Techniques and devices for implementing the techniques for adjusting atrial arrhythmia detection based on analysis of one or more P-wave sensing windows associated with one or more R-waves. An implantable medical device may determine signal characteristics of the cardiac signal within the P-wave sensing window, determine whether the cardiac signal within the sensing window corresponds to a P-wave based on the determined signal characteristics, determine a signal to noise ratio of the cardiac signal within the sensing window, update the arrhythmia score when the P-wave is identified in the sensing window and the determined signal to noise ratio satisfies a signal to noise threshold.

An apparatus and a method of measuring bioinformation are provided. The apparatus for measuring bioinformation includes a first sensor configured to measure a first biosignal including arterial pulse wave information, a second sensor configured to measure a second biosignal including venous or capillary pulse wave information, and a bioinformation estimator configured to estimate bioinformation of a user based on a time delay between the first biosignal and the second biosignal.

An apparatus and a method of measuring bioinformation are provided. The apparatus for measuring bioinformation includes a first sensor configured to measure a first biosignal including arterial pulse wave information, a second sensor configured to measure a second biosignal including venous or capillary pulse wave information, and a bioinformation estimator configured to estimate bioinformation of a user based on a time delay between the first biosignal and the second biosignal.

The present invention relates to a method to provide a mean temporal spatial isochrone (TSI) feature relating to an ECG feature (wave form) of interest, such as the activation of the heart from a single point (QRS), relative to the heart in a torso while using an ECG measurement from an ECG recording device. The method includes: receiving ECG measuring data from the ECG recording device; determining vector cardiogram (VCG) data; receiving a model of the heart, preferably with torso, as an input, preferably based on a request including request parameters; determining mean TSI data values representing the TSI feature relating to an electrophysiological phase representing the ECG feature, the mean TSI providing a location within the heart representing the mean location of the ECG feature at the corresponding time; positioning the mean TSI feature and preferably the vector cardiogram data points in the model of the heart and/or torso at an initial position; and rendering the model of the heart, preferably with torso, with the mean TSI feature, preferably with VCG data related to the TSI, for displaying on a display screen for interpretation of the displayed rendering.

Medical apparatus and methods for diagnostic and site determination of cardiac arrhythmias within a heart of a subject are provided. A computing device receives, records and processes electrocardiogram (ECG) signals in the form of bipolar and unipolar ECGs associated with respective cardiac tissue locations corresponding to catheter distal end sensors on locations. Unipolar ECGs that include signals from a plurality of successive heartbeats corresponding to locations within an area of study are analyzed to identify Fractionated Unipolar ECG Signal Complexes (FUESCs) of unipolar ECGs by defining complexes of the unipolar ECGs that correspond to respective bipolar activity windows. Identified arrhythmia sites for treatment include a predetermined number of unipolar ECGs that have a predetermined number of FUESCs. Atrial arrhythmia sites for treatment by ablation can be identified with respect to FUESCs of unipolar ECGs that include signals from at least ten successive heartbeats of an atrial tissue study area.

Medical apparatus and methods for diagnostic and site determination of cardiac arrhythmias within a heart of a subject are provided. A computing device receives, records and processes electrocardiogram (ECG) signals in the form of bipolar and unipolar ECGs associated with respective cardiac tissue locations corresponding to catheter distal end sensors on locations. Unipolar ECGs that include signals from a plurality of successive heartbeats corresponding to locations within an area of study are analyzed to identify Fractionated Unipolar ECG Signal Complexes (FUESCs) of unipolar ECGs by defining complexes of the unipolar ECGs that correspond to respective bipolar activity windows. Identified arrhythmia sites for treatment include a predetermined number of unipolar ECGs that have a predetermined number of FUESCs. Atrial arrhythmia sites for treatment by ablation can be identified with respect to FUESCs of unipolar ECGs that include signals from at least ten successive heartbeats of an atrial tissue study area.

A method includes, based on respective signals acquired by a plurality of electrodes on an anatomical surface of a heart, computing respective local activation times (LATs) at respective locations of the electrodes. The method further includes, based on the LATs, computing respective directions of electrical propagation at the locations. The method further includes selecting pairs of adjacent ones of the electrodes such that, for each of the pairs, a vector joining the pair is aligned, to within a predefined threshold degree of alignment, with the direction of electrical propagation at the location of one of the electrodes belonging to the pair. The method further includes associating respective bipolar voltages measured by the pairs of electrodes with a digital model of the anatomical surface. Other examples are also described.

A method includes obtaining multiple local activation times (LATs) at different respective measurement locations on an anatomical surface of a heart. The method further includes computing respective directions of electrical propagation at one or more sampling locations on the anatomical surface, by, for each sampling location, selecting a respective subset of the measurement locations for the sampling location, constructing a set of vectors, each of at least some of the vectors including, for a different respective measurement location in the subset, three position values derived from respective position coordinates of the measurement location and an LAT value derived from the LAT at the measurement location, and computing the direction of electrical propagation at the sampling location based on a Principal Component Analysis (PCA) of a 4×4 covariance matrix for the set of vectors. The method further includes indicating the directions of electrical propagation on a display.

A system comprises processing circuitry and memory comprising program instructions that, when executed by the processing circuitry, cause the processing circuitry to: apply a first set of rules to first patient parameter data for a first determination of whether sudden cardiac arrest of a patient is detected; determine that a one or more context criteria of the first determination are satisfied; and in response to satisfaction of the context criteria, apply a second set of rules to second patient parameter data for a second determination of whether sudden cardiac arrest of the patient is detected. At least the second set of rules comprises a machine learning model, and the second patient parameter data comprises at least one patient parameter that is not included in the first patient parameter data.

There is provided a nerve activity monitoring method that includes receiving an input signal indicative of activity in a nerve of a subject; receiving physiological data indicative of physiological activity in the subject; establishing a relationship between the physiological data and the input signal; identifying a plurality of periodic portions in the input signal based on the relationship between the physiological data and the input signal; and outputting the periodic portions identified.