Abstract: A method of atrial focal source detection is provided which includes detecting, via sensors, electro-cardiogram (ECG) signals over time. Each ECG signal is detected via one of the sensors and indicates electrical activity of a heart. The method also includes determining, for each ECG signal, local activation times (LATs) each indicating a time of one of a plurality of atrial activations of a corresponding ECG signal and detecting whether one or more focal source areas of activation in the heart is indicated based on the detected ECG signals and the one or more local LATs. S-waves can be distinguished from non-S-waves by generating models for each atrial activation and classifying atrial activations. Maps can be generated by visually indicating, for each sensor, a level of incidence of the atrial activations occurring before atrial activations of neighboring sensors within a period of time.

Abstract: A system comprising: at least one sensor, comprised within a wireless wearable electronic device, the sensor configured to sense, over a given time period, information enabling determination of a Heart Rate Variability (HRV) of a wearer of the wireless wearable electronic device; and one or more processing units configured to: obtain, from the sensor, the information enabling determination of the HRV of the wearer; determine, using the information, the HRV of the wearer; calculate, utilizing the HRV, a stress score indicative of a stress level of the wearer.

Abstract: A method of determining target heart ablation regions is provided which includes detecting electro-cardiogram (ECG) signals each indicating an electrical activity of a heart over time and determining, for each of the ECG signals, local activation times (LATs) each indicating a time of electrical activation for an area the heart. The method also includes generating, based on the LATs, electrical activity mapping information for displaying one or more maps representing the electrical activity of the heart and alternatively, or in addition to the electrical activity mapping information, generating spatio-temporal mapping information for one or more maps representing a spatio-temporal manifestation of the conditions indicative of cardiac arrhythmia, such as atrial fibrillation (AF). The method further includes determining a region of interest (ROI) of the heart by identifying the ROI as a region exhibiting conditions indicative of cardiac arrhythmia based on the mapping information.

Abstract: A method of atrial focal source detection is provided which includes detecting, via sensors, electro-cardiogram (ECG) signals over time. Each ECG signal is detected via one of the sensors and indicates electrical activity of a heart. The method also includes determining, for each ECG signal, local activation times (LATs) each indicating a time of one of a plurality of atrial activations of a corresponding ECG signal and detecting whether one or more focal source areas of activation in the heart is indicated based on the detected ECG signals and the one or more local LATs. S-waves can be distinguished from non-S-waves by generating models for each atrial activation and classifying atrial activations. Maps can be generated by visually indicating, for each sensor, a level of incidence of the atrial activations occurring before atrial activations of neighboring sensors within a period of time.

Abstract: A system and method of identifying focal sources is presented. The method can comprise detecting, via sensors, electro-cardiogram (ECG) signals over time, each ECG signal detected via one of the sensors having a location in a heart and indicating electrical activity of the heart, each signal comprising at least an R wave and an S wave; creating an R-S map comprising an R-to-S ratio for each of the ECG signals, the R-to-S ratio comprising a ratio of absolute magnitude of the R wave to absolute magnitude of the S wave; identifying, for each of the ECG signals, local activation times (LATs); and correlating the R-to-S ratios for the ECG signals on the R-S map and the identified LATs and using the correlation to identify the focal sources.

Abstract: A method of atrial rotational activity pattern (RAP) source detection is provided which includes detecting, via a plurality of sensors, electro-cardiogram (ECG) signals over time, each ECG signal detected via one of the plurality of sensors and indicating electrical activity of a heart. The method also includes determining, for each of the plurality of ECG signals, one or more local activation times (LATs) each indicating a time of activation of a corresponding ECG signal. The method further includes detecting whether one or more RAP source areas of activation in the heart is indicated based on the detected ECG signals and the one or more local LATs. Mapping information of the detected RAP source areas of activation in the heart is also generated for providing one or more maps.

Abstract: A method of analyzing a plethysmograph signal is disclosed. The method comprises: extracting from the signal a plurality of features, thereby constructing a feature space. The method further comprises employing a path selection procedure to the feature space for determining at least one sequence of respiration frequencies and reconstructing a respiratory signal using the sequence.

Abstract: A method of analyzing physiological data indicative of myocardial activity is disclosed. The method comprises: identifying in the data a set of N features, each corresponding to a ventricular depolarization, and calculating M time-intervals for each ventricular depolarization feature, thereby providing a vector of N*M time-intervals. The method further comprises fitting the vector to a power density function of time-intervals, and determining possible cardiac arrhythmia based on statistical parameters characterizing the function.

Abstract: A method of analyzing a plethysmograph signal is disclosed. The method comprises: extracting from the signal a plurality of features, thereby constructing a feature space. The method further comprises employing a path selection procedure to the feature space for determining at least one sequence of respiration frequencies and reconstructing a respiratory signal using the sequence.

Abstract: A method for diagnosis comprises receiving a signal associated with respiration of a patient. The signal is processed so as to identify features that are indicative of beginning and end times of apnea episodes. Time shifts between recurrences of the features are computed and processed so as to generate an output comprising a plurality of bands corresponding to different multiples of a cycle length of the apnea episodes.