115 results about "ST segment" patented technology

Cardiac monitoring and/or stimulation methods and systems that provide one or more of monitoring, diagnosing, defibrillation, and pacing. Cardiac signal separation is employed to detect, monitor, track and/or trend ischemia using cardiac activation sequence information. Ischemia detection may involve sensing composite cardiac signals using implantable electrodes, and performing a signal separation that produces one or more cardiac activation signal vectors associated with one or more cardiac activation sequences. A change in the signal vector may be detected using subsequent separations. The change may be an elevation or depression of the ST segment of a cardiac cycle or other change indicative of myocardial ischemia, myocardial infarction, or other pathological change. The change may be used to predict, quantify, and/or qualify an event such as an arrhythmia, a myocardial infarction, or other pathologic change. Information associated with the vectors may be stored and used to track the vectors.

A system for the detection of cardiac events occurring in a human patient is provided. At least two electrodes are included in the system for obtaining an electrical signal from a patient's heart. An electrical signal processor is electrically coupled to the electrodes for processing the electrical signal. The system determines the presence of a cardiovascular condition by applying a sliding scale rule to heart signal feature values. When the cardiovascular condition is ischemia, the ST segment may be analyzed. A sliding scale is applied to ST segment shifts such that when the magnitudes of ST segment shifts are relatively small, a larger number of beats is required to detect ischemia compared to the case when the magnitudes of ST shifts are large.

An apparatus is provided for evaluating cardiovascular functions. The apparatus combines the principles of measuring pressure and pulse signals, and monitors blood pressure, pulse wave velocity and electrocardiogram (ECG) signals simultaneously. An inflatable cuff measures blood pressure and pulse wave velocity. The apparatus also calculates systolic pressure, diastolic pressure, mean arterial pressure and other parameters related to blood pressure. The apparatus not only calculates vascular Stiffness Index (SI), vascular Reflection Index (RI) and other arterial related parameters but also Pulse Wave Velocity (PWV), heartbeat, QRS interval, ST segment, and other ECG parameters.

A system to detect the presence or absence of T wave alternans is described based on statistical tests and periodicity transform. T wave and ST segment boundaries are detected in multi-lead ECG signals acquired from the regular clinical leads. Once the fiducial point and the above boundaries are delineated, computation of regular parameters like T wave amplitude, area under the T waves or segments of T wave, ST segment slope and/or the curvature of T wave are performed. Each parameter forms a rolling array of values with each successive beat. The array of values, or the time series, is used to make the decision about the T wave alternans. Two different methods are employed based on periodicity transforms and statistical tests. A set of numerical values (e.g. norm of the projection on to p-2 space, sums of adjacent terms after the trend removal, t-value, and number of deviations from alternans pattern) are all computed and compared to threshold values. Threshold values are computed from past information and experience with clinical databases and simulations. Final system comprises a software module, which can be part of the existing ECG monitoring programs as well as external defibrillator modules, apart from being stand-alone algorithms.

A patient diagnostic emergency room triage system includes an implanted cardiac device which may be a cardiosaver, pacemaker or cardiac defibrillator for recording electrogram data associated with the detection of a cardiac event. A communication mechanism receives electrogram data from the implanted cardiac device and a visual display displays the electrogram data recorded by the implanted cardiac device. The visual display permits displaying electrogram data associated with an ST segment related cardiac event.

A system for heart performance characterization and abnormality detection includes an acquisition device for acquiring an electrophysiological signal representing heart beat cycles of a patient heart. A detector detects one or more parameters of the electrophysiological signal of parameter type comprising at least one of, (a) amplitude, (b) time duration, (c) peak frequency and (d) frequency bandwidth, of multiple different portions of a single heart beat cycle of the heart beat cycles selected in response to first predetermined data. The multiple different portions of the single heart beat cycle being selected from, a P wave portion, a QRS complex portion, an ST segment portion and a T wave portion in response to second predetermined data. A signal analyzer calculates a ratio of detected parameters of a single parameter type of the multiple different portions of the single heart beat cycle. An output processor generates data representing an alert message in response to a calculated ratio exceeding a predetermined threshold.

Techniques are described for adaptively adjusting detection thresholds for use in detecting cardiac ischemia and other abnormal physiological conditions based on morphological parameters derived from intracardiac electrogram (IEGM) signals, impedance measurements, or other signals. In one example, where ST segment elevation is used to detect cardiac ischemia, default detection thresholds are determined in advance from an examination of variations in ST segment elevations occurring within a population of patients. Thereafter, an individual pacemaker or other implantable medical device uses the default thresholds during an initial learning period to detect ischemia within the patient in which the device is implanted. During the initial learning period, the pacemaker also collects data representative of the range of variation in ST segment elevations occurring within the patient. The pacemaker then adaptively adjusts the thresholds based on the range of variation so as to improve detection specificity within the patient.

A system for analyzing an ECG signal is provided. The system comprises an interface that receives an ECG waveform associated with heart beat cycle of a patient. The system includes signal processor that determines a first isoelectric portion lying between a T-wave of a first heart beat cycle and a P-wave of a successive heart beat cycle, and a second isoelectric portion lying between a P-wave and a QRS complex of the first heart beat cycle. The signal processor determines a stability measure for each of said first and second portions and adaptively selects the first or the second portion as a baseline for the first heart beat cycle based on the stability measures. The signal processor determines a point of reference on an ST segment associated with the first heart beat cycle and evaluates a deviation of the point of reference on the ST segment from the selected baseline.

Electrocardiologic device for assisted diagnosis, preferably for the diagnosis of Brugada syndrome or Early Repolarization syndrome. This device allows characterizing the ventricular repolarization wave of an ECG signal collected from a patient. Extracting out of the ECG signal, for each heart beat, an ST segment is constituted of a successsion of samples of the ventricular repolarization wave, taken within a time window ([Q_ON+80 ms, Q_ON+140 ms]) of a predetermined duration spreading from a moment of window onset defined by a time offset applied to a predetermined temporal origin given by the moment (Q_ON) of appearance of the QRS complex, whose time position is determined on the ECG signal for each heart beat. Quantizing computes an elevation index compared to a predetermined reference level (BL), and analyzing over a succession of heart beats the persistence and/or variation of this elevation index.

A patient diagnostic emergency room triage system includes an implanted cardiac device which may be a cardiosaver, pacemaker or cardiac defibrillator for recording electrogram data associated with the detection of a cardiac event. A communication mechanism receives electrogram data from the implanted cardiac device and a visual display displays the electrogram data recorded by the implanted cardiac device. The visual display permits displaying electrogram data associated with an ST segment related cardiac event.

The invention discloses a method for performing superposition analysis on electrocardio data of any time segment. The method comprises the following steps of: selecting any segment of representative waveforms from an electrocardiogram; reading electrocardio data and waveform information in the time period; superposing the waveform of each heart beat in the time period and analyzing the waveform type of the superposed waveforms, the forward voltage and the negative voltage of a P wave, the voltage of a Q wave, an R wave and an S wave, the average voltage of an ST segment, the forward voltage and the negative voltage of a T wave, the time limit of the P wave, the Q wave, the R wave, the S wave and the T wave, a QT interval and other data; and providing a human-computer interaction interface, displaying an analysis result obtained after waveforms are superposed, and allowing a user to perform manual intervention on the analysis result. The application scope of an exercise load test is broadened, the accuracy of the test result is improved, and the diagnostic report has higher reference value.

Disclosed is a system for the detection of cardiac events that includes an implanted device called a cardiosaver, a physician's programmer and an external alarm system. The system is designed to provide early detection of cardiac events such as acute myocardial infarction or exercise induced myocardial ischemia caused by an increased heart rate or exertion. The system can also alert the patient with a less urgent alarm if a heart arrhythmia is detected. Using different algorithms, the cardiosaver can detect a change in the patient's electrogram that is indicative of a cardiac event within five minutes after it occurs and then automatically warn the patient that the event is occurring. To provide this warning, the system includes an internal alarm sub-system (internal alarm means) within the cardiosaver and/or an external alarm system (external alarm means) which are activated after the ST segment of the electrogram exceeds a preset threshold.

The invention discloses an application of umbilical cord mesenchymal stem cells (MSCs) in the acute myocardial infarction cell transplantation therapy; the application is suitable for ST-segment elevation acute myocardial infarction within one mouth or non ST-segment elevation acute myocardial infarction cases, a vascular remodeling is carried out to a patient who is attacked by the disease withinsix hours, after about four to six days, coronary perfusion is carried out to the patient; and the other patients who choose date to carry out vascular remodeling operation, the coronary perfusion iscarried out at the same time. The treating effect in the invention is superior to the bone mesenchymal stem cells transplantation.

A magnetic dipole model based on MCG data of the heart is used to localize cardiac tissue afflicted with ischemia. The direction of diaplacement of the dipole during the ST segment, superimposed on the heart's general outline, indicates a rough location of the ischemic cardiac tissue. Furthermore, the extent of ischemia is quantified based upon the how much displacement occurs in the ST segment. For example, if significant dipole's displacement occurs in the first quarter of the ST segment, then it is identified as a first-degree ischemia. Similarly, if diaplacement occurs in 1/2, 3/4, or 1 full ST segment, then the level of ischemia is identified as second degree, third degree, or fourth degree ischemia (fourth degree being the worst kind of ischemia where the dipole's position is dynamic all through the ST segment).

A method and system for predicting the onset of heart arrhythmias more accurately observes trends in abnormal or pathologic morphology of the electrocardiogram (ECG). A first set of ECG signals is monitored from a patient. A baseline measurement is generated from the monitored first set of ECG signals to contain nonpathologic ECG morphologies in each lead. A second set of ECG signals is monitored from the patient and the baseline measurement is subtracted from the second set of ECG signals on a beat-to-beat basis. Afterwards, a residuum signal is generated for each lead based on the subtraction. R-wave heterogeneity, T-wave heterogeneity, P-wave heterogeneity, or ST-segment heterogeneity or other indicators of arrhythmia risk or myocardial ischemia are quantified based on the generated residuum signals.

The invention discloses a method for recognizing the ST segment of an electrocardiosignal. According to the method, a wave S and a wave T are accurately located through a slope ratio extremum method based on a peak R for the filtered electrocardiosignal, and finally the displacement, slope and length characteristics of the ST segment are accurately recognized. The method is simple in calculation, easy to implement and high in accuracy rate, and a new way is provided for fast and effective recognition of the electrocardiosignal.

The invention discloses a coronary heart disease self-diagnosis system based on electrocardiographic monitoring and back-propagation neural network, comprising an electrocardiographic collection terminal and a hospital monitoring center computer system, wherein the electrocardiographic collection terminal is composed of an electrocardiographic monitoring collector and a data transmission module based on wired or wireless data transmission. By means of multi-scale features of wavelet transformation, the system of the invention completes the extraction of wave peak points and the detection of ST segment in different scale decomposition coefficients by adopting a quadratic spline wavelet transformation method, thus the electrocardiographic waveform of the clinical patient can be accurately extracted. On the basis of correctively extracting characteristic points, an electrocardiogram ST segment pattern recognition model is set up by using a BP (Back-Propagation) neutral network in order to successfully recognize the pattern of the ST segment, and the initial weight and the threshold of the BP neutral network are optimized by using genetic algorithm and DNA (deoxyribonucleic acid) algorithm, thereby problem that the BP neutral network is liable to fall into local optimum in the process of training is solved, and the pattern recognition of ST segment and the diagnosis of coronary heart disease in the manner of artificial experience before are replaced.