199 results about "Heart activity" patented technology

A mapping catheter is positioned in a heart chamber, and active electrode sites are activated to impose an electric field within the chamber. The blood volume and wall motion modulates the electric field, which is detected by passive electrode sites on the preferred catheter. Electrophysiology measurements, as well as geometry measurements, are taken from the passive electrodes and used to display a map of intrinsic heart activity.

Methods and systems for long term monitoring of one or more physiological parameters such as respiration, heart rate, body temperature, electrical heart activity, blood oxygenation, blood flow velocity, blood pressure, intracranial pressure, the presence of emboli in the blood stream and electrical brain activity are provided. Data is acquired non-invasively using ambulatory data acquisition techniques.

An apparatus, system, and method are disclosed for detecting seizure symptoms in an individual 102. A sensor module 202 receives physiological data for an individual 102 from one or more sensors 110, 112, such as a heart activity sensor. A feature detection module 204 detects a predefined feature 500, 520, 530, 540 in the physiological data. The predefined feature 500, 520, 530, 540 is associated with a seizure or another medical condition. An alert module 206 broadcasts an alert in response to the feature detection module 204 detecting the predefined feature 500, 520, 530, 540.

Apparatus and associated methodology for monitoring correlatable anatomical electrical and sound signals, such as electrical and audio signals produced by human heart activity, including (a) attaching to a selected, common anatomical site ECG (or other) electrode structure, and a multi-axial sound sensor, and (b) simultaneously collecting from adjacent that site both ECG(or other)-electrical and sound signals, where such sound signals arrive adjacent the site along multiple, angularly intersecting axes.

A heart activity sensor structure includes a flexible substrate being substantially non-conductive, at least two electrodes printed on one side of the flexible substrate and configured to be placed against a skin of a user in order to measure biometric signals related to heart activity, and an electrostatic discharge shield printed on opposite side the flexible textile substrate, compared to the printing of the at least two electrodes, for protecting the at least two electrodes from static electricity.

The present invention provides a system for vehicle security, personalization, and cardiac activity monitoring of a driver wherein electrocardiography of a driver is monitored and registered which is used for identification of a person entering in the vehicle and personalization of vehicle based on user preferences thereby act as intruder detection towards vehicle security. In addition to registration the present invention also monitors cardiac activity of driver in a continuous and real time fashion without any intrusion to driver with the facility of generation of alert and making emergency call.

The use of machine learning for pattern recognition in magnetocardiography (MCG) that measures magnetic fields emitted by the electrophysiological activity of the heart is disclosed herein. Direct kernel methods are used to separate abnormal MCG heart patterns from normal ones. For unsupervised learning, Direct Kernel based Self-Organizing Maps are introduced. For supervised learning Direct Kernel Partial Least Squares and (Direct) Kernel Ridge Regression are used. These results are then compared with classical Support Vector Machines and Kernel Partial Least Squares. The hyper-parameters for these methods are tuned on a validation subset of the training data before testing. Also investigated is the most effective pre-processing, using local, vertical, horizontal and two-dimensional (global) Mahanalobis scaling, wavelet transforms, and variable selection by filtering. The results, similar for all three methods, were encouraging, exceeding the quality of classification achieved by the trained experts. Thus, a device and associated method for classifying cardiography data is disclosed, comprising applying a kernel transform to sensed data acquired from sensors sensing electromagnetic heart activity, resulting in transformed data, prior to classifying the transformed data using machine learning.

This invention relates to a system and a kit for stress and relaxation management. A cardiac activity sensor (101) is used for measuring the heart rate variability (HRV) signal of the user and a respiration sensor (102) for measuring the respiratory signal of the user. The system contains a user interaction device (103) having an input unit (104) for receiving user specific data and an output unit for providing information output to the user. A processor (106) is used to assess the stress level of the user by determining a user related stress index. The processor is also used to monitor the user during a relaxation exercise by means of determining a relaxation index based on the measured HRV and respiratory signals, the relaxation index being continuously adapted to the incoming measured signals and based thereon the processor instructs the output unit to provide the user with biofeedback and support messages. Finally, the processor uses the user specific data as an input in generating a first set of rules defining an improvement plan for self-management of stress and relaxation. The first set of rules is adapted to trigger commands instructing the output unit to provide the user with motivation related messages. Also, at least a portion of said user specific data is further used to define a second set of rules indicating the user's personal goals.

A method and apparatus to detect irregular heart activity and estimate heart rate. In one embodiment, the heart rate estimation apparatus includes a group of six RR storage structures that receives an input of six successive RR interval values. The apparatus also includes a probability engine coupled to the group of RR storage structures, the probability engine is operable to calculate and output a mean value of the six RR interval values and a median value of the mean value and the six RR interval. In one embodiment, the apparatus carries out a method including the acts of determining a plurality of interval values between successive R waves; determining a mean of a group of six interval values; determining a median interval value for a group including the group of six interval values and the mean of the group of six interval values; and determining a running average of interval values between successive R waves using the median interval value.

In a method for acquisition of magnetic resonance images of the heart, MR signals of the heart are acquired using an imaging sequence, wherein the magnetization is inverted by an RF inversion pulse before the acquisition of the MR signals; and of the heart activity is detected, and the point in time of the switching of the RF inversion pulse dependent on the detected heart activity.

An automated external defibrillator (AED) and methods for reducing the delay between termination of cardiopulmonary resuscitation (CPR) and administration of a defibrillating shock, among other disclosed apparatus and methods. In one embodiment, the AED includes an ECG sensor that obtains an ECG signal corresponding to patient heart activity and a prompting device that provides instructions regarding cardiopulmonary resuscitation. The AED also has a control system including a microprocessor programmed to run two rhythm analysis algorithms after instructions to terminate CPR. The two rhythm analysis algorithms analyze segments of the ECG signal for recognizing the presence of a shockable rhythm, with one algorithm having a delayed start relative to the other algorithm. The AED additionally includes a therapy generation circuit for treating the shockable rhythm with a defibrillation pulse in response to the control system determining the presence of a shockable rhythm.

The invention discloses a device for classifying dynamic electrocardio data. The device comprises an electrocardio data collecting device, an electrocardio information database, an electrocardio index obtaining device, an electrocardio index screening device, a feature combination obtaining device, a classifier screening device and a classification result output device, wherein the electrocardio index screening device is used for carrying out difference analysis on electrocardio indexes to screen out electrocardio indexes with significance differences, the feature combination obtaining device is used for carrying out feature combination on at least two items in the electrocardio indexes, with the significance differences, screened by the electrocardio index screening device to obtain a plurality of feature combinations, the classifier screening device adopts a plurality of classifiers for testing the feature combinations obtained by the feature combination obtaining device so as to screen out the optimum classifier and the optimum feature combination, the classification result output device is used for receiving the personnel information of patients and pathological data relevant to the heart activity state, classifying the pathological data, relevant to the heart activities, of the patients according to the optimum feature combination and the optimum classifier screened out by the classifier screening device, and outputting the classification results.

A heart activity sensor structure includes a flexible textile substrate, and at least two electrodes with an electric insulation between each of the at least two electrodes. The at least two electrodes are applied on one side of the flexible textile substrate and configured to be placed against a skin of an exerciser in order to measure biosignals related to heart activity. The heart activity sensor also includes an electrostatic discharge shield applied on one side of the flexible textile substrate for protecting the at least two electrodes from static electricity.

Described is an apparatus for oxygenation and/or CO2 clearance of a patient, comprising: a flow source or a connection for a flow source for providing a gas flow, a gas flow modulator, a controller to control the gas flow, wherein the controller is operable to: receive input relating to heart activity and/or trachea gas flow of the patient, and control the gas flow modulator to provide a varying gas flow with one or more oscillating components with a frequency or frequencies based on the heart activity and/or trachea flow of the patient.

A blood pump control system includes a local processing terminal and a remote processing terminal. The local processing terminal is configured to transmit to the remote processing terminal, collected current state parameters of the blood pump and heart activity indexes, and to drive and control the blood pump according to blood pump adjusting parameters received from the remote processing terminal. The remote processing terminal is configured to obtain current blood pump adjusting parameters according to the current state parameters, and the heart activity indexes received from the local processing terminal, and set adjusting conditions; and to transmit the blood pump adjusting parameters back to the local processing terminal.

A semi-automatic atrial defibrillation system monitors activity of a heart, detects atrial fibrillation (AF), and cardioverts detected AF. The system includes an implantable atrial defibrillator capable of communicating with an external portable device that can further communicate with a remote service center. The implantable atrial defibrillator is capable of detecting AF, automatically sending warning signal and diagnostic data to an external portable device after detection of AF, receiving commands from the external portable device, and cardioverting AF. The external portable device is capable of sending commands to the implantable atrial defibrillator, receiving data from the implantable atrial defibrillator, providing patient discernable warning signal and brief diagnostic information after detection of AF, and transmitting diagnostic information to the remote service center. The external portable device is operable by the patient, who may self-control the delivery of atrial cardioversion therapy after receiving the AF warning message, or may contact the remote service center for physician's advice before taking any action.