Intra-cardiac voltage data display systems display a plurality of data sets derived at least from intra-cardiac voltage data sampled by an electrode. In some embodiments, at least some of the data sets are derived from a portion of the intra-cardiac voltage data that excludes an excludable portion of the intra-cardiac voltage data having a relationship with an occurrence of a particular cardiac event to facilitate identification of the existence of a transmural lesion in tissue adjacent the electrode. In some embodiments, the particular cardiac event is the occurrence of an R wave in the cardiac cycle, and the excludable portion is a V wave in the cardiac cycle.

A system and method of locating a source of a heart rhythm disorder are provided in which a first pair of cardiac signals is processed to define a first coefficient associated with variability of the first pair of signals at a first region of the heart. A second pair of cardiac signals is processed to define a second coefficient associated with variability of the second pair of signals at a second region of the heart. Thereafter, the first coefficient of variability is compared to the second coefficient of variability to determine a direction towards the source of the rhythm disorder.

Methods for displaying physiological mapping data are disclosed. An example method may include storing a set of three-dimensional positional data on a memory, storing a set of metric data on the memory, and storing a set of electrogram data on the memory. The method may also include outputting the set of three-dimensional positional data, the set of two-dimensional metric data, and the set of electrogram data from the memory to a display unit and displaying the set of three-dimensional positional data, the set of two-dimensional metric data, and the set of electrogram data on the display unit as a dynamic display.

An authentication apparatus includes one or more processors configured to temporally implement a neural network, used to extract a feature value from hidden nodes, that is connected to input nodes to which an electrocardiogram (ECG) signal is input so as to share a weight set with the input nodes, and to match the ECG signal and the extracted feature value to a user for registration.

An example method includes analyzing morphology and/or amplitude of each of a plurality of electrophysiological signals across a surface of a patient's body to identify candidate segments of each signal satisfying predetermined conduction pattern criteria. The method also includes determining a conduction timing parameter for each candidate segment in each of the electrophysiological signals.

A Phono-Electro-Cardiogram Monitoring Unit that detects and monitors ECG and PCG signal comprising a phono-electro-cardiogram sensor button capable of electrical conduction of the electrical potential changes arising from the heart activity of a user or a patient. The sensor button includes a microphone which allows detection of electrocardiography signal and phonocardiogram signal simultaneously and the detected electrocardiography signal and phonocardiogram signal are processed by a multifunction microprocessor and the processed electrocardiography signal and phonocardiogram signal data are stored in a memory or be transmitted to a work station or a personal cloud for further processing and storing where the data can be forwarded to authorized individuals via wireless connectivity for communication, interpretation, service and help.

A diagnosis support apparatus for physiological monitoring includes a data acquisition device for obtaining information of a heartbeat waveform of an examinee. An extractor extracts blood pressure fluctuations based on changes of blood pressure of the examinee from the heartbeat waveform. A guide information output device outputs guide information for induction of respiratory cycle time of breathing of the examinee according to a period of the blood pressure fluctuations. An arithmetic processor obtains a parameter value related to intensity of the heartbeat waveform. A determiner determines occurrence or non-occurrence of a problem in autonomic activity in an autonomic nervous system in the examinee according to the parameter value. A result output device outputs a determination result of the determiner. Also, the determiner performs the determining according to a maximum of the parameter value within a predetermined first period.

A method and system are presented for use in assessment of at least one cardiac parameter of an individual. An electrodes arrangement is applied to an individual's body, for applying an electrical field to the body and providing an electrical output indicative of a systolic impedance change and of a velocity of said change during a cardiac cycle. Also provided is additional data indicative of at least of the following conditions of the individual: a value of total peripheral resistance (TPR), a value of cardiac index (CI), and existence of the AHF condition. Data corresponding to these condition is analyzed to determine whether the TPR satisfies a first predetermined condition and/or the CI satisfies a predetermined second condition and/or whether the acute heart failure (AHF) condition is identified, to thereby use the data indicative of the measured electrical output and selectively calculate said at least one cardiac parameter based on either the systolic impedance change data or on said data of the velocity of the impedance change.

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.

A defibrillating system includes a processor coupled to a memory. The processor and the memory are configured to identify a treatment event associated with treatment of a victim with the defibrillating system, and transmit a representation of a portion of an ECG signal associated with the identified treatment event. In some cases, the processor and the memory are configured to identify the portion of the ECG signal associated with the identified treatment event. In some cases, the portion of the ECG signal is of a predetermined length of time having a start time and an end time based on a time associated with the identified treatment event.