98 results about "Electrocardiographic waveform" patented technology

A plurality of electrodes for measuring electrocardiogarphic waveforms are attached on body surface positions that constitute a subset of the standard 12-lead system. The measured electrocardiogarphic waveforms of said subset of said standard 12-lead system are used to calculate the electrocardiogarphic waveforms of remaining leads in the said standard 12-lead system. The measured and calculated electrocardiographic waveforms are synthesized to form a standard 12-lead electrocardiogram. The invention is capable of monitoring the 12-lead electrocardiogram with reduced number of electrodes, wherein a portion of waveforms are directly measured and used as primary information for diagnosing heart disease, and the other portion of waveforms are derived from the measured leads and are used as a secondary information for improving the accuracy of diagnosis. The invention is especially useful in monitoring ischemic heart disease and acute myocardial infarction in cases where mounting and maintaining ten electrodes to obtain 12-lead electrocardiogram is difficult, such as in ambulatory monitoring, long-term monitoring and home monitoring.

A method for analyzing a subject-visit group of ECG waveforms captured digitally on an electrocardiograph machine, on a Holter monitor device or digitized from paper electrocardiograms. A cardiologist selects a subject-visit group from a number of subject-visit groups, and each ECG waveform of the subject-visit group is scanned for artifact. Those ECG waveforms containing artifact are annotated appropriately. A determination is made if measurement calipers are present in each ECG waveform, measurement calipers are added to ECG waveforms lacking measurement calipers, and a preliminary interpretation is assigned to each ECG waveform that lacks a preliminary interpretation. Each ECG waveform is assigned a grouping metric, and the ECG waveforms are segregated according to their grouping metric for display and evaluation.

Method and apparatus for preventing heart rhythm disturbances by recording cardiac electrical activity, measuring beat-to-beat variability in the morphology of electrocardiographic waveforms, and using the measured beat-to-beat variability to control the delivery of drug therapy and electrical impulses to the heart.

A portable electrocardiograph having a display function and a display method for the electrocardiograph are disclosed in which the information on display can be easily recognized visually. In measuring an electrocardiographic waveform using an electrocardiograph (1), the electrocardiograph (1) is held in position by a grip including a negative electrode (14) while at the same time pressing a contact section including a positive electrode (16) against an electrode contact portion other than the right hand of the subject. In the electrocardiograph (1), the measurement result such as an electrocardiographic waveform is displayed on a display unit (10) during the measurement operation. The measurement method is divided into what is called the induction mode I in which the contact section including the positive electrode (16) is pressed against the left hand of the subject, and what is called the induction mode II in which the contact section including the positive electrode (16) is pressed against the lower left abdomen of the subject. In the measurement conducted according to induction mode I, the measurement result is displayed in horizontal position on the display (10), while in the measurement conducted in the induction mode II, the measurement result is displayed in vertical position on the display (10).

A motion parameter measuring unit two-dimensionally measures a motion parameter of a myocardial tissue by a tracking process on time-series ultrasonic image data acquired by transmission and reception of ultrasonic waves to and from a sample. On the other hand, a time phase setting unit adds a diastolic heartbeat time phase, which is set on the basis of a systole end specified by a time phase where a cardiac cavity area of the ultrasonic image data is the smallest and a diastole end specified by an R wave in an electrocardiographic waveform of the sample, relative to the systole end to time-series parameter image data generated by a parameter image data generating unit on the basis of the motion parameter. An image data extracting unit extracts parameter image data to which the diastolic heartbeat time phase closest to a desired diastolic heartbeat time phase set by an input unit is added and displays the extracted parameter image data on a display unit.

A portable electrocardiograph includes an electrode unit brought into contact with a living body of a subject, a processing circuit measuring an electrical signal detected by the electrode unit with being in contact with the living body as an electrocardiographic waveform, and a display unit displaying a measurement result of the electrocardiographic waveform. In measurement, when a CPU of the processing circuit receives the electrical signal of the electrocardiographic waveform via the electrode unit, an amplifier circuit, a filter circuit, and an A/D converter, the CPU detects whether or not baseline fluctuation in the electrocardiographic waveform deviates from a predetermined range in which analysis of the waveform is acceptable, based on the received electrical signal. If the CPU detects deviation from the predetermined range, it displays such information on the display unit as a measurement result.

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.

The invention discloses an automatic gain-regulated output method for waveform drawing of a multi-channel electrocardiograph, which comprises the following steps: (1) detecting and calculating the voltage amplitude of an electrocardiographic waveform of each channel; (2) determining the magnitude of the automatic gain of the electrocardiographic waveform of each channel based on the magnitude of the voltage amplitude obtained in the step (1); (3) carrying out gain processing on an original signal of the electrocardiographic waveform of each channel based on the magnitude of the automatic gain; and (4) drawing the electrocardiographic waveforms obtained after gain processing on an interface, recording and outputting. The invention simultaneously meets the requirements for both interface displaying and recording and outputting, and can achieve a better balance between the both. When being used for an electrocardiograph with a large number of channels (e.g. 12 channels), the automatic gain-regulated output method provided by the invention can achieve a more obvious optimization effect.

In order to derive a standard 12-lead electrocardiogram, ones of limb leads and chest leads which constitute a lead system for the standard 12-lead electrocardiogram using 10 electrodes are selected. Electrocardiographic waveforms corresponding to the selected ones of the limb leads and the chest leads are obtained, as measured electrocardiographic waveforms, with electrodes attached on a living body. Electrocardiographic waveforms corresponding to a remaining ones of the limb leads and the chest leads are calculated, as non-measured electrocardiographic waveforms, with a prescribed transformation matrix and the measured electrocardiographic waveforms.

An X-ray CT apparatus detects a predetermined characteristic wave from each electrocardiographic waveform acquired from an electrocardiograph, predicts intervals with which the characteristic wave appears based on appearance times of the detected predetermined characteristic wave in each electrocardiographic waveform, and determines an X-ray irradiation start time based on the predicted interval time. After an instruction to start collection of X-ray intensity distribution data is received, if an appearance interval of a detected predetermined characteristic wave is within an acceptable normal-heartbeat range, it is determined as a normal heartbeat. If the appearance interval of the detected predetermined characteristic wave is outside the acceptable normal-heartbeat range, it is determined as an abnormal heartbeat. During a period after receiving the instruction to start the collection until reaching a time of starting the collection of X-ray detection information, when determined as an abnormal heartbeat, an X-ray irradiation start time is recalculated, and then determined.

In a portable electrocardiograph, combinations of analysis results corresponding to analysis items of an electrocardiographic waveform based on electrocardiography and display contents are stored in advance in association with each other. Thereby, the portable electrocardiograph analyzes obtained electrocardiographic waveform data to classify the electrocardiographic waveform data by the analysis items based on electrocardiography. It collates a classification result being classified and the combinations of analysis results stored to select a corresponding display content. It displays the selected display content as an evaluation of the electrocardiographic waveform data.

The invention relates to the technical field of image processing, and specifically relates to an electrocardiogram (ECG) analysis method and ECG analysis apparatus. In order to solve the problems of lack of high-quality medical labeling and lack of interpretable auxiliary analysis in the prior art, the invention discloses the ECG analysis method comprising the following steps: obtaining text semantic information vector corresponding to each ECG on basis of a plurality of ECGs acquired in advance through a text semantic information extraction model; obtaining ECG waveform vector corresponding to each ECG on basis of the plurality of ECGs through an ECG waveform vector extraction model; obtaining a first ECG analysis result according to the text semantic information vectors, the ECG waveformvectors and a first event set acquired in advance; obtaining a second ECG analysis result according to the text semantic information vectors and the ECG waveform vectors; and then, obtaining ECG event corresponding to each ECG according to the first ECG analysis result and the second ECG analysis result. The ECG analysis method disclosed by the invention is capable of directly interpreting ECGs in PDF format.

A transmitting/receiving circuit drives an ultrasonic probe in accordance with a trigger signal based on an electrocardiographic waveform under the control of a control device so as to scan a plurality of regions, and obtains scan data for each region. During the scanning, the transmitting/receiving circuit causes the ultrasonic probe to scan the respective regions so that scan data in which time phases of the electrocardiographic waveform substantially coincide are obtained in the vicinities of the boundary between at least two adjacent regions among the plurality of regions. That is, in adjacent regions, the transmitting/receiving circuit causes the ultrasonic probe to scan the respective regions in the main or sub-scanning directions set to be reverse to each other. Further, an image processor generates ultrasonic image data of the range in which the plurality of regions are joined, on the basis of the scan data obtained by starting scanning at the same time phase.

An electrocardiograph and an electrocardiograph control method capable of recording the electrocardiographic waveform under satisfactory measurement conditions with a simple operation are disclosed. In the case where a measurement switch is depressed (MEASUREMENT SW in S10) in sleep mode, a CPU starts the main power supply and sets the electrocardiograph in active mode and performs the initial operation for starting to control the various parts (S20). Further, the electrocardiograph selects a measurement program for executing the measurement function thereof, and the process before step S60 is skipped to branch to the measurement process.

The invention discloses a coronary heart disease self-diagnosis system with electrocardiographic monitoring and self-adaptive fuzzy reasoning network, which comprises an electrocardiogram acquisition terminal and a hospital monitoring center computer system. The electrocardiogram acquisition terminal is composed of an electrocardiographic monitoring and acquiring instrument and a data transmission module based on wired or wireless data transmission. Based on multi-dimension feature of wavelet transformation, the system of the invention completes the extraction for crest value points and the detection for ST segment in different dimensional decomposition coefficients by using quadratic spline wavelet transformation, thus electrocardiographic waveform of clinical patients can be accurately extracted. Based upon corrective extraction of characteristic points, six electrocardiogram ST segment morphologic models constructed by using self-adaptive fuzzy reasoning network training method succeed in ST segment morphologic recognition and replace the former human experience way for ST segment morphologic recognition and diagnosis of coronary heart disease.