Patent Publication Number: US-2015088020-A1

Title: System and Method For Interactive Processing Of ECG Data

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This non-provisional patent application is a continuation-in-part of U.S. patent application Ser. No. 14/082,071, filed Nov. 15, 2013, pending; which is a continuation-in-part of U.S. patent application Ser. No. 14/080,717, filed Nov. 14, 2013, pending, and a continuation-in-part of U.S. patent application Ser. No. 14/080,725, filed Nov. 14, 2013, pending; and which further claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent application Ser. No. 61/882,403, filed Sep. 25, 2013, the disclosures of which are incorporated by reference. 
    
    
     FIELD 
     This application relates in general to electrocardiography and, in particular, to a system and method for interactive processing of electrocardiogram (ECG) data. 
     BACKGROUND 
     An ECG procedure measures cardiac electrical potentials that can be graphed to visually depict the electrical activity of the heart over time. Conventionally, a standardized set format 12-lead configuration is used by an ECG machine to record cardiac electrical signals from well-established traditional chest locations. Sensed cardiac electrical activity is represented by PQRSTU waveforms that can be interpreted post-ECG recordation to derive heart rate and physiology and for use in medical diagnosis and treatment. 
     Within an ECG waveform, the P-wave represents atrial electrical activity. The QRSTU components represent ventricular electrical activity. Some cardiac conditions have frequency-specific content. The QRS complex in ventricular tachyarrhythmia, for instance, has a maximum amplitude at 4 Hz, while the frequencies associated with ventricular fibrillation are concentrated in the 4-7 Hz range. Cardiac vagal activity and respiratory sinus arrhythmias are seen in the 0.15-0.50 Hz range. Other frequencies may reflect other cardiac conditions. 
     Noise in recorded signals or other artifacts that do not reflect cardiac activity can contribute to an incorrect diagnosis of a patient. The main sources of noise in an ECG machine are common mode noise, such as 60 Hz power line noise, baseline wander, muscle noise, and radio frequency noise from equipment including pacemakers or other implanted medical devices. Such noise can contribute to an incorrect diagnosis of the patient. For example, electrical or mechanical artifacts, such as produced by poor electrode contact or tremors, can simulate life-threatening arrhythmias. Similarly, baseline wander produced by excessive body motion during an ECG procedure may simulate an ST segment shift ordinarily seen in myocardial ischemia or injury. 
     Current ECG over-reading software generally does not allow a user to apply an arbitrary noise filter of choice to an ECG trace; users are generally limited to a set of proprietary filters. In addition, conventional over-reading software generally fails to provide users with a way to compare the results of combinations of arbitrary noise filters, thus preventing the user from finding the most appropriate filter. This is especially relevant when trying to record the P-wave or cardiac atrial signal. 
     Therefore, a need remains for a way to facilitate real-time, interactive processing of an ECG. 
     SUMMARY 
     An ECG is displayed to a user, and a user selection of a desired portion of the ECG is received. A list of filters is provided to the user, and the user can try applying different filters to the selection by selecting of one or more sets of the filters in the list. For each of the sets, the filters are applied to digitized signals corresponding to the selection, a filtered ECG for the selection is generated based on the signals filtered by each of the sets, and the filtered selection ECG traces are displayed to the user. The filtered selections can be displayed side-by-side, allowing the user to compare the ECG traces of the selection filtered using the different sets of filters, and to decide whether application of certain filters resulted in an easily-interpretable ECG, or whether different filters need to be applied. As the result, the user can select the most appropriate filters for the selection, which facilitates removal of noise and enhancement of ECG features that were corrupted by noise or were made difficult to see due to the amplitude of the noise. In addition, by applying the filters to only a particular selection, the user is permitted to filter the selection without degrading the quality of other portions of the ECG. 
     One embodiment provides a computer-implemented system and method for interactive processing of ECG data. An electrocardiogram is displayed. A user selection of a portion of the displayed ECG is received. Digitized signals corresponding to the selection are obtained. A list of digital filters for filtering the selection are displayed. A user selection of one or more sets of the digital filters is received, with each of the sets including one or more of the filters from the list. The selected sets are applied to the digitized signals for the selection. A filtered ECG for the selection is generated for each of the sets based on the signals filtered by that set. The filtered selection ECG for each of the sets are presented on the display. 
     Providing a real-time, interactive ECG processing apparatus and method for a user, such as a cardiologist or a trained technician, to select and apply ECG noise filters to a desired portion of an ECG trace, particularly but not exclusively the P-wave, simplifies ECG result processing and improves ECG interpretation accuracy. 
     Still other embodiments of the present invention will become readily apparent to those skilled in the art from the following detailed description, wherein are described embodiments by way of illustrating the best mode contemplated for carrying out the invention. As will be realized, the invention is capable of other and different embodiments and its several details are capable of modifications in various obvious respects, all without departing from the spirit and the scope of the present invention. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not as restrictive. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a graph showing, by way of example, a normal ECG waveform for a single cardiac cycle. 
         FIG. 2  is a graph showing, by way of example, an ECG waveform of a patient with atrial flutter for a single cardiac cycle, where the ECG waveform has been corrupted by power line noise. 
         FIG. 3  is a diagram showing a screen shot generated by an application for interactive processing of ECG data in accordance with one embodiment. 
         FIG. 4  is a functional block diagram showing a system for interactive processing of ECG data in accordance with one embodiment. 
         FIG. 5  is a flow diagram showing a method for interactive processing of ECG data in accordance with one embodiment. 
         FIG. 6  is a flow diagram showing a routine for recommending an ECG filter for use in the method of  FIG. 5  in accordance with one embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     An ECG includes multiple waveforms reflecting multiple contractions of a patient&#39;s heart.  FIG. 1  is a graph showing, by way of example, a normal ECG waveform  10  for a single cardiac cycle. The x-axis represents time in approximate units of tenths of a second. The y-axis represents cutaneous electrical signal strength in approximate units of millivolts. The P-wave  11 , when recorded from the anterior thorax, normally has a smooth, initially upward slope, (i.e., a positive vector) that indicates atrial depolarization from right to left atrium. The QRS complex usually begins with the downward deflection of a Q wave  12 , followed by a larger upward deflection of an R-wave  13 , and terminated with a downward waveform of the S wave  14 , collectively representative of ventricular depolarization. The T wave  15  is normally a modest upward waveform, representative of ventricular repolarization, while the U wave  16 , often not directly observable, indicates repolarization of the Purkinje conduction fibers. 
     ECG signals include low amplitude voltages in the presence of high offsets and noise, which requires the signals to be amplified and filtered prior to being displayed for interpretation. In an unfiltered ECG, some of the features may not be apparent, particularly if their shapes have been corrupted by noise. For example, the P-wave morphology, presence or absence, timing, and size can be indicative of a variety of cardiac conditions. An abnormally large P-wave can be indicative of atrial hypertrophy, an abnormally wide P-wave can be indicative of an intra-atrial block, and atrial flutter may cause the P-waves to adopt a “saw-tooth” or negative shape. Absent or not-easily discernible P-waves can be indicative of atrial fibrillation, while discrete P-waves that vary from beat-to-beat with at least three different morphologies, can be indicative of multifocal atrial tachycardia. A dissociation between the timing of the P-wave and the QRS complex can indicate ventricular tachycardia. Other associations between the P-wave and cardiac conditions exist. Identifying presence, timing and morphology or the P-wave is critical to arrhythmia diagnosis. 
     Noise in an ECG or inadequate signal clarity is a major problematic for cardiologists when caring for patients with possible cardiac arrhythmias.  FIG. 2  is a graph showing, by way of example, an ECG waveform  20  of a patient with atrial flutter for a single cardiac cycle, where the ECG waveform  20  has been corrupted by power line noise. In the United States, power line noise has a frequency of 60 Hz with a high amplitude. The wall outlets in an examination room invariably surround a patient and create an electrical field that causes power line noise to be coupled into the ECG. Here the patient&#39;s ECG lacks a clearly defined P-wave, with the signal noise obscuring the “saw-tooth” P-wave shape seen in the underlying atrial flutter. As a result, the diagnosis is missed. 
     Classical ways to reduce power line noise are to make physical changes to the circuit design of ECG equipment. For instance, power line noise can be reduced by isolating front-end ground electronics from the digital components of the machine, and using shielded cables to acquire ECG signals driven with a common voltage to reduce noise from being coupled from proximal power lines. However, some degree of power line noise will always be present due to the power draw of the ECG machine itself. Power line noise is more predictable and more readily lends itself to classical noise-reduction techniques, as described above. 
     Other types of noise, such as those associated with muscle activity, often the main source of ECG noise, including baseline wander, is best diminished with a more patient-specific and dynamic method of noise reduction involving the appropriate application of digital noise filters. 
     Digital filters are inherently flexible. Changing the characteristics of a digital filter merely involves changing the program code or filter coefficients. They also do not require physical reconstruction of the ECG system, and thus tend to be low cost and highly compatible with existing ECG equipment. Noise present in an ECG of one patient can be different from noise present in an ECG of another patient, and the flexibility provided by the digital filters helps to clarify each individual ECG and provide for patient-specific ECG signal processing. In addition, digital filters are immune to the effects of wear and degradation that all hardware experiences. 
     ECG noise can be effectively reduced by allowing a user to pick particular portions of an ECG for application of a filter and allowing the user to compare results of applications of different filters to the selected portions. This is critical when seeking to record the more difficult-to-see P-wave compared to the high voltage high frequency content of the QRS wave.  FIG. 3  is a diagram showing a screen shot generated by an application  30  for interactive processing of ECG data in accordance with one embodiment. The application  30  can be a downloadable application executed on a user device  31 . While the user device  31  is shown as a tablet computer with reference to  FIG. 1 , other kinds of user devices  31 , such as mobile phones, desktop computer, laptop computers, portable media players are possible; still other types of user devices  31  are possible. The user device  31  can include components conventionally found in general purpose programmable computing devices, such as a central processing unit, memory, input/output ports, network interfaces, and non-volatile storage, although other components are possible. The central processing unit can implement computer-executable code, including digital ECG filters, which can be implemented as modules. The modules can be implemented as a computer program or procedure written as source code in a conventional programming language and presented for execution by the central processing unit as object or byte code. Alternatively, the modules could also be implemented in hardware, either as integrated circuitry or burned into read-only memory components. The various implementations of the source code and object and byte codes can be held on a computer-readable storage medium, such as a floppy disk, hard drive, digital video disk (DVD), random access memory (RAM), read-only memory (ROM) and similar storage mediums. Other types of modules and module functions are possible, as well as other physical hardware components. 
     The application  30  receives results of an ECG monitoring, which can include an ECG  32 , including in a printed form. The ECG  32  can be received at once, such as upon completion of monitoring, or in portions, as the monitoring progresses. In addition to the ECG  32 , the application  30  can display information about the patient  33  such as the patient&#39;s name, date of birth, gender, and patient ID; other clinical or physiological information associated with the patient can also be displayed. 
     A user may select a portion  34  of the displayed ECG  32  for application of one or more digital filters, such as by clicking on the portion or highlighting the portion with a mouse. The selected portion  34  can be zoomed and displayed in a separate area  35  of the application screen. By looking at the selection in the area  35 , the user can decide what filters to apply to the selection  34 . 
     Application of filters to an ECG can result in a loss of clinical information present in the ECG waves. Only a limited number of filters can be applied before such clinical information is lost due to the filters introducing distortions into some part of the ECG signals. For example, a high-pass filter, a filter whose purpose is to remove low-frequency noise, introduces distortions to the ST segment of ECG. The distortion arises from the combination of the frequencies of some of the noise overlapping with the spectra of useful ECG waves, with the noise generally being stochastic; thus any attempt of removing the noises after signal acquisition is typically accompanied by some degree of signal degradation. An excessive number or an incorrect set of applied filters can remove useful diagnostic features from the ECG waveform, leading to false diagnostic statements. By selecting a portion  34  of the ECG and, applying filters only to that portion, the rest of the ECG  32  is maintained intact and unfiltered. 
     The user may filter the selection  34  using a list of ECG digital noise filters provided by application in filter selection menus  36 ,  38 . By selecting the filters in different menus  36 ,  38 , the user can select different sets of filters for filtering the ECG  32 . Each of the digital filters is a mathematical algorithm that is applied to digital ECG signals to output a set of filtered signals that differs from the set of the ECG signals to which that filter is initially applied. The filters can be stored in the memory of the user device  31 . Such filters can include a low-pass filter, which attenuates noise with a frequency higher than a cut-off frequency; a high-pass filter, which attenuates signals with frequencies lower than the cut-off frequency; a notch filter, which passes all frequencies except those in a stop-band centered on a center frequency; a phase correction filter, which corrects a phase of an ECG wave following earlier digital processing; and an adaptive filter, which obtains the frequency of the noise present, such as based on patient input or by calculating the noise, and minimizes the identified noise. Other types of filters are possible. 
     The user can customize the filter selection menus  36 ,  38 . For instance, the user can change the order in which the filters are displayed in the selection menus  36 ,  38 , such as by dragging and dropping the filters with a mouse. Thus, if the user uses particular filters more often than other filters, the more used filters can be brought to the top of the menus  36 ,  38 . Further, the order of the filters in the filter selection menu  36  can be different from the order in the menu  38 . 
     Also, the user can select the displayed filters, such as by clicking on a name of one of the filters, and change one or more parameters of the selected filter. For example, if the selected filter is a high-pass filter, the user can enter a cut-off frequency used for the filter. Other parameters can also be changed. The desired parameters can be changed in a separate window of the application  32  that appears upon the filter being selected, though other ways for the user to change the parameters are possible. Still other ways to customize the filter selection menus are possible. 
     The user may apply different filters or combinations of filters to the selection  34 , and see the results of applications of different filters side-by-side in the areas  37  and  39 . For example, the user may select a notch filter to be applied to the selection  34 , and see the results of the application of the filter, a filtered ECG of the selection, in the area  37 . While the application of the notch filter results in a clearer shape of the selection  34 , including that of the P-wave, if the user is still not satisfied with the result, the user can choose in the filter selection menu  38  to choose to apply a different set of filters, choosing the notch filter in combination with the low-pass filter to further remove the noise from the selection  34 , with the results of the application of the filters being displayed in the area  39 . The user can compare the application of different selected filters side-by-side and decide whether any of the applied filters or combinations of filters produce a satisfactory result or whether applications of other filters are necessary. The results of application of different filters to the selection  34  are displayed to the user immediately upon becoming available, allowing the user to explore different filter set possibilities in real-time and reducing the time necessary to find the most appropriate filter set. 
     If the user is satisfied with a filtered ECG of the selection in the area  37  or  39 , the user can replace the selection  34  of the ECG  32  with the filtered ECG of the selection in area  37  or  39 , such as by dragging the selection in the area  37 ,  39  to the displayed ECG  32  or pressing a button on the screen of the application  31  (not shown). 
     While two sets of filter selection menus  36 ,  38  and areas with the results of filter application  38 ,  39  are shown in the screen of the application, in a further embodiment, other numbers of filter menus and areas showing results of the filtering using the selected filters are possible. 
     As further described with reference to  FIGS. 5 and 6 , the application  30  can make a recommendation (not shown) of one or more filters to be applied to the selection  34 . The recommendation is created by identifying a frequency of a noise recurring in the selection  34  (“recursive noise”), such as presence of 60 Hz power line noise, based on one or more of user input or mathematical estimation of the noise frequency, and recommending the frequency based on the noise. For example, if the recursive noise includes power line noise, a notch filter or a low-pass filter can be recommended to remove the noise. The recommendation can be presented in different ways, such as presenting the recommendation in a separate field on the screen of the application  30  or by highlighting the filters presented in the menus  36 ,  38 . 
     In a further embodiment, in addition to providing a filtering recommendation, the application  30  can automatically apply one or more filters to an ECG prior to presenting the ECG to the user, saving the user the labor of filtering noise that can be automatically identified and removed. The application  30  can identify the presence of noise in an ECG received from an ECG monitor or from another source, automatically apply a filter or a combination of filters to digitized signals for portions of the ECG with the noise, and generate the ECG  32  that is displayed to the user based on digitized signals that have been filtered and any digitized signals that did not include the noise. For example, if the application  30  identifies baseline wander corrupting a received ECG, which can be identified using techniques such as measuring deviation of signals from the baseline in a random fashion within set frequency domains, the application  30  can automatically apply a filter or a set of filters to digitized signals for portions of the ECG with the baseline wander, and generate the ECG  32  displayed to the user based on digitized signals that have been filtered and signals that have not been corrupted by the baseline wander. The filters to be applied can be determined via testing, such by as applying different filters, such as various high-pass filters, or combinations of filters to the digitized signals and identifying the filters or combinations of filters that result in the greatest reduction of the baseline wander. In a further embodiment, a preset filter or combination of filters can be used to automatically reduce or remove the baseline wander. In a still further embodiment, the application  30  can also test effect of changing parameters of the filters on the removal of the noise, and choose the most appropriate parameters for the filters used. Other kinds of automated application of filters are possible. 
     The application can obtain results of an ECG recording from a variety of sources.  FIG. 4  is a functional block diagram showing a system  40  for interactive processing of ECG data in accordance with one embodiment. As seen in  FIG. 2 , the application  30  can receive the results from a long-term ECG monitor, a monitor that continuously monitors patient information over a number of days. 
     In one embodiment, the long-term electrocardiography ECG monitor can be the extended wear ambulatory physiological sensor monitor  41  described in detail in a commonly-assigned U.S. Patent application, entitled “Extended Wear Ambulatory Electrocardiography and Physiological Sensor Monitor,” Ser. No. 14/080,725, filed Nov. 14, 2013, pending, the disclosure of which is incorporated by reference. The placement of the wearable monitor  41  in a location at the sternal midline  42  (or immediately to either side of the sternum) of the patient  43  significantly improves the ability of the wearable monitor  41  to cutaneously sense cardiac electric signals, particularly the P-wave (or atrial activity) and, to a lesser extent, the QRS interval signals in the ECG waveforms that indicate ventricular activity, while simultaneously facilitating comfortable long-term wear for many weeks. As further described in detail in commonly-assigned U.S. Patent application, entitled “Remote Interfacing of Extended Wear Electrocardiography and Physiological Sensor Monitor,” Ser. No. 14/082,071, filed on Nov. 15, 2013, pending, the disclosure of which is incorporated by reference, upon completion of the monitoring period, the monitor  41  can be connected to a download station  44 , which could be a programmer or other device that permits the retrieval of stored ECG monitoring data, execution of diagnostics on or programming of the monitor recorder  41 , or performance of other functions. The monitor  41  has a set of electrical contacts (not shown) that enable the monitor recorder  41  to physically interface to a set of terminals  45  on a paired receptacle  46  of the download station  44 . In turn, the download station  44  can execute a communications or offload program  47  (“Offload”) or similar program that interacts with the monitor recorder  41  via the physical interface to retrieve the stored ECG monitoring data. The download station  44  could be the user device  31  or another server, personal computer, tablet or handheld computer, smart mobile device, or purpose-built programmer designed specific to the task of interfacing with a monitor  41 . Still other forms of download station  44  are possible. 
     Upon retrieving stored ECG monitoring data from the monitor  41 , middleware (not shown) first operates on the retrieved data to adjust the ECG capture quality, as necessary, and to convert the retrieved data into a format suitable for use by third party post-monitoring processing software, such as the application  30 . If the download station  44  is not the user device  31 , the formatted data can then be retrieved from the download station  44  over a hard link  48  using a control program  49  (“Ctl”) or analogous application executing on a personal computer  50  or other connectable computing device, via a communications link (not shown), whether wired or wireless, or by physical transfer of storage media (not shown). The personal computer  50  or other connectable device may also execute middleware that converts ECG data and other information into a format suitable for use by a third-party post-monitoring processing program, such the application  30 . Note that formatted data stored on the personal computer  50  would have to be maintained and safeguarded in the same manner as electronic medical records (EMRs)  51  in a secure database  52 , as further discussed infra. In a further embodiment, the download station  44  is able to directly interface with other devices over a computer communications network  53 , which could be some combination of a local area network and a wide area network, including the Internet, over a wired or wireless connection. Still other forms of download station  44  are possible. In addition, the wearable monitor  41  can interoperate with other devices, as further described in detail in commonly-assigned U.S. Patent application, entitled “Remote Interfacing of Extended Wear Electrocardiography and Physiological Sensor Monitor,” Ser. No. 14/082,071, filed on Nov. 15, 2013, pending, the disclosure of which is incorporated by reference. In addition, the wearable monitor  41  is capable of interoperating wirelessly with mobile devices, including so-called “smartphones,” such as described in in commonly-assigned U.S. Patent application, entitled “Computer-Implemented System And Method for Providing A Personal Mobile Device-Triggered Medical Intervention,” filed on Mar. 17, 2014, the disclosure of which is incorporated by reference. 
     Other kinds of long-term monitors, such as Holter monitors (not shown), can be used to obtain the data processed by the application  30 . In addition, the application  30  can receive the results from other kinds of ECG monitors, such as a standard 12-lead ECG monitor (not shown) that records a patient&#39;s ECG during a visit to a doctor&#39;s office, which can provide the results to the application  30  through the download station  44  or in other ways described above. Still other kinds of ECG and physiological monitors, from which data can be received, are possible. Further, in one embodiment, the results can be obtained by the application  30  upon the completion of the monitoring. In a further embodiment, the results can be provided to the application  30  running on the user device  31  as they are obtained. 
     While as mentioned above the user device  31  can be the download station  44  and receive ECG recording data from an ECG monitor directly, the application  30  running on the user device  31  can also receive results of monitoring from other sources, such as from a server  54  storing results of completed recordings or “monitorings”. A client-server model could be used to employ a server  54  to remotely interface with the download station  44  over the network  53  and retrieve the formatted data or other information. The server  54  executes a patient management program  55  (“Mgt”) or similar application that stores the retrieved formatted data and other information in the secure database  52  cataloged in that patient&#39;s EMRs  51 . The application  30  can receive the results of the monitoring from the server  54 . In addition, the patient management program  55  could manage a subscription service that authorizes a monitor recorder  41  to operate for a set period of time or under pre-defined operational parameters. 
     The patient management program  55 , or other trusted application, also maintains and safeguards the secure database  52  to limit access to patient EMRs  51  to only authorized parties for appropriate medical or other uses, such as mandated by state or federal law, such as under the Health Insurance Portability and Accountability Act (HIPAA) or per the European Union&#39;s Data Protection Directive. For example, a physician may seek to review and evaluate his patient&#39;s ECG monitoring data, as securely stored in the secure database  52 . 
     Still other sources from which the application  30  can receive the results of the ECG monitoring are possible. 
     As mentioned above, the application  30  applies one or more of ECG digital filters to a user selection of a displayed ECG trace  32 . The application  30  can obtain the filters  56  from a database  57 , with which the application  30  can interact via the network  53 . The database  57  can be updated with more filters  56 , allowing the application  30  and present them to the user as the filters  56  become available. 
     Allowing a user to choose and selectively apply filters to selected portions of an ECG facilitates obtaining an ECG that includes discernible diagnostic information and can be used for patient diagnosis.  FIG. 5  is a flow diagram showing a method  60  for interactive processing of ECG data in accordance with one embodiment. Initially, an ECG  32  that is a result of electrocardiographic monitoring of a patient is obtained by the application  30  executed on the user device  31  (step  61 ). The ECG  32  can be obtained from an ECG monitor or from other sources, as described above, and can be obtained upon a completion of the monitoring, or continuously received in real-time as monitoring progresses. In a still further embodiment, both the ECG  32  and the digitized ECG signals corresponding to the ECG  32  can be obtained. 
     Optionally, if the application  30  identifies presence of noise, such as baseline wander, in the ECG received from a monitor or another source, the application  30  can automatically apply one or more filters to digitized signals corresponding to portions of the obtained ECG that has the noise, with the ECG  32  that is subsequently displayed to the user being generated based on the filtered digitized signals and signals for portions of the ECG that did not include the baseline wander, as further described above with reference to  FIG. 3  (step  62 ). 
     The ECG  32 , after having been optionally automatically filtered, is displayed on a display screen of the user device  31  (step  63 ). If the ECG  32  is received over a period of time, such as when the ECG is a result of an ongoing electrocardiographic monitoring, portions of the ECG can be updated in real-time as they are being received, with the displayed ECG being updated as more results of the monitoring become available. If the ECG  32  is a result of an already completed monitoring, all portions of the ECG can be displayed at the same time. 
     A user selection  34  of a portion of the ECG is received, such as via the user touching the portion on the touch-screen display of the user device  31 , entering the selection from a keyboard, or using a mouse (step  64 ). Digitized ECG signals corresponding to the selected portion  34  of the ECG are obtained by the application  30  (step  65 ). If the digitized signals for the ECG  32  were received with the ECG  32 , the signals corresponding to the selection  34  can be identified among the received signals. If no digitized ECG signals have been received, the application  30  can reconstruct the digitized signals from the selection  34 . Other ways to obtain the digitized signals are possible. 
     Optionally, the selection is zoomed and the zoomed selection  35  is displayed to the user by the application (step  66 ). A list, such as in the selection menus  36 ,  38 , of a plurality of digital ECG filters for filtering the selection is displayed to the user, with the user being able to select one or more sets of the filters for filtering the selection (step  67 ). Optionally, a filter recommended for processing the selection  34  is determined and displayed to the user, as further described with reference to  FIG. 6  (step  68 ). A user selection of one or more sets of the filters is received by the application  30 , with each of the filter sets including at least one of the filters displayed (step  69 ). The application  30  applies each of the sets of the selected filters to the digitized ECG signals for the selection (step  70 ), generates filtered ECG for the selection based on the digital signals filtered by each of the sets, and displays the filtered ECG for the selection on portions  37 ,  39  of the display screen of the user device  31  (step  71 ). The filtered ECGs can be displayed visually proximate to each other, allowing comparison of results of filtering side-by-side, and thus enabling the user to decide which of the results is more useful, whether one of the results satisfies the user&#39;s needs, or whether a still different set of filters needs to be applied. Optionally, upon receiving a user selection of one of the filtered ECGs for the selection, the application  30  can replace the selected portion  34  of the ECG  32  with the selected filtered ECG (step  72 ), ending the method  60 . 
     Recommending an ECG filter to the user can save the user time and simplify ECG interpretation for the user.  FIG. 6  is a flow diagram showing a routine  80  for recommending an ECG filter to a user for use in the method  60  of  FIG. 5  in accordance with one embodiment. First, a frequency of a recursive noise present in the ECG selection is identified (step  81 ). Second, one or more digital filters are selected based on the noise frequency (step  82 ). For example, if the selection includes high-frequency recursive noise, a low-pass filter can be chosen for the recommendation. Lastly, the selected filter is recommended to a user, terminating the routine  80  (step  83 ). 
     While the invention has been particularly shown and described as referenced to the embodiments thereof, those skilled in the art will understand that the foregoing and other changes in form and detail may be made therein without departing from the spirit and scope.