59 results about "ECG analysis" patented technology

An AED being powered by 120/240 VAC electrical power alone, being powered by external DC power alone, or any in combination with or without internal-integral battery power, and further an AED access service business method for sales of access to AEDs. The inventive AED, in addition to the defibrillator circuitry comprises a long, tangle free power access cord to be plugged into an external source of AC or DC power and optionally, additional sets of body surface and alternative electrodes positioned in the esophagus and/or heart. The AED has additional advanced capabilities including the ability to deliver rapid sequential shocks through one or more sets of patient electrodes, and the optional mode of shock delivery whereby the shock is delayed while the AED continues to analyze the patients ECG waveform and delays the defibrillation shock or sequence of shocks until the ECG analysis indicates conditions are optimum for successful defibrillation.

In a multi-tier patient monitoring data analysis system, an algorithm server is positioned as a middle tier between an acquisition device, such as a cardiograph or patient monitor that can be seen as a lower tier, and a storage device for a database, such as that of a central computer for a hospital or clinic that can be seen as an upper tier. The algorithm server gathers current data from the real time acquisition device and obtains previously stored ECG signal data from the database. The algorithm server contains ECG analysis algorithm(s) and runs one or more algorithms using the current and previously acquired ECG signal data. Analysis algorithms may also be run on the acquisition device. The system provides the rapid, extensive, and thorough ECG analysis that is critical to patient welfare.

An analysis method of electrocardiogram (ECG) and the device thereof are provided. The method diagnoses a subject by non-invasive method to see whether the subject is at high risk of high mountain disease (HMD). The ECG analysis method comprises: first, detecting the ECG of the subject; transforming the ECG to obtain a plurality of heart rate variability (HRV) parameters; analyzing the HRV parameters and outputting an analyzed result.

The invention provides an ECG (electrocardiogram) diagnosis system which comprises an ECG acquisition system and an ECG analysis and diagnosis system that are connected with each other, wherein the ECG analysis and diagnosis system comprises a DLL (dynamic link library) system, an ECG feature extraction module, and an ECG feature statistical analysis module; and the ECG feature statistical analysis module comprises a plurality of analysis units corresponding to different ECG features; doctors choose the analysis units according to conditions of patients; the ECG feature extraction module takes the corresponding ECG features as ECG feature extraction objects, calls a corresponding dynamic database of the DLL system, to extract the ECG features from ECG data and transmits the ECG features to the ECG feature statistical analysis module; and the ECG feature statistical analysis module conducts statistical analysis on the ECG features for the doctors for diagnosis. The ECG diagnosis system facilitates the quick diagnosis of the doctors, the working efficiency of the doctors is improved, the interaction among the different ECG features is avoided, and the accuracy rate of the analysis is increased. The invention further provides an operating method of the ECG diagnosis system.

Devices and methods are described that provide improved diagnosis from the processing of physiological data. The methods include use of transforms prior to submitting the data to a multiple level neural network. In one embodiment for ECG analysis, a template is used to subtract data that is not pertinent to the diagnosis and then a Fourier transform is applied to the time series data. Examples are shown with applications to electrocardiogram data, but the methods taught are applicable to many types of physiological data.

Medical devices, software and methods are provided, for making a decision as to whether to administer electric shock therapy to a patient. The decision is made with respect to ECG data that is discounted at least partially, and sometimes even completely, if it occurs during a transition between chest compression group and a pause for ventilation.

A diagnostic medical device (900) is described which incorporates an improved ECG analysis algorithm (600, 800) that identifies an arrhythmia treatable by a defibrillation shock, wherein the identification can occur even in the presence of underlying CPR artifact. The analysis algorithm allows for a shorter interval between the application of CPR compressions and the delivery of electrotherapy, and thus increases the likelihood of successful resuscitation. The medical device may also include a defibrillating electrotherapy circuit (920).

A defibrillator and method for using a defibrillator which adopts an ECG analysis algorithm that can detect a cardiac arrhythmia in the presence of noise artifact induced by cardio pulmonary resuscitation (CPR) compressions. The apparatus and method offers guidance throughout a cardiac rescue protocol involving both defibrillation shocks and CPR that improves the effectiveness of the rescue, resulting in more CPR "hands-on" time, better treatment of refibrillation, and reduced transition times between CPR and electrotherapy.

The invention elates to an ECG analysis system and a device and particularly relates to an ECG automatic diagnosis system and a device for cardiac premature beat. In order to solve the problem that the accuracy of automatic diagnosis and analysis of premature beats still needs to be improved. The system of the invention comprises an ECG signal coarsening module, which is used for constructing thecollected ECG signal into an ECG signal time series, and coarsening the ECG signal time series according to a set time scale factor tau; a signal sample entropy module used for calculating the sampleentropy of each group of coarse-grained ECG signal time series and extracting the feature vector; a classifier module which resamples the eigenvector sample set obtained by the signal sample entropy module, obtains resampled samples, and constitutes a random forest classifier. The system and device are used for ECG analysis.

The invention discloses a single-guided heart stick data intelligent diagnosis cloud calculation system and a processing method thereof. The system comprises a client acquisition module, a storage service module, a message queue service module and a calculation service module, wherein the client acquisition module is used for acquiring long-term dynamic electrocardiogram (EEG) data of a single-guided heart stick, uploading the data to the storage service module and downloading required data from the storage service module, the storage service module is used for storing the long-term dynamic ECG data and the ECG analysis report, the message queue service module is used for realizing message transmission and function decoupling, the calculation service module is used for providing hardware resources required for calculation, an ECG scatter plot is drawn based on the long-term dynamic electrocardiogram data of the single-guided heart stick, an AI model is utilized to carry out artificialintelligence diagnosis of the ECG scatter plot, the classification result of the ECG scatter plot is calculated, and the ECG analysis report is formed. The system is advantaged in that on the basis ofstorage service and calculation service of the cloud service architecture, the analysis speed of the dynamic ECG and diagnosis accuracy are effectively improved.

A method of processing images for interventional imaging, wherein a region of interest is visualized, is provided. The method comprises acquiring a series of 2D images of the region of interest in a patient during at least one respiratory phase, acquiring an electrocardiographic signal which is synchronized with the acquisition of the series of 2D images, processing the electrocardiographic signal to estimate at least one deformation phase of the region of interest induced by the patient's respiratory movement, and registering the different successive 2D images in relation to the estimated deformation phase.

The invention relates to the field of monitoring of abnormal performance of student preventive examination, in particular to portable monitoring equipment for abnormal performance of preventive examination based on ECG analysis. The equipment comprises an electrocardiogram collection assembly used for collecting electrocardiogram signals and transmitting the signals, an electrocardiogram display and excitation assembly used for receiving, preprocessing and analyzing the electrocardiogram signals, and a cloud background analysis and processing terminal used for carrying out algorithm processing, analysis and storage on the electrocardiogram signals. The electrocardiogram collecting assembly comprises an electrocardiogram collecting patch used for making contact with a human body and collecting electrocardiogram signals, an ECG chip used for receiving the electrocardiogram signals and conducting recognition processing, a signal transmission module used for transmitting the electrocardiogram signals, and flexible power supply equipment used for supplying power to the electrocardiogram collecting assembly. The equipment is simple in structure and convenient to operate, ECG signal monitoring and data feedback excitation adjustment are achieved, monitoring data are more accurate and representative, and the practicability and high efficiency of the ECG signal monitoring device in use are greatly improved.

The invention discloses a long-distance monitoring and diagnosis system and a processing method for single-guide heart paste data. The system includes a collection terminal, a client and a server; The terminal is used to preprocess the obtained long-term dynamic ECG data, and send the preprocessed ECG signal data to the server, and display the ECG analysis report received from the server to the user; the server: for Draw the ECG scatter diagram according to the obtained ECG signal data, input the ECG scatter diagram to the convolutional neural network model, calculate the classification results of the ECG scatter diagram, form an ECG analysis report and send it to the client. The present invention uses the convolutional neural network model to analyze the collected user's electrocardiogram data on the scatter diagram drawn by the user's electrocardiogram data, which effectively improves the analysis speed of dynamic electrocardiogram and improves the accuracy of diagnosis, and saves the time and cost of electrocardiographic diagnosis physicians. time and reduce the misdiagnosis rate.