Cardiac activity (e.g., a cardiac electrogram) is analyzed for local abnormal ventricular activity (LAVA), such as by using a LAVA detection and analysis module incorporated into an electroanatomical mapping system. The module transforms the electrogram signal into the wavelet domain to compute as scalogram; computes a one-dimensional LAVA function of the scalogram; detects one or more peaks in the LAVA function; and computes a peak-to-peak amplitude of the electrogram signal. If the peak-to-peak amplitude does not exceed a preset amplitude threshold, then the module can compute one or more of a LAVA lateness parameter for the electrogram signal using one of the one or more peaks detected in the LAVA function and a LAVA probability parameter for the electrogram signal.

A method and system are provided for detecting arrhythmias in cardiac activity. The method the method and system, under control of one or more processors configured with specific executable instructions, obtain cardiac activity (CA) signals for a series of beats, build a QRS-T template based on an ensemble of QRS complexes within the CA signals, and subtract the QRS-T template from the CA signals to obtain QRS-T scrubbed CA signals. The method and system determine an atrial flutter (AFL) timing feature within the QRS scrubbed CA signals, and declare an AFL episode based on a relation between the AFL timing feature and an AFL cluster criteria.

A medical device and method for detecting a ventricular arrhythmia event is disclosed. The medical device includes input circuitry configured to receive an electrocardiogram (ECG) signal and processing circuitry coupled to the input circuitry that is configured to identify fiducial points within the ECG signal. Feature extraction circuitry coupled to the processing circuitry is configured to determine interval variability between the fiducial points. Machine learning circuitry is coupled to the feature extraction circuitry and is configured to detect ventricular arrhythmia based on the interval variability between the fiducial points.

Device and methods for a wearable medical device are disclosed. The device and methods use an on-board mobile system to alert emergency services when the user is in cardiovascular distress. The device takes advantage of newly miniaturized electrocardiograph, pulse oximetry sensors, mutual reinforcement and anomaly detection algorithms. Electrocardiograph waveforms are recorded digitally for physician review with emphasis on critical events. In the occurrence of a immediate critical-need cardiac event, the system will contact emergency services (EMS) for assistance. The system is a biometric monitoring system that implements key concepts of cardiovascular monitoring through pulse oximetry and electrocardiography (ECG). The system implements key concepts of ECGs and active/capacitive electrodes to produce a wireless network of (individually isolated) ECG nodes that can produce a system ranging from 3 to 16 leads.

The present application discloses a method for identifying arrhythmia, a device for identifying arrhythmia, and a computer readable medium. The method includes: acquiring a type of arrhythmia to be identified; acquiring an ECG signal collected by an ECG acquisition device; detecting feature wave information in the ECG signal according to the type of arrhythmia to be identified; extracting a feature parameter from the denoised ECG signal and the feature wave information according to the type of arrhythmia to be identified; and identifying, by a classifier, an occurrence of the type of arrhythmia to be identified according to the feature parameter.

Disclosed are a method and a system for comprehensive evaluation of organic compound and heavy metal pollution in water based on fish electro-cardio, and fish electro-cardio signals are acquired by a real-time and miniaturized fish electro-cardio acquisition system which includes a real-time and miniaturized fish electro-cardio acquisition device, then a change of the electro-cardio index in a QT interval is obtained for assessing the corresponding organic compound in water to be tested, and a change of the electro-cardio index in a QRS interval is obtained for assessing the corresponding heavy metal in water to be tested. Based on fish electro-cardio acquired continuously on-line in real-time while keeping fish swims in a normal state and the water quality parameters acquired by various water quality sensors, water quality is online analyzed and water sudden pollution is online monitored and assessed.

A system for marking cardiac time intervals from heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory. The one or more processors causes the one or more processors to perform operations including separating a plurality of individual heart vibration events into heart valve signals from the composite vibration objects, and marking cardiac time interval from the heart valve signals by detecting individual heartbeats and processing cumulative energy within the individual heartbeat to set a threshold to set a marking point.

Systems and methods for pacing cardiac conductive tissue are described. An embodiment of a medical system includes an electrostimulation circuit to generate His-bundle pacing (HBP) pulses to stimulate a His bundle, and a cardiac event detector to detect a His-bundle activity within a time window following an atrial activity. The cardiac event detector may use a cross-chamber blanking, or an adjustable His-bundle sensing threshold, to avoid or reduce over-sensing of far-field atrial activity and inappropriate inhibition of HBP therapy. The electrostimulation circuit may deliver HBP in the presence of the His-bundle activity. The system may further recognize the detected His-bundle activity as either a FFPW or a valid inhibitory event, and deliver or withhold HBP therapy based on the recognition of the His-bundle activity.

When a user uses a finger to press and hold a first candidate display area, the first candidate display area is enclosed in a selection frame (W1), a simple window (W10) is displayed, and analysis results relating to a first candidate segment waveform are displayed in this simple window (W10). Analysis results can therefore be confirmed without switching screens and, as a result, inspection results can be confirmed with fewer steps and an electrocardiographic waveform and analysis results therefor can be compared on the same screen.

Individuals who suffer from certain kinds of medical conditions, particularly conditions that only sporadically exhibit measurable symptoms, can feel helpless in their attempts to secure access to medical care because, at least in part, they are left to the mercy of their condition to present symptoms at the right time to allow diagnosis and treatment. Providing these individuals with ambulatory extended-wear health monitors that record ECG and physiology, preferably available over-the-counter and without health insurance preauthorization, is a first step towards addressing their needs. In addition, these individuals need a way to gain entry into the health care system once a medically-actionable medical condition has been identified. Here, the ECG and physiology is downloaded and evaluated post-monitoring against medical diagnostic criteria. Medical specialists are pre-identified and paired up with key diagnostic findings, such that an individual whose monitoring data indicates a medical concern will be automatically referred and treated.