means are known to those skilled in the art. Filtering is implemented by this invention to filter the acquired signal to eliminate possible high frequency, switch-related artifacts. 
     An additional clamping circuit is also employed to aid in the reduced recovery time during stimulation. As can be seen in FIG. 39, an electronic track and hold switch  160  is placed between two stages of the amplifier. Track and hold switch  160  remains closed during stimulation, and in a preferred embodiment, a blanking period following stimulation. FIG. 39 is a block diagram/flow chart of the operation of the isolated fast-recovery EKG amplifier. Differential input signal  261  enters the Differential First Stage Amplifier Circuitry  264 . The signal is thereafter controlled by Clamping Circuit  117 . The signal is then conditioned by Bandpass Gain Stage  267  and is regulated by Impedance Switching Track and Hold Circuitry  160 . As depicted in FIG. 39, Switch Control  277  and Switch Isolation circuitry  275  control the timing of the signal. At the appropriate time, signals pass to Low Pass circuitry  269  and then to Final Gain Stage  271  and Isolation Stage  273 . Finally, the amplified signal leaves the fast-recovery EKG amplifier as Amplified Signal  278 . 
     FIG. 40 is a schematic of the fast-recovery EKG amplifier. FIG. 40 depicts the circuitry implementing the flow chart of FIG.  39 . As can be seen, differential inputs  183  connect to the differential first-stage amplifier circuitry  187 . The next stage is clamping circuitry  184 , which is in electrical communication with the bandpass gain stage  185 . Next are the switch-and-hold circuitry  181 , low-pass filter stage  189 , and final gain stage  188 . Isolated circuitry  186  and switching circuitry  181  are also depicted in FIG.  40 . 
     FIG. 32 is a block diagram of the switching circuit. A clamping circuit is also added within the preswitch stages. The clamping circuit is designed to engage when the input signal is greater than about plus or minus 5 mV. When switch  70  is closed, the circuit behaves as a typical amplifier, using the reference lead as a body surface reference point for amplification of the differential signal between the positive and negative leads. Advantageously, this reference point is utilized during periods of blanking of the input signals. The clamping circuit remains inactive for input signals of plus or minus 5 mV. This allows amplification of normal skin surface ECG signals. During stimulation, the switch electronically disengages the amplification stages from each other. While open, switch  70  itself provides a hold function that holds constant the signal level for all postswitch stages  74 . Switch  70  also decouples the reference signal from the preswitch stage  77 . This decoupling advantageously prevents the preswitch stage from accepting any transient energy present during stimulation. In addition, to switch  70 , clamping circuit  62  engages when the input signal of greater than plus or minus 5 mV occurs. This clamping circuit  62  uses reference lead  9  to measure a baseline. A baseline shift is caused by the remnant charge left in the patient&#39;s body following the stimulation, shunting and modeling cycles performed by a preferred embodiment of the invention. This remnant charge equalizes over time at an exponential rate referred to as baseline decay. Compensation for baseline effects can be done by subtracting a non-stimulated waveform from a stimulated waveform. Further, a baseline shift with a time constant decay may also be utilized. The decay rate may be modeled by sampling the decay rate over a predetermined interval, for example, about 10 ms. The decaying baseline shift can then be mathematically removed from the acquired data. Advantageously, the decaying baseline shift may be removed for predetermined intervals, for example, intervals up to about 300 ms. Baseline noise can advantageously be reduced by filtering and statistical noise reduction by this invention. Whenever the input signal deviates from this baseline by more than 5 mV, the internal amplification stage is held at that level. This further reduces the effect of transient voltages generated during stimulation. These two features work together to keep the amplifier stages as close as possible to their prestimulation values, advantageously providing a very fast recovery time. An additional circuit in postswitch stage  74  provides a filter that eliminates any possible high-frequency, switch-related artifact that may occur. This is required because of the nature of the switch employed. This recovery technique is incorporated within the amplifier in one preferred embodiment of this invention. 
     FIG. 41 is a flow chart/block diagram of the isolated driver section of the subject invention. This is additional circuitry located within electronic interface  18 . This driver section depicted in FIG. 41 has the characteristics to shape the energy delivery pulse to reduce rise-and-fall slopes, thereby reducing induced artifact signals. Further, the isolated driver depicted in FIG. 41 provides for shunting of any charges built up as a result of energy delivery. Shunting means may include switching from a high-impedance path to a low-impedance path for a short period of time to dissipate unwanted voltage that is present. The switching between high and low impedances is designed to occur within a time of less than 1 ms. Typically, high impedance is greater than about 5,000 Ohms, and low impedance is less than about 500 Ohms. This shunting means can be connected between more than one energy delivery lead. Further, the driver employs a constant current circuit, thereby allowing control over energy delivery and varying lead or physiological impedances. As can be seen from FIG. 41, the Current Control  197  communicates with Isolated Driver Circuitry  193 . Advantageously, there is also safety circuitry, which includes Safety Fuse  199  and Isolated Safety Relay  198 , controlled by Safety Relay Control  192 . Shunt Control  196  then controls the Isolated Shunt Circuitry  170 , which timely delivers the subpacing current output  194  to the subject. 
     FIG. 42 is a schematic level of an exemplary isolated driver section. Blocked off on the schematic are Isolated Driver section  193 , Safety Fuse  172 , safety switch  174 , and shunting circuitry  170 . 
     Additional techniques and means for improving sensing and analysis of cardiac signals will now be discussed, including both stimulated as well as non-stimulated signals. Such techniques and means include: wavelet decomposition, alternative or passive shunting, detection of ECG alternans, stimulation of alternans behavior, detection of differences between natural and stimulation induced alternans behavior, cardiomyopathy detection techniques, body surface shunting synchronous with the R-Wave on Signal Averaged Electrocardiogram, subthreshold stimulation without capture to reduce the stimulation threshold causing changes to the action potential of a subsequent suprathreshold stimulation with capture, Wedensky transthoracic stimulation, Wedensky phenomenon within the late potential region, wavelet analysis of subthreshold stimulated and control Signal Averaged Electrocardiograms in healthy subjects and ventricular tachycardia patients, QRS complex alternans detected by wavelet decomposition of Signal Averaged Electrocardiograms, and QRS background noise differentiation. Each such means will now be discussed, including reference to FIGS. 47-57. 
     Wavelet Decomposition is a mathematical analysis allowing the study of a particular signal of interest in the presence of other signals. The analysis allows itself to be tuned towards higher sensitivity to one or more particular type(s) of waveforms while reducing sensitivity towards another. This type of analysis is particularly useful when used on ECG data. ECG data can contain specific environmentally present electrical noise, for example 50 Hz or 60 Hz. ECG data may also contain broadband constant or intermittent noise produced by local sources of electromagnetic interference. The dynamics of the ECG waveform itself (as it is produced by the heart) can be defined in both frequency and amplitude. Research has defined such an analyzing waveform for use with Wavelet Decomposition in studying ECG data. This application includes the use of such wavelet decomposition to analyze either the natural ECG or stimulated ECG data produced by an ECG device, including the devices disclosed herein. Also included is the use of wavelet decomposition to analyze combinations of natural ECG or stimulated ECG data produced by an ECG device, including the devices disclosed herein. 
     This application discloses, inter alia, the methods and apparatus of using the stimulation electrodes (or any large area surface electrodes) in an ECG device, including the devices disclosed herein, as a method of enhancing sensing of cardiac condition. First, these electrodes can act as a shielding mechanism to enhance the sensing of ECG signal. The presence of a large area electrode acts as an electrical shield allowing better sensing of cardiac signal. The use of such an electrode is identified and claimed here. 
     Shunting is a technique of dissipating unwanted voltage. Use of the devices and methods disclosed herein involve the delivery of energy followed by the shunting of the stimulation leads as a means of reducing the artifact caused by charge remaining on the lead system. This shunting process also has application when no energy is delivered through the leads, and is interchangeably referred to herein as alternative or passive shunting. 
     By passively changing (shunting) the potential of a large area of the body, an impedance modulation in the body can be realized. The generation of the surface ECG from the heart involves the current flow from cell to cell as depolarization recruitment progresses. This current vector multiplied times the local resistivity gives the local electrical field. The components of that on the skin are what is called the ECG. By pulsing the shunt across the chest it is possible to modulate that resistance (i.e., “impedance modulation”). This is similar to changing the angle of view of the cardiac signal. This altered measurement can also be compared against the non-shifted measurement. 
     Also disclosed herein is the process of shunting these or any larger area surface electrodes together to effectively provide an isopotential at the skin surface. This action can be viewed as “passive stimulation.” It can shift the body potentials and possibly alter conduction pathways to allow better sensing of the cardiac condition. This altered measurement can also be compared against the non-shifted measurement. The use of either “impedance modulation” or “passive stimulation” and its effect on the QRS signal is thus disclosed herein. 
     Alternant behavior consists of the changing of cardiac signal in a modal fashion. That is, one beat will have certain characteristics, the next will have different characteristics, and the following will have characteristics like the first. The process of averaging together alternate beats used in an ECG device, including the devices disclosed herein, allows the measurement of the natural ECG alternan behavior. The extent and change of this measurement can be a measure of cardiac condition. The use of this measurement as an indication of cardiac condition is disclosed and included in this application. 
     By averaging together alternate beats, the systems and methods disclosed herein allow the measurement of alternan behavior. This method can be useful in the determination of cardiac condition. Thus, this application discloses use of the systems and methods to achieve stimulation-related changes in alternan behavior, or shunting/impedance shifting-related changes (passive stimulation in alternan behavior as a method for detecting cardiac condition). Furthermore, the differences between natural alternan behavior and stimulated alternan behavior can also be useful in determining cardiac condition. This application discloses and includes the use of the differences between these behaviors as an indicator of cardiac condition. 
     A further use of the devices and methods disclosed herein is to assess conduction pathway changes within the heart by examining the changes in ECG while stimulating and not stimulating the myocardium. Another use disclosed herein is to detect non-conduction related abnormalities of the heart including, but not limited to, cardiomyopathy. The changes invoked by the process of stimulating, shunting, or examining alternate beats could also be used to determine the extent of physical myocardial abnormality. Stimulation related changes, shunting and impedance shifting related changes (passive stimulation), or changes due to average of alternate beats as a method of detecting non-conduction related abnormalities are disclosed and included herein. 
     Applicants have further discovered improved means for signal analysis by analyzing the effect of body surface shunting synchronous with the R-wave on Signal Averaged Electrocardiograms by comparing the differences between normal subjects and patients with ventricular tachycardia. This study investigated the effects of creating a body surface short circuit synchronous with the R-wave on the spectral profile of signal averaged electrocardiograms. 
     In 35 patients with EP inducible ventricular tachycardia and in 30 healthy volunteers, 60 to 200 QRS complexes were digitally recorded using orthogonal leads. Synchronous with on-line R-wave detection, two surface patches corresponding to the orthogonal Z lead (a precordial patch and a left dorsal subscapular patch) were electrically connected with negligible impedance for 2 ms. The QRS complexes recorded in this way were averaged and compared with the same number of averaged QRS complexes recorded without surface shunting. Both high-gain signals were decomposed with 53 scales of Morlet wavelets of central frequencies 40 to 250 Hz and vector magnitudes of wavelet decompositions were constructed. The differences between these decompositions were characterized by their surface areas in windows of 0 to 10 ms, 10 to 20 ms, and 20 to 30 ms, etc., after surface shunting. 
     The area difference was substantially greater in healthy volunteers, as shown by the light bars in FIG. 47, than in VT patients (dark bars) both immediately, i.e., 0-10 ms after surface shunting (p&lt;0.04) and 10 ms later (p&lt;0.03) but not later (p=0.4 at 20 ms later, and p=0.5 at 30 ms later). From this research data, it may be concluded that short circuiting the body surface produces both recording artifact and physiological stimulus affecting the depolarization sequence. This stimulus is very short lived and is more marked in healthy hearts than in VT patients who are probably less susceptible to minor electrical provocations. 
     Applicants further compared high-gain electrocardiographic evidence of Wedensky Phenomenon in healthy subjects and ventricular tachycardia patients. Of course, it is known that Wedensky Phenomenon is the effect of a subthreshold stimulation without capture that reduces the stimulation threshold and changes the action potential of a subsequent suprathreshold stimulation with capture. 
     To investigate whether this phenomenon can be documented after transthoracic subthreshold stimulation (2 ms. pulse of 5 to 40 MA between surface precordial and subscapular patches delivered synchronous with R-wave detection), 60 to 200 subthreshold stimulated QRS complexes were signal averaged and compared with the same number of average non-stimulated complexes recorded during the same experimental session. The electrocardiographic recordings were obtained with standard orthogonal leads. In order to detect even minor changes within the QRS complex, each lead of both stimulated and control averaged complexes were wavelet decomposed (53 scales of the Morlet wavelet with central frequencies of 40 to 250 Hz). The wavelet residuum corresponding to the Wedensky Phenomenon was obtained by subtracting the vector magnitude wavelet decomposition of the control QRS from the vector magnitude decomposition of the subthreshold stimulated QRS. The surface of the residuum was investigated in windows of 1 to 25 ms following the stimulation. The test was performed in 35 patients with EP inducible ventricular tachycardia and in 30 healthy controls. 
     The wavelet residuum showed sharp increase in the spectral power of the stimulated complex that was significantly more marked in healthy volunteers (p&lt;0.01) than in VT patients. This is shown in FIG. 48, in which there is 20 ms stimulation, and in which full circles are VT patients, and empty circles are control patients. This shows that Wedensky phenomenon induced by an external transthoracic subthreshold stimulation can be documented in man and differentiates VT patients from controls. 
     In further investigation, patients with electrophysiologic documented ventricular tachycardia (n=35) and healthy controls (n=30) were subjected to a subthreshold external stimulation between precordial and left subscapular patches. Stimuli of 5, 10, 20, and 40 ma were delivered for 2 ms synchronous with R-wave detection. 60 to 200 subthreshold stimulated QRS complexes were averaged and compared with the same number of non-stimulated complexes. Vector magnitude wavelet decompositions (53 scales of central frequencies 40 to 250 Hz) were obtained for both stimulated and non-stimulated complexes and their difference characterized the Wedensky Phenomenon numerically. The surface area of the 3D envelope of the wavelet residuum was measured in a window ±5 ms from the R peak (stimulation moment) and in surrounding 10 ms windows. 
     The wavelet residuum showed a sharp increase of the surface of the 3D spectral envelope at and after the stimulation that was more marked in healthy volunteers than in VT patients, as shown in FIG. 49 in which 40 ma experiments were conducted, and full circles are VT patients, and open circles are control patients. The maximum changes in wavelet residuum increased with stimulation subthreshold energy: 5 ma: control 1993±181 technical units, VT patients 1488±159; 10 ma: control 2151±200, VT patients 1543±154; 40 ma: control 2746±332, VT patients 1842±177, i.e., all were statistically significant. Thus, externally induced Wedensky phenomenon shows a dose response that is more marked in healthy volunteers than in VT patients. 
     Wedensky Phenomenon within the late potential region was analyzed utilizing dose-related separation of patients with ventricular tachycardia from healthy controls. Patients with EP documented ventricular tachycardia (n=35) and healthy controls (n=30) were subjected to a subthreshold external stimulation between precordial and left subscapular patches. Stimuli of 5, 10, 20, and 40 ma were delivered by 2 ms after a 20 ms delay following a realtime R-wave detection. 60 to 200 subthreshold stimulated QRS complexes were averaged and compared with the same number of non-stimulated complexes. Vector magnitude wavelet decompositions (53 scales of central frequencies 40 to 250 Hz were obtained for both stimulated and non-stimulated complexes and their difference characterized the Wedensky Phenomenon numerically. The surface area of the 3D envelope of the wavelet residuum was measured in a window 20±5 ms after the R peak (a window centered around the stimulation moment) and the subsequent 10 ms windows (30±5 ms after the R peak). The areas of the residuum spectral 3D envelope in these windows were statistically compared in the VT patients and healthy controls. 
     All differences were highly statistically significant, as shown in FIG. 50 (up to p&lt;0.00005), with the manifestation being more pronounced in the control group. The separation of the groups was more significant in the window around the stimulation moment that in the subsequent window and the significance decreased with increasing subthreshold stimulation energy. Accordingly, a Wedensky phenomenon in the late QRS part is brief, and VT patients are less sensitive to the phenomenon, especially at very low subthreshold energies. 
     In yet another assessment, patients with EP documented ventricular tachycardia (n=35) and healthy controls (n=30) were subjected to a subthreshold external stimulation between precordial and left subscapular patches. Stimuli of 5, 10, 20 and 40 ma were delivered for 2 ms either simultaneously with the R-wave or 20 ms after the R-wave. 60 to 200 subthreshold stimulated QRS complexes were averaged and compared with the same number of non-stimulated complexes (reference). Vector magnitude wavelet decompositions (53 scales of Morlet wavelet with central frequencies 40 to 250 Hz) were obtained for both stimulated and non-stimulated complexes. Local maxima of the 3D spectral envelopes were counted in 50 ms windows following the subthreshold stimulation and compared in VT patients and healthy controls. 
     In reference recordings, FIG. 51, there were no statistical differences between VT patients (shown as closed dots) and controls (open dots). In subthreshold stimulated recordings, the local maxima decreased (3D spectral envelopes became more smooth). This decrease was greater in healthy controls and with stimulation after the R-wave, FIG. 52, wherein all the differences except in experiment 10/00 were significant up to p&lt;0.001. Accordingly, subthreshold external stimulation makes the depolarization wave more uniform, mainly when delivered in the terminal QRS part in healthy volunteers. 
     Although the electrical altemans of the ST segment and T-wave has been extensively researched, the alternans of the QRS complex has generally not been investigated mainly because of difficulties in detecting it. Applicants&#39; innovations overcome such previous limitations, and allowed further assessment as follows. 
     In 35 patients with EP inducible ventricular tachycardia and in 30 healthy volunteers, 120 to 400 QRS complexes were digitally recorded using orthogonal leads. From these sequences of beats, the complexes with even and odd order numbers were separately aligned and averaged. The resulting high-gain signals were processed with wavelet decomposition (53 scales of Morlet wavelets with central frequencies of 40 to 250 Hz) and the differences between the resulting 3D spectral envelopes were computed. These created alternans-related 3D spectral envelopes and were characterized by surface areas in subsequent 10 ms windows. 
     The surfaces of the alternans-related 3D spectral envelopes were substantially larger, as shown in FIG. 53, in VT patients (full circles) compared to healthy controls (open circles). The differences between the groups were particularly marked within the initial and terminal portions of the QRS complex (p&lt;0.00005 in the 10 ms window preceding the R-wave by 40 ms). Thus, a wavelet decomposition of alternating signal averaged ECG is capable of detecting electrical alternans within the QRS complex, and the QRS complex alternans is significantly more expressed in VT patients compared to healthy controls. Also, the QRS complex alternans differs between VT patients and controls mainly at the beginning and at the end of the QRS complex. 
     Of the many improvements discussed above, it is worth noting that wavelet analysis is particularly significant. Indeed wavelet analysis is a highly reproducible method for SAECG processing which is as powerful as the time-domain analysis for the identification of ischemic VT patients. As compared to the time-domain analysis, wavelet analysis is not dependent on infarct site, and is able to distinguish post-myocardial infarction patients without VT from healthy subjects. As compared to known applications of wavelet representations, Applicants utilized much finer distinctions of scales (7 vs. 54) with a different range of middle frequencies (70-200 Hz vs. 40-250 Hz). Applicants also determined that wavelet analysis of signal-averaged ECGs is superior to the standard time-domain analysis in predicting post myocardial infarction events. In particular, this analysis identifies not only those post MI patients who are at risk of non-fatal sustained ventricular tachycardia, but also those who are at risk of sudden cardiac death. Thus, this is the first discovery of using wavelet analysis for categorical risk analysis with prospectively collected signal-averaged ECG data in an almost consecutive population of MI survivors. As such, a significant advantage of this technology is that compared with standard time-domain analysis, the wavelet decomposition of signal-averaged ECGs provides a more powerful distinction between survivors of an acute MI who are and are not at high risk of further complications. FIG. 54 shows sample data of the interdependence of time-domain and wavelet decomposition indices, in which is presented the correlation coefficient between the two techniques. The value of correlation coefficient is shown above the diagonal, and the corresponding p-values are displayed below. FIG. 55 is data representing a comparison of signal-averaged ECG indices in patients with and without follow-up events. For each category of follow-up events and for each time-domain and wavelet decomposition parameters, the table lists the averaged value in patients with and without the event. The last column (p=) shows the significance of statistical comparison of values in patients with and without events (nonparametric Mann-Whitney test). FIG. 56 shows the association of positive SAECG findings with follow-up events. For each category of two year followup events and for each of four diagnostic criteria, the table shows the number of true positive (tp) and true negative (tn) patients as well as the statistical significance (p−) of the association of events with findings of a positive signal averaged ECG analysis (Fishers exact test). Herein, CM represents cardiac mortality, PAD represents potentially arrhythmic death, SCD represents sudden cardiac death, VT represents sustained ventricular tachycardia, PAE represents potentially arrhythmic events, and ARF represents sudden cardiac death and/or ventricular fibrillation. FIG. 57 is a comparison of positive predictive accuracy of predicting follow-up events. In this figure, for each category of follow-up events and for six selected levels of sensitivity (Sen), the table shows maximum positive predictive accuracy (PPA) achieved at that level of sensitivity with time-domain indices (TD) and wavelet decomposition indices (WD) of signal averaged ECGs. The table also shows the numbers of patients for which the diagnostic criteria of both techniques adjusted for the given level of sensitivity did not agree (Discordance) divided into the number of those for which the time-domain diagnosis was correct (TD+) and those for which the wavelet decomposition diagnosis (WD+). The last column shows the statistical significance (p=) of the comparison of values of TD+ and WD+ (sign test). 
     One additional signal improvement technique involves improved noise management in the QRS realm. When sensing signals from electrodes, a certain amount of environmental background noise is unavoidable. This noise may vary in frequency and direction, causing certain electrode placements to be more sensitive to receiving it than others. The following software-based approach addresses an implementation to reduce sensitivity to this background environmental noise during the processing of data recorded from electrodes. 
     To improve alignment of QRS complexes of multiple channel ECG data (XYZ, multi-lead intercardiac, 2 lead, etc.) a mechanism which reduces sensitivity to background noise may be applied. The mechanism involves the determination of the signal level of the background noise and the signal level of the desirable signal (in the case of ECG data, the QRS). These parameters are determined for each data channel. The parameters are combined into ratios of Desirable/Background signals (hereby called D/B ratio). Channels with low D/B ratios are excluded from use during QRS alignment. Since it is possible for background noise to vary over time, an alternate implementation of this mechanism could be to assess the signal around each QRS complex for D/B ratio and exclude QRS&#39;s based on their individual ratios. 
     While the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the foregoing description. Accordingly, it is intended to embrace all such alternatives, modifications, and variations which fall within the spirit and broad scope of the invention.