Cardiac arrhythmia detector using ECG waveform-factor and...

Details Cardiac arrhythmia detector using ECG waveform-factor and... Cardiac arrhythmia detector using ECG waveform-factor and...

2000-06-30

2002-11-12

Evanisko, George R. (Department: 3762)

Surgery

Diagnostic testing

Cardiovascular

Reexamination Certificate

active

06480734

ABSTRACT:

BACKGROUND OF THE INVENTION
A. Field of Invention
The present invention relates generally to a cardiac arrhythmia detector in a prosthesis such as an internal or external cardiac defibrillator and pacemaker. More specifically, such a detector comprises a microprocessor used to perform an arrhythmia detection algorithm that detects and analyzes an ECG waveform factor and its irregularity for promptly and accurately discriminating among various types of cardiac arrhythmias, including ventricular fibrillation (VF), ventricular tachycardia (VT), supraventricular tachycardia (SVT), or other arrhythmias.
B. Description of the Prior Art
Sudden cardiac arrest (SCA) accounts for about 76% of sudden non-traumatic deaths in adults and about 50% of all cardiac deaths. Approximately 350,000 Americans experience SCA each year with only about 5% national survival rate. Even in hospital, the percentage of patients who survive SCA is not encouraging. This percentage has remained stable at approximately 15%, and has not improved in the last 30 years. Thus SCA still represents a major and unresolved public health problem.
Ventricular tachyarrhythmia (which includes ventricular fibrillation (VF) and ventricular tachycardia (VT)) is the most common initial incidence of SCA. Unlike other life-threatening conditions such as cancer or AIDS, there is an effective, inexpensive and standard therapy for SCA: timely cardioversion/defibrillation applied by a cardiac stimulator device. Early timely cardioversion/defibrillation (i.e., immediately after onset) is the key to survival, since the chances of success are reduced by 10 percent for every minute of delay of the treatment. Death usually follows unless a normal heart rhythm is restored within 5-7 minutes. Therefore, it is the lack of warning, i.e. detection, and the delay for intervention, not a lack of effective treatment, that accounts for the high death rate following SCA.
The most effective means of saving SCA victims outside a hospital consists of widespread deployment of public access defibrillators as suggested by American Heat Association, and wearable automatic external defibrillators. For diagnosed SCA high-risk patients or SCA survivals, implantable cardioverter defibrillator (ICD) is also an effective treatment. For in-hospital SCA, self-monitoring, self-evaluating, and self-defibrillating monitors, such as fully automatic external defibrillator/monitor Powerheart®(Cardiac Science, Inc., Irvine, Calif.), and automatic defibrillator module plugged into the existing modular monitoring systems, are the expected effective tools. For both implantable and external automatic defibrillators, the tachyarrhythmia detection algorithm plays the key role for the device's safety, reliability, effectiveness, ease of use, extent of automatic operations, and widespread acceptance. Prompt and accurate detection of VT and VF is still a major challenge in the defibrillation art. Different tachycardias require different electrical therapies: no electrical therapy needed for the conditions like sinus rhythm, sinus tachycardia (ST), and supraventricular tachycardia (SVT); a comparatively low-energy cardioversion for VT; and a high-energy defibrillation shock for VF. Therefore, the challenge for an effective and successful arrhythmia detector is to discriminate these three types of arrhythmias reliably and accurately. A cardiac device can then treat the appropriate condition on an “as-needed” basis. In this way, the false shocks caused by SVT and ST can be avoided, since it causes unnecessary patient distress, and may initiate VT or VF when none previously existed. Moreover, unnecessary treatment applied by an ICD also wastes power.
Differentiating VT from VF makes it allow the treatment of tachyarrhythmia with the lowest energy levels, least painful electrical stimulation pulses, and potentially the most effective therapies. For implantable devices where power source energy and patient tolerance to repeated cardioversion/defibrillation shocks are both limited, therefore, discrimination among these three types of arrhythmias is necessary and important.
Among the methods most widely used for detection of VT & VF in antitachycardia devices is heart rate (HR), and the rate of change of rate or suddenness of onset of tachycardias. Rate stability and sustained high rate also are suggested as additional criteria. Rate and rate-related measures are not a reliable criterion because of difficulty in separating SVT, VT, and VF, due to the overlap of the heart rate for these arrhythmias and the likelihood of missing an R-wave trigger (i.e., ECG dropout) during VF with rapidly changing peak amplitudes.
Another known criterion, the probability density function which was used as the original ICD detection scheme to measure of time the signal is away from the isoelectric baseline, is being gradually abandoned due to its lack of specificity for tachyarrhythmia discrimination.
Along with rate, shape differentiation between ventricular electrograms during sinus rhythm (SR) and VT and VF is another known criteria that can be expected to provide an accurate discrimination using a morphology-based algorithm with correlation analysis and template matching. However, its shortcoming is the necessity of waveform alignment, which is critical to a proper point-by-point comparison. If the test and template signals are not aligned correctly, the result of the waveform comparison can be erroneous. Moreover, aligning the test and template signals and the calculation programs can be a burdensome and time-consuming problem, especially for implantable cardioverter/defibrillator. Furthermore, more memory is required for storing the test and template signals. Therefore, there is still some difficulties for real-time implementation in defibrillators, especially for ICD.
A method of discriminating among cardiac rhythms of supraventricular and ventricular origin by exploiting the differences in their underlying nonlinear dynamics reflected in the morphology of the waveform is disclosed in U.S. Pat. No. 5,645,070, issued to Turcott. A two-channel scatter diagram analysis algorithm for distinguishing VT from VF is disclosed in U.S. Pat. No. 5,404,880, issued to Throne. The shortcoming for these methods is still the computationally complex and more memory requirement. Other algorithms for tachyarrhythmia discrimination utilizing statistical methods were also proposed (Thakor et al., Ventricular Tachycardia And Fibrillation Detection By A Sequential Hypothesis Testing Algorithm, IEEE Trans. Biomed. Eng., 1990, 37:837-843 and Turner et al., Statistical Discriminant Analysis of Arrhythmias Using Intracardiac Electrograms, IEEE Trans. Biomed. Eng., 1993, 40:985-989). However, their effectiveness and practical feasibility still need further investigation.
Modulation domain function (MDF) is effective in discriminating SVT from ventricular tachyarrhythmias (Mattioni et al., Initial Clinical Experience With A Fully Automatic In-hospital External Cardioverter Defibrillator, PACE 1999, 22:1648-1655). However, SVT with an underlying chronic bundle branch block or with aberrant conduction can result in high MDF values, this method may fail for this kind of rhythm. Moreover, MDF cannot differentiate VT from VF.
Currently, AED's in use are 90% sensitive for ventricular tachyarrhythmia and 90-95% specificity for other heart rhythms. For ICD the percentage of patients who are paced or shocked unnecessarily still exceeds 40% of those receiving ICD therapies. Moreover, discrimination of VT from VF is also a difficulty objective to achieve using existing algorithms. A need still exists for discovering additional information from ECG waveform to develop computationally simple method of discriminating SVT, VT, and VF.
In atrial and ventricular tachyarrhythmias, the shapes of the P-waves and QRS-waves are distorted from the normal sinus rate shapes. Nonshockable arrhythmias have different morphology with shockable arrhythmias (VT and VF). In fact, while physicians classify a cardiac rhythm, they examine the morphol

Affiliated with

Also associated with

Rating

Cardiac arrhythmia detector using ECG waveform-factor and... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Cardiac arrhythmia detector using ECG waveform-factor and..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cardiac arrhythmia detector using ECG waveform-factor and... will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-2993367