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.

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.

In one embodiment of the invention, a portable device with multiple integrated sensors for vital signs scanning and method of using said device is disclosed. The portable personal scanning device includes multiple sensors such as a plurality of ECG, thermometer, PPG, accelerometer, and microphone for determining a user's vital signs. The method includes concurrently scanning with one or more sensors, validating and enhancing the results of each sensor scan with other concurrent sensor scan and patient interaction models, processing the sensor scans separately or in combination to extract user's vital signs, validating the vital signs extracted by comparison to physiological models, and fusing the similar vital signs extracted from more than one process according to a determination of the measure of quality of the process that produced the vital sign.

A defibrillator for guiding a rescuer based on a probability of defibrillation success includes at least one output device and a processor and associated memory, the processor being configured to receive at least two ECG signals over time for a cardiac arrest victim, the at least two ECG signals including at least a first ECG signal at a first point in time and a second ECG signal at a second point in time, process the at least two ECG signals to determine at least two parameters related to the at least two ECG signals, the at least two parameters forming a sequence of parameter sets, analyze a trajectory of the sequence of parameter sets, determine the probability of defibrillation success based on the analysis of the trajectory, and control the at least one output device to provide one or more caregiver prompts based on the probability of defibrillation success.

Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

This disclosure provides a monitoring apparatus and a statistical display method for physiological parameter(s) thereof. The method may include receiving statistical setting information including a time range, a time interval, a classification rule, and a target parameter, and the classification rule may define one or more types of the target parameter; obtaining N group of target parameter result corresponding to N time interval from a result of historical physiological parameter, where the N time interval is included in the time range, and the N group of target parameter result may be a physiological parameter result corresponding to the target parameter in the result of historical physiological parameter; counting the number of each type of the target parameter in the N group of target parameter result according to the classification rule, and obtaining N group of statistical result corresponding to the N time interval for each target parameter.

Methods, systems, and apparatuses are described for automated external defibrillation for determining shock/no-shock decisions based on ECG readings taken when a patient is undergoing cardiopulmonary resuscitation (CPR). A device may filter an ECG signal of a patient to reduce artifacts from the signal caused by CPR being performed on the patient. The device may use the filtered ECG signal to determine whether to deliver a therapeutic shock to a patient even if the patient is undergoing CPR.

In one embodiment, a method to determine reliable electrocardiogram (ECG) signal is described. The method includes receiving at least one ECG signal for a period of time from a patient. The method also includes analyzing the at least one ECG signal to determine a first heart rate using a first method and analyzing the at least one ECG signal to determine a second heart rate using a second method different from the first method. The method includes comparing the first and second heart rates to each other and classifying the at least one ECG signal as reliable when a reliability threshold is satisfied.

In one embodiment, a method to determine reliable electrocardiogram (ECG) signal is described. The method includes receiving at least one ECG signal for a period of time from a patient. The method also includes analyzing the at least one ECG signal to determine a first heart rate using a first method and analyzing the at least one ECG signal to determine a second heart rate using a second method different from the first method. The method includes comparing the first and second heart rates to each other and classifying the at least one ECG signal as reliable when a reliability threshold is satisfied.