|Publication number||US7415304 B2|
|Application number||US 10/824,964|
|Publication date||19 Aug 2008|
|Filing date||15 Apr 2004|
|Priority date||15 Apr 2004|
|Also published as||US20050234356|
|Publication number||10824964, 824964, US 7415304 B2, US 7415304B2, US-B2-7415304, US7415304 B2, US7415304B2|
|Inventors||G. Ian Rowlandson, David E. Albert|
|Original Assignee||Ge Medical Systems Information Technologies, Inc.|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (114), Non-Patent Citations (30), Referenced by (5), Classifications (11), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
A pacemaker's main purpose is to analyze the function of the heart's electrical system and to keep the electrical system operating properly. A pacemaker can prevent the cardiac problems associated with slow heart rhythms (e.g., congestive heart failure, fainting, death, etc.). Pacemakers are necessary because, while there are many medications that prevent the heart from operating too quickly, there are only a few medications that can make the heart operate more quickly. Pacemakers have become a reliable means of helping people live longer and improve their lifestyles despite having a slow heart rhythm.
An automatic internal cardioverter defibrillator (“AICD”) is an electronic device that is implanted in a pocket formed in the chest wall that senses the heart's rhythm and can deliver a powerful shock to the heart. The AICD automatically detects certain arrhythmias (e.g., ventricular fibrillation, ventricular tachycardia, atrial fibrillation, etc.) and delivers a shock to the heart to terminate the arrhythmia.
Both pacemakers and AICDs provide artificial stimulation for the management of rhythm and/or improved heart function. Both pacemakers and AICDs include electronic circuitry that stores information about the heart as it monitors the heart rhythm and delivers therapy. Caregivers can review this stored information by using a programmer or interrogator that communicates with the pacemaker or AICD through the skin. Caregivers are able to review the heart's rhythms, arrhythmia episodes, and device operation over a period of time with the programmer or interrogator.
Conventionally, caregivers review the implant data gathered by the programmer or interrogator independently of other cardiac data available for the patient.
In one embodiment, the invention includes a method of analyzing cardiac data acquired from a patient having an implant. The method comprises acquiring non-implant cardiac data and implant cardiac data from the patient, synchronizing the non-implant cardiac data and the implant cardiac data, and correlating the non-implant cardiac data with the implant cardiac data to determine a cardiac condition of the patient.
Before any embodiments of the invention are explained in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the following drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limited. The use of “including,” “comprising” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “mounted,” “connected” and “coupled” are used broadly and encompass both direct and indirect mounting, connecting and coupling. Further, “connected” and “coupled” are not restricted to physical or mechanical connections or couplings, and can include electrical connections or couplings, whether direct or indirect.
In addition, it should be understood that embodiments of the invention include both hardware and electronic components or modules that, for purposes of discussion, may be illustrated and described as if the majority of the components were implemented solely in hardware. However, one of ordinary skill in the art, and based on a reading of this detailed description, would recognize that, in at least one embodiment, the electronic based aspects of the invention may be implemented in software. As such, it should be noted that a plurality of hardware and software based devices, as well as a plurality of different structural components may be utilized to implement the invention. Furthermore, and as described in subsequent paragraphs, the specific mechanical configurations illustrated in the drawings are intended to exemplify embodiments of the invention and that other alternative mechanical configurations are possible.
Generally, pacemakers and AICDs can be programmed in any suitable manner to accommodate the needs of the patient. The pacemaker can be programmed wirelessly using a hand-held programmer that communicates with the pulse generator through the patient's skin using radio frequencies. For example, the following parameters can be programmed: the strength and duration of the impulse delivered to the heart muscle, the speed of the pacemaker, and the time period between stimulating the atrium and the ventricle.
Periodically, the pulse generator can be interrogated in order to download patient information and cardiac data (e.g., electrocardiograms; “ECGs”) and in order to monitor the operation of the pacemaker. The pulse generator can also be reprogrammed to extend the battery life and/or to adjust the operational parameters to accommodate changes in the patient's lifestyle.
Most electronic cardiac implants (e.g., pacemakers and AICDs) acquire diagnostic and therapeutic information and patient data. It should be noted that the invention is not limited to pacemakers and AICDs. Rather, any electronic cardiac implant can be utilized with the embodiments of the invention. Caregivers for patients with electronic cardiac implants can use information from a variety of sources to monitor and treat the patient, including data acquired from the implant, as well as from other sources. However, as the implant patient moves throughout the medical care system, all caregivers may not have access to the implant data to assist in making diagnostic and treatment decisions. In contrast, other cardiac monitoring that acquires non-implant data (e.g., bedside monitoring and resting 12-lead ECGs) is used routinely in the medical care system, and the results are generally readily available to most caregivers.
These other cardiac monitoring techniques can record significant patient clinical events that are reflected in the non-implant data. In some embodiments of the invention, the non-implant data can be correlated with the data acquired by the electronic implant. The correlation of the non-implant data and the implant data can increase the usefulness of the patient's overall data and can provide a bigger clinical picture from which to make medical diagnoses and treatment recommendations for the patient.
As shown schematically in
The patient monitoring system 10 can also include hardware, such as a processor, I/O interfaces, and storage devices or memory. In addition, the patient monitoring system 10 can include input devices (such as a keyboard and a mouse) and output devices (such as a monitor). The patient monitoring system 10 can further include peripherals (such as a printer and a scanner). The patient monitoring system 10 can still further include other software, such as a display application.
As shown in
One or both of the patient monitoring system 10 and the wireless device 42 can include a transmitter 44 that can periodically transmit a polling signal in order to determine if any patient in the vicinity has an implant 18. The polling signal can cause the implant 18 to begin transmitting data that can be received by the receiver 38 and/or wireless device 42. In some embodiments, if the receiver 38 or wireless device 42 receives a signal from the implant 18, the software program 26 can automatically detect that the patient 14 has an implant 18 and can initiate the data acquisition module 30 of the patient monitoring system or the wireless device 42 to begin acquiring data from the implant 18. As a result, when a patient 14 enters a room with the patient monitoring system 10, the patient monitoring system 10 can automatically detect that the patient 14 has an implant 18 and can begin acquiring clinical data from the implant 18.
The patient monitoring system 10 can include a plurality of systems, modules, and/or components that can communicate over a network 46 (as shown schematically in
In one embodiment of the invention, the data acquisition module 30 of the patient monitoring system 10 can acquire data from the electrodes 22 and data from the implant 18 at the same time. The data can be in the form of, but is not limited to, measurements, waveforms, raw data, processed data, numerical representations, time periods, etc. The implant and non-implant data can include, but is not limited to, one or more of the following: heart rate; blood oxygen saturation; blood pressure; respiration rate; body temperature; ECG data; QRS duration; Q and R wave amplitude and duration; T-wave amplitude, duration, polarity, and alternans; Q-T angle; autonomic turbulence; heart rate variability; wall motion abnormalities; ejection fraction; electrical gradient across the ventricular wall; depolarization time; repolarization time; timing and coupling intervals; cardiac output; pacing protocol; energy consumption; patient activity; etc.
In some embodiments, the data acquisition module 30 can acquire data from the electrodes 22 and data from the implant 18 in real-time. The data acquired from the implant 18 can be transmitted wirelessly from the implant 18 to the patient monitoring system 10 or to the wireless device 42. If the implant data is transmitted to the wireless device 42, the implant data can be transmitted or downloaded from the wireless device 42 to the patient monitoring system 10, either wirelessly or with the appropriate hardware.
Alternatively, if the data is not analyzed and/or reviewed in real-time, the patient monitoring system 10 can assign to the data the date and time when the data was acquired by use of an internal timing system, such as an atomic clock. The implant and non-implant data can be saved and reviewed by caregivers at a later time. When the implant and non-implant data is to be analyzed and reviewed, the implant data can be time-synchronized with the non-implant data by the patient monitoring system 10 based on the date and time when the implant and non-implant data was acquired. In other embodiments, if implant and non-implant data was not acquired during the same date and time, the implant data can be aligned with the non-implant data according to one or more fiducial points (e.g., QRS complexes).
After the implant and non-implant data has been acquired by the data acquisition module 30, the data can be transmitted to the analysis module 34. The analysis module 34 can use a correlation algorithm to correlate the implant data to the non-implant data. The correlation algorithm can be based on a statistical or linear regression model or any other suitable mathematical technique. The results of the correlation algorithm can provide a signature pattern 50, which can be compared with other data and/or other signature patterns previously acquired from the patient 14. The signature pattern 50 can also be stored in the patient monitoring system 10 and/or in any suitable database (not shown) connected to the network 46. The signature pattern 50 can be used to determine whether a cardiac event has occurred in the patient 14 and/or how the implant 18 reacted to or was affected by the cardiac event. The signature pattern 50 can also be used to determine the effectiveness of the current treatment, to determine whether a new diagnosis is warranted, and/or to recommend a new treatment for the patient 14.
In addition, the signature pattern 50 can be used to determine the point at which treatment was applied to the patient 14 and the effect the treatment had on the patient's implant and non-implant data. In other words, the signature pattern 50 can be used to identify when and to reflect the effectiveness of treatment or therapy, such as artificial vagal stimulation, artificial hormonal stimulation, artificial cardiac pacing, artificial airway stimulation, defibrillation, and cardiac resynchronization.
If time-synchronized implant data is not available or cannot be obtained, non-implant data can be acquired and compared to a previously-acquired implant data signature pattern 50. The previously-acquired implant data that was used to generate the implant data signature pattern 50 can generally also be recognized in the non-implant data. For example, artificial stimulation of R waves at specified varying intervals by the implant 18 can be recognized in the non-implant data.
In one example situation, the patient 14 may be in an electrophysiology lab undergoing tests in which arrhythmias and other cardiac conditions are electrically provoked and measured to obtain a signature pattern 50. In this case, the signature pattern 50 can identify the event that was provoked and can reflect the reaction of the implant 18. Both implant and non-implant data can be acquired in real-time while the patient 14 is in the electrophysiology lab and can be reviewed by caregivers on a display of the patient monitoring system 10. The implant and non-implant data acquired can show a different perspective, and thus, a potentially different diagnosis and treatment recommendation than if data from only the implant or data from only the non-implant source was reviewed by the caregivers.
In another example situation, the patient 14 may be undergoing a stress test (pharmaceutical or conventional), which can provoke clinical conditions that can be measured to obtain a signature pattern 50. In yet another example situation, the implant 18 can provoke clinical conditions, such as artificial pacing of the heart at a rapid rate. This event can provide a signature pattern 50 specifically reflecting that the implant 18 was artificially pacing the heart. In still another example situation, the implant 18 can obtain certain measurements, such as autonomic turbulence, via a pacing protocol with shorter or longer coupling intervals. In general, the signature patterns 50 in any of these example situations can be stored and used as future references to which subsequently-acquired data can be compared to determine the functionality of the implant 18 and/or to detect changes in the patient's cardiovascular system.
In general, the criteria for the detection of diseases and the prediction of poor outcomes based only on non-implant data are well established. Based on certain symptoms, caregivers can order specific tests to be performed on the patient 14. The results of those tests, (i.e., the non-implant data only), can be analyzed and reviewed by the caregivers to detect the presence of disease, to detect whether a certain cardiac event occurred, to determine a diagnosis, and to recommend treatment or other tests. However, criteria for the detection of diseases and the prediction of poor outcomes based on only implant data are yet to be established.
Acquiring and correlating implant and non-implant data using the patient monitoring system 10 can provide a basis for establishing criteria for the diagnosis and treatment of disease based on implant data only. For example, if a certain ECG pattern acquired in non-implant data is known to represent S-T elevation and requires treatment X, the ECG pattern acquired from the implant 18 at the same time must also represent S-T elevation and must also require treatment X. In other words, the implant and non-implant data can be correlated to establish that the ECG pattern acquired with the implant 18 also represents S-T elevation and also requires treatment X. The process of comparing known criteria based on non-implant data with unknown criteria based on implant data can help develop criteria for implant data only. According to one embodiment of the invention, the patient's implant 18 can be interrogated and the implant data can be compared to now known criteria in order to determine a diagnosis, recommend treatment, and detect whether the implant 18 is operating properly.
In addition, each patient 14 can develop over time individual known criteria and patterns for certain diseases based on implant data only. Each time the implant 18 is interrogated, the implant data can be compared to the patient's known criteria and patterns to detect whether the disease state has changed, whether the patient's cardiovascular system has changed, or whether the implant 18 has modified its own operation.
In some embodiments, by correlating implant and non-implant data, known criteria and patterns for implant data only can be developed for any one or more of the following: QRS duration (paced or non-paced beats), morphology, and polarity; Q or R-wave amplitude and duration; T-wave amplitude, duration, polarity, and alternans; Q-T angle; wall motion abnormalities; ejection fraction; etc.
Correlating implant and non-implant data can also be used to improve the therapy provided by the implant 18 for subsequent events or for recommending alternative treatment strategies that can be provided by the implant 18. Non-implant data acquired in relation to an onset of implant therapy can be used to better identify a cardiac problem or disease. For example, non-implant data can identify a cardiac problem with timing interval, focus, re-entrant pathway, or bypass track that caused the implant 18 to provide therapy to the patient 14. The caregiver can change one or more settings on the implant 18 or provide other therapy, such as electrophysiology ablation, to treat the cardiac problem. The problem may not have been detected if the caregiver could review only the implant data or only the non-implant data. However, by reviewing the correlation of the implant data and the non-implant data, the caregiver can determine whether the therapy supplied by the implant 18 was effective.
Non-implant data can also be used to trend and identify predictors for therapy that can be provided by the implant 18. For example, the patient monitoring system 10 can trend and identify predictors including one or more of QRS duration (paced or non-paced beats), heart rate variability, QT prolongation, late potentials, T-wave abnormality, PR interval prolongation, QRS conduction defects, P-wave conduction defects, repolarization abnormalities, etc. By reviewing correlated implant and non-implant data, the caregiver can identify problems that led to the therapy provided by the implant 18. In one embodiment, the patient monitoring system 10 can use correlated implant and non-implant data to provide the placement and settings for a bi-ventricular pacemaker in relation to such values as wall motion, ejection fraction, cardiac output, renal function, etc.
The analysis module 34 can receive the data and can analyze and correlate (at 104) the implant and non-implant data. The correlated data (i.e., the signature patterns 50), the implant data, and/or the non-implant data can be displayed by the patient monitoring system 10 using a computer terminal or any monitor capable of displaying (at 108) data. The computer terminal or display monitor can be remote from the patient monitoring system 10. The correlated, implant, and/or non-implant data can also be printed (at 108) at a printer.
If the implant data and non-implant data are not acquired and/or analyzed at the same time, the caregiver can select (at 128) the specific patient data that has been stored in the database or server for review. The software program 26 can synchronize (at 132) the implant data and non-implant data via time-synchronization techniques and/or alignment alignment techniques (e.g., fiducial points). After the implant and non-implant data has been synchronized, the analysis module 30 can receive the data and can analyze and correlate (at 136) the implant and non-implant data. The correlated data (i.e., the signature patterns 50), the implant data, and/or the non-implant data can be displayed (at 140) by the patient monitoring system 10 using a computer terminal or any monitor capable of displaying data. The computer terminal or display monitor can be remote from the patient monitoring system 10. The correlated, implant, and/or non-implant data can also be printed (at 140) at a printer.
Various features and advantages of the invention are set forth in the following claims.
|Cited Patent||Filing date||Publication date||Applicant||Title|
|US3554187||21 Oct 1965||12 Jan 1971||Humetrics Corp||Method and apparatus for automatically screening of electrocardiac signals|
|US3658055||11 Apr 1969||25 Apr 1972||Hitachi Ltd||Automatic arrhythmia diagnosing system|
|US3759248||8 Feb 1971||18 Sep 1973||Spacelabs Inc||Cardiac arrythmia detector|
|US3821948||3 Nov 1971||2 Jul 1974||Hoffmann La Roche||System and method for analyzing absolute derivative signal from heartbeat|
|US3902479||15 Feb 1974||2 Sep 1975||Hoffmann La Roche||Method and apparatus for heartbeat rate monitoring|
|US3952731||12 Dec 1974||27 Apr 1976||Ferranti Limited||Cardiac monitoring apparatus|
|US4124894||27 Apr 1977||7 Nov 1978||Hycel, Inc.||Apparatus and method for reporting detected error in a cardiac signal|
|US4136690||31 Oct 1977||30 Jan 1979||Del Mar Avionics||Method and apparatus for vector analysis of ECG arrhythmias|
|US4170992||5 Jan 1978||16 Oct 1979||Hewlett-Packard Company||Fiducial point location|
|US4181135||3 Mar 1978||1 Jan 1980||American Optical Corporation||Method and apparatus for monitoring electrocardiographic waveforms|
|US4202340||15 Feb 1978||13 May 1980||Mieczyslaw Mirowski||Method and apparatus for monitoring heart activity, detecting abnormalities, and cardioverting a malfunctioning heart|
|US4316249||9 Nov 1979||16 Feb 1982||Hittman Corporation||Automatic high speed Holter scanning system|
|US4417306||7 Jan 1982||22 Nov 1983||Medtronic, Inc.||Apparatus for monitoring and storing utilizing a data processor|
|US4422459||1 Mar 1982||27 Dec 1983||University Patents, Inc.||Electrocardiographic means and method for detecting potential ventricular tachycardia|
|US4432375||24 May 1982||21 Feb 1984||Cardiac Resuscitator Corporation||Cardiac arrhythmia analysis system|
|US4457315||22 Oct 1979||3 Jul 1984||Arvin Bennish||Cardiac arrhythmia detection and recording|
|US4458691||11 Feb 1982||10 Jul 1984||Arrhythmia Research Technology, Inc.||System and method for predicting ventricular tachycardia by adaptive high pass filter|
|US4458692||11 Feb 1982||10 Jul 1984||Arrhythmia Research Technology, Inc.||System and method for predicting ventricular tachycardia with a gain controlled high pass filter|
|US4475558||9 Jul 1982||9 Oct 1984||Healthdyne, Inc.||System for providing short-term event data and long-term trend data|
|US4492235||11 Feb 1982||8 Jan 1985||Arrhythmia Research Technology, Inc.||System and method for predicting ventricular tachycardia by derivative analysis|
|US4499904||23 Feb 1983||19 Feb 1985||Belorussky Nauchnoissledovatelsky Institut Kardiologii||Heart monitoring device|
|US4519395||15 Dec 1982||28 May 1985||Hrushesky William J M||Medical instrument for noninvasive measurement of cardiovascular characteristics|
|US4583553||15 Nov 1983||22 Apr 1986||Medicomp, Inc.||Ambulatory ECG analyzer and recorder|
|US4589420||13 Jul 1984||20 May 1986||Spacelabs Inc.||Method and apparatus for ECG rhythm analysis|
|US4603703||13 Apr 1984||5 Aug 1986||The Board Of Trustees Of The Leland Stanford Junior University||Method for real-time detection and identification of neuroelectric signals|
|US4616333 *||5 Jun 1984||7 Oct 1986||Elscint, Ltd.||Data correlation system|
|US4616659||6 May 1985||14 Oct 1986||At&T Bell Laboratories||Heart rate detection utilizing autoregressive analysis|
|US4665485||17 Jul 1984||12 May 1987||Lundy Research Laboratories, Inc.||Method and apparatus for characterizing the unknown state of a physical system|
|US4679144||21 Aug 1984||7 Jul 1987||Q-Med, Inc.||Cardiac signal real time monitor and method of analysis|
|US4680708||5 Nov 1984||14 Jul 1987||Washington University||Method and apparatus for analyzing electrocardiographic signals|
|US4732157||18 Aug 1986||22 Mar 1988||Massachusetts Institute Of Technology||Method and apparatus for quantifying beat-to-beat variability in physiologic waveforms|
|US4796638||10 Mar 1988||10 Jan 1989||Kabushiki Kaisya Advance Kaihatsu Kenkyujo||Artifact detecting apparatus in the measurement of a biological signal|
|US4802491||30 Jul 1986||7 Feb 1989||Massachusetts Institute Of Technology||Method and apparatus for assessing myocardial electrical stability|
|US4832038||20 Jan 1987||23 May 1989||The Board Of Trustees Of University Of Illinois||Apparatus for monitoring cardiovascular regulation using heart rate power spectral analysis|
|US4854327||7 Mar 1988||8 Aug 1989||Kunig Horst E||Non-invasive and continuous cardiac performance monitoring device|
|US4860762||12 Jan 1989||29 Aug 1989||Hewlett-Packard Company||Dual channel resolver for real time arrythmia analysis|
|US4896677||16 Dec 1988||30 Jan 1990||Fukuda Denshi Kabushiki Kaisha||Electrocardiographic waveform display apparatus, and method of expressing electrocardiographic waveforms|
|US4924875||9 Oct 1987||15 May 1990||Biometrak Corporation||Cardiac biopotential analysis system and method|
|US4928690||25 Apr 1988||29 May 1990||Lifecor, Inc.||Portable device for sensing cardiac function and automatically delivering electrical therapy|
|US4938228||15 Feb 1989||3 Jul 1990||Righter William H||Wrist worn heart rate monitor|
|US4951680||27 Sep 1988||28 Aug 1990||National Research Development Corporation||Fetal monitoring during labor|
|US4955382||3 Apr 1989||11 Sep 1990||Ep Technologies||Apparatus and method for recording monophasic action potentials from an in vivo heart|
|US4957115||25 Mar 1988||18 Sep 1990||New England Medical Center Hosp.||Device for determining the probability of death of cardiac patients|
|US4958641||10 Mar 1989||25 Sep 1990||Instromedix, Inc.||Heart data monitoring method and apparatus|
|US4972834||30 Sep 1988||27 Nov 1990||Vitatron Medical B.V.||Pacemaker with improved dynamic rate responsiveness|
|US4974162||13 Mar 1987||27 Nov 1990||University Of Maryland||Advanced signal processing methodology for the detection, localization and quantification of acute myocardial ischemia|
|US4974598||28 Mar 1989||4 Dec 1990||Heart Map, Inc.||EKG system and method using statistical analysis of heartbeats and topographic mapping of body surface potentials|
|US4977899||24 Nov 1989||18 Dec 1990||Instromedix, Inc.||Heart data monitoring method and apparatus|
|US4979510||27 Jul 1988||25 Dec 1990||Ep Technologies, Inc.||Apparatus and method for recording monophasic action potentials from an in vivo heart|
|US4989610||16 Nov 1987||5 Feb 1991||Spacelabs, Inc.||Method and system of ECG data review and analysis|
|US4998535||5 Sep 1989||12 Mar 1991||Univ. of Washington New England Medical Center Hospitals, Inc.||Thrombolysis predictive instrument|
|US5000189||15 Nov 1989||19 Mar 1991||Regents Of The University Of Michigan||Method and system for monitoring electrocardiographic signals and detecting a pathological cardiac arrhythmia such as ventricular tachycardia|
|US5010888||4 Nov 1988||30 Apr 1991||Arzco Medical Electronics, Inc.||Method and apparatus for detection of posterior ischemia|
|US5020540||22 Aug 1989||4 Jun 1991||Biometrak Corporation||Cardiac biopotential analysis system and method|
|US5025795||28 Jun 1989||25 Jun 1991||Kunig Horst E||Non-invasive cardiac performance monitoring device and method|
|US5042497||30 Jan 1990||27 Aug 1991||Cardiac Pacemakers, Inc.||Arrhythmia prediction and prevention for implanted devices|
|US5092341||18 Jun 1990||3 Mar 1992||Del Mar Avionics||Surface ecg frequency analysis system and method based upon spectral turbulence estimation|
|US5109862||21 Feb 1991||5 May 1992||Del Mar Avionics||Method and apparatus for spectral analysis of electrocardiographic signals|
|US5117833||13 Nov 1990||2 Jun 1992||Corazonix Corporation||Bi-spectral filtering of electrocardiogram signals to determine selected QRS potentials|
|US5117834||6 Aug 1990||2 Jun 1992||Kroll Mark W||Method and apparatus for non-invasively determing a patients susceptibility to ventricular arrhythmias|
|US5148812||30 Sep 1991||22 Sep 1992||Georgetown University||Non-invasive dynamic tracking of cardiac vulnerability by analysis of t-wave alternans|
|US5188116||28 Feb 1991||23 Feb 1993||Vital Heart Systems, Inc.||Electrocardiographic method and device|
|US5201321||11 Feb 1991||13 Apr 1993||Fulton Keith W||Method and apparatus for diagnosing vulnerability to lethal cardiac arrhythmias|
|US5234404||11 Oct 1991||10 Aug 1993||Gensia Pharmaceuticals, Inc.||Diagnosis, evaluation and treatment of coronary artery disease by exercise simulation using closed loop drug delivery of an exercise simulating agent beta agonist|
|US5253650||29 Mar 1991||19 Oct 1993||Sharp Kabushiki Kaisha||Apparatus for recording an electrocardiogram|
|US5265617||22 Sep 1992||30 Nov 1993||Georgetown University||Methods and means for non-invasive, dynamic tracking of cardiac vulnerability by simultaneous analysis of heart rate variability and T-wave alternans|
|US5276612||21 Sep 1990||4 Jan 1994||New England Medical Center Hospitals, Inc.||Risk management system for use with cardiac patients|
|US5277188||26 Jun 1991||11 Jan 1994||New England Medical Center Hospitals, Inc.||Clinical information reporting system|
|US5277190||7 Apr 1992||11 Jan 1994||The Board Of Regents Of The University Of Oklahoma||Cycle length variability in nonsustained ventricular tachycardia|
|US5323783||12 Nov 1992||28 Jun 1994||Del Mar Avionics||Dynamic ST segment estimation and adjustment|
|US5343870||12 Nov 1991||6 Sep 1994||Quinton Instrument Company||Recorder unit for ambulatory ECG monitoring system|
|US5423878||2 Aug 1993||13 Jun 1995||Ep Technologies, Inc.||Catheter and associated system for pacing the heart|
|US5437285||30 Nov 1993||1 Aug 1995||Georgetown University||Method and apparatus for prediction of sudden cardiac death by simultaneous assessment of autonomic function and cardiac electrical stability|
|US5501229||1 Aug 1994||26 Mar 1996||New England Medical Center Hospital||Continuous monitoring using a predictive instrument|
|US5560370||26 May 1995||1 Oct 1996||Georgetown University||Method and apparatus for prediction of cardiac electrical instability by simultaneous assessment of T-wave alternans and QT interval dispersion|
|US5570696||26 Jan 1994||5 Nov 1996||Cambridge Heart, Inc.||Method and apparatus for assessing myocardial electrical stability|
|US5718233||11 Jan 1996||17 Feb 1998||New England Medical Center Hospitals, Inc.||Continuous monitoring using a predictive instrument|
|US5724983||25 Mar 1996||10 Mar 1998||New England Center Hospitals, Inc.||Continuous monitoring using a predictive instrument|
|US5747274||5 Sep 1996||5 May 1998||Spectral Diagnostics Inc.||Method and device for diagnosing and distinguishing chest pain in early onset thereof|
|US5819007||15 Mar 1996||6 Oct 1998||Siemens Medical Systems, Inc.||Feature-based expert system classifier|
|US5819741||24 May 1996||13 Oct 1998||Ortivus Medical Ab||Cardiac monitoring system and method|
|US5921940||4 Nov 1997||13 Jul 1999||Georgetown University||Method and apparatus for using physiologic stress in assessing myocardial electrical stability|
|US5935082||15 May 1997||10 Aug 1999||Cambridge Heart, Inc.||Assessing cardiac electrical stability|
|US5948005 *||28 Jan 1997||7 Sep 1999||Pacesetter, Inc.||Multi-event bin heart rate histogram for use with and implantable pacemaker|
|US6059724||14 Feb 1997||9 May 2000||Biosignal, Inc.||System for predicting future health|
|US6067466||18 Nov 1998||23 May 2000||New England Medical Center Hospitals, Inc.||Diagnostic tool using a predictive instrument|
|US6099469||2 Jun 1998||8 Aug 2000||Armstrong; E. Glenn||Reflex algorithm for early and cost effective diagnosis of myocardial infractions suitable for automated diagnostic platforms|
|US6129677 *||10 Aug 1998||10 Oct 2000||Nihon Kohden Corporation||Non-invasive heart monitoring apparatus and method|
|US6142078||23 Feb 1999||7 Nov 2000||Quad/Tech, Inc.||Adaptive color control system and method for regulating ink utilizing a gain parameter and sensitivity adapter|
|US6169919||18 Jun 1999||2 Jan 2001||Beth Israel Deaconess Medical Center, Inc.||System and method for quantifying alternation in an electrocardiogram signal|
|US6334192||9 Mar 1998||25 Dec 2001||Ronald S. Karpf||Computer system and method for a self administered risk assessment|
|US6385485 *||20 Dec 1999||7 May 2002||Ela Medical S.A.||Continuously monitoring cardiac events in an active implantable medical device|
|US6394952||20 Apr 1998||28 May 2002||Adeza Biomedical Corporation||Point of care diagnostic systems|
|US6443889||10 Feb 2000||3 Sep 2002||Torgny Groth||Provision of decision support for acute myocardial infarction|
|US6450954||1 Nov 1999||17 Sep 2002||New England Medical Center Hospitals, Inc.||Method of randomizing patients in a clinical trial|
|US6453191||20 Feb 2001||17 Sep 2002||Cambridge Heart, Inc.||Automated interpretation of T-wave alternans results|
|US6458086 *||5 Apr 2000||1 Oct 2002||Kenneth Lawrence Franco||Implantable blood flow monitoring system|
|US6507753||9 Aug 2000||14 Jan 2003||Ge Marquette Medical Systems, Inc.||Method and apparatus to detect acute cardiac syndromes in specified groups of patients using ECG|
|US6640134 *||27 Aug 2001||28 Oct 2003||Brigham And Women's Hospital||Health monitoring system|
|US6647287 *||14 Apr 2000||11 Nov 2003||Southwest Research Institute||Dynamic cardiovascular monitor|
|US6654631 *||12 Jul 2001||25 Nov 2003||Anil Sahai||Method and apparatus for a hand-held computer EKG device|
|US6668188 *||25 Apr 2001||23 Dec 2003||Cardiac Pacemakers, Inc.||Determination of long-term condition of cardiac patients|
|US7054679 *||31 Oct 2001||30 May 2006||Robert Hirsh||Non-invasive method and device to monitor cardiac parameters|
|US7074194 *||19 May 2003||11 Jul 2006||Ischemia Technologies, Inc.||Apparatus and method for risk stratification of patients with chest pain of suspected cardiac origin|
|US20020099302 *||7 Jan 2002||25 Jul 2002||Bardy Gust H.||System and method for providing diagnosis and montoring of congestive heart faliure for use in automated patient care|
|US20020123672 *||26 Oct 2001||5 Sep 2002||Christophersom Mark A.||Externally worn transceiver for use with an implantable medical device|
|US20030204145 *||29 Apr 2003||30 Oct 2003||Jan Manolas||Device for and method of rapid noninvasive measurement of parameters of diastolic function of left ventricle and automated evaluation of the measured profile of left ventricular function at rest and with exercise|
|US20050103351 *||13 Nov 2003||19 May 2005||Stomberg Charles R.||Time syncrhonization of data|
|DE2604460A1||5 Feb 1976||11 Aug 1977||Michael S Dipl Ing Lampadius||Extended time cardiac action display - has shift register to store sequentially measured cardiac potentials|
|DE3303104A1||31 Jan 1983||2 Aug 1984||Bruss Nii Kardiologii||Device for monitoring cardiac action|
|DE4024360A1||1 Aug 1990||21 Mar 1991||Transform Roentgen Matern Veb||Heart frequency classification circuit - compares input signal with normal and critical threshold values to detect abnormal increase rate|
|EP0080821A2||15 Nov 1982||8 Jun 1983||Datamedix, Inc.||Dual channel ambulatory monitoring unit and system|
|FR2539978A1||Title not available|
|GB2070871A||Title not available|
|1||Ahnve et al., 'Circadian variations in cardiovascular parameters during sleep deprivation, A noninvasive study of young healthy men,' European Journal of Applied Physiology, 1981, 46, pp. 9-19.|
|2||Bibler et al., 'Recurrent ventricular tachycardia due to pentamidine-induced cardiotoxicity,' Chest, Dec. 1988, 94(6), pp. 1303-1306.|
|3||Braunwald, et al.; ACC/AHA Guidelines for the Management of Patients With Unstable Angina and Non-ST-Segment Elevation Myocardial Infarction, Journal of the American College of Cardiology; vol. 36, No. 3, Sep. 2000; 970-1062.|
|4||Circulation; American Heart Association; ECC Guidelines, Part 7: The Era of Reperfusion; http://circ.ahajournals.org/cgi/content/full/102/suppl<SUB>-</SUB>1/I-172?maxtoshow+HIRA=10&hits=10&RES; 2000; 102: I-172.|
|5||Joyal et al., 'ST-segment alternans during percutaneous transluminal coronary angioplasty,' Division of Cardiology, Department of Medicine, University of Florida and the Veterans Administration Medical Center, Jun. 1984, pp. 915-916.|
|6||Kudenchuk, et al., Accuracy of Computer-Interpreted Electrocardiography in Selecting Patients for Thrombolytic Therapy; Journal of the American College of Cardiology; vol. 17, No. 7, Jun. 1991, 1486-91.|
|7||Laks et al., 'ECG computer program developed for a retrospective and prospective study of the Pardee T wave,' Department of Medicine, UCLA School of Medicine, Harbor-UCLA Medical Center, Torrence, CA, 1992, pp. 365-368.|
|8||Little et al., 'Torsade de Pointes and T-U wave alternans associated with arsenic poisoning,' Pace, 1990, 13, pp. 164-170.|
|9||Makarov et al., 'Holter monitoring in the long QT syndrome of children and adolescents,' Cor Vasa, 1990, 32(6), pp. 474-483.|
|10||Mitsutake et al., 'Usefulness of the Valsalva Maneuver in management of the long QT syndrome,' Circulation, 1981, 63(5), pp. 1029-1035.|
|11||Narayanaswamy et al., 'Selective beat signal averaging and spectral analysis of beat intervals to determine the mechanisms of premature ventricular contractions,' University of Oklahoma Health Sciences Center, May 1993, pp. 81-84.|
|12||Navarro-Lopez et al., 'Isolated T wave alternans elicited by hypocalcemia in dogs,' Electrocardiology, 1978, 11(2), pp. 103-108.|
|13||Navarro-Lopez et al., 'Isolated T wave alternans,' American Heart Journal, 1978, pp. 369-374.|
|14||Nearing et al., 'Personal computer system for tracking cardiac vulnerability by complex demodulation of the T wave,' American Physiological Society, 1993, pp. 2606-2612.|
|15||O'Rourke, et al.; Accuracy of a Portable Interpretive ECG Machine in Diagnosis of Acute Evolving Myocardial Infarction; Aust NZ J Med 1992; 22; 9-13.|
|16||Ring et al., 'Exercise-induced ST segment alternans,' American Heart Journal, May 1986, 111(5), pp. 1009-1011.|
|17||Ryan, et al.; 1999 Update: ACC/AHA Guidelines for the Management of Patients With Acute Myocardial Infarction; Journal of the American College of Cardiology; vol. 34, No. 3, Sep. 1999; 890-911.|
|18||Ryan, et al.; ACC/AHA Guidelines for the Management of Patients With Acute Myocardial Infarction; Journal of the American College of Cardiology; vol. 28, No. 5, Nov. 1, 1996; 1328-428.|
|19||Schwartz et al., 'Electrical alternation of the T-wave: clinical and experimental evidence of its relationship with the sympathetic nervous system and with the long Q-T syndrome,' American Heart Journal, Jan. 1975, 89(1), pp. 45-50.|
|20||Schwartz, 'Idiopathic long QT syndrome: progress and questions,' American Heart Journal, Feb. 1985, 109(2), pp. 399-411.|
|21||Sharma et al., 'Romano-Ward prolonged QT syndrome with intermittant T wave alternans and atrioventricular block,' American Heart Journal, 1981, pp. 500-501.|
|22||Speranza et al., 'Beat-to-beat measurement and analysis of the R-T interval in 24 h ECG Holter recordings,' Med and Biol Eng & Comput, 1993, 31, pp. 487-494.|
|23||Stroobandt et al., 'Simultaneous recording of atrial and ventricular monophasic action potentials: monophasic action potential duration during atrial pacing, ventricular pacing, and ventricular fibrillation,' Pace, Jul.-Aug. 1985, 8, pp. 502-511.|
|24||Surawicz, 'ST-segment, T-wave, and U-wave changes during myocardial ischmeia and after myocardial infarction,' Canadian Journal of Cardiology, Supplement A, Jul. 1986, pp. 71A-84A.|
|25||Turitto et al., 'Alternans of the ST segment in variant angina,' Chest, Mar. 1988, 93(3), pp. 587-591.|
|26||Verrier et al., 'Ambulatory electrocardiogram-based tracking of T wave alternans in postmyocardial infarction patients to assess risk of cardiac arrest or arrhythmic death,' Journal of Cardiovascular Electrophysiology, Jul. 2003, 14(7), pp. 705-711.|
|27||Verrier et al., 'Behavioral states and sudden cardiac death,' Pace, Sep. 1992, 15, pp. 1387-1393.|
|28||Verrier et al., 'Electrophysiologic basis for T wave alternans as an index of vulnerability to ventricular fibrillation,' Journal of Cardiovascular Electrophysiology, May 1994, 5(5), pp. 445-461.|
|29||Wayne et al., 'Exercise-induced ST segment alternans,' Chest, May 1983, 83(5), pp. 824-825.|
|30||Weintraub et al., 'The congenital long QT syndromes in childhood,' Journal of the American College of Cardiology, Sep. 1990, 16(3), pp. 674-680.|
|Citing Patent||Filing date||Publication date||Applicant||Title|
|US8892184||18 Oct 2010||18 Nov 2014||Siemens Medical Solutions Usa, Inc.||Systems and methods for reducing interference in a dual modality imaging system|
|US9220430||7 Jan 2014||29 Dec 2015||Alivecor, Inc.||Methods and systems for electrode placement|
|US9247911||10 Jul 2014||2 Feb 2016||Alivecor, Inc.||Devices and methods for real-time denoising of electrocardiograms|
|US9254092||17 Mar 2014||9 Feb 2016||Alivecor, Inc.||Systems and methods for processing and analyzing medical data|
|US9254095||8 Nov 2013||9 Feb 2016||Alivecor||Electrocardiogram signal detection|
|International Classification||A61B5/0452, A61B5/04, A61B5/0472, A61B5/0402, A61B5/00|
|Cooperative Classification||A61B5/0006, A61B5/0472, A61B5/04525|
|European Classification||A61B5/00B3B, A61B5/0452B|
|1 Sep 2004||AS||Assignment|
Owner name: GE MEDICAL SYSTEMS INFORMATION TECHNOLOGIES, INC.,
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ROWLANDSON, G. IAN;ALBERT, DAVID E.;REEL/FRAME:015062/0224;SIGNING DATES FROM 20040603 TO 20040610
|23 Sep 2011||FPAY||Fee payment|
Year of fee payment: 4
|19 Feb 2016||FPAY||Fee payment|
Year of fee payment: 8