An example method includes establishing a communications link between an electrophysiology (EP) monitoring system and an implantable medical device (IMD). IMD electrical data is received at the monitoring system via the communications link. The IMD electrical data may be synchronized with EP measurement data to provide synchronized electrical data based on timing of a synchronization signal sensed by an IMD electrode and/or EP electrodes. The method also includes computing reconstructed electrical signals for locations on a surface of interest within the patient's body based on the synchronized electrical data and geometry data. The geometry data represents locations of the EP electrodes, a location of the IMD electrode within the patient's body and the surface of interest.

Devices and methods provide for the sensing of physiological signals during stimulation therapy by preventing stimulation waveform artifacts from being passed through to the amplification of the sensed physiological signal. Thus, the sensing amplifier is not adversely affected by the stimulation waveform and can provide for successful sensing of physiological signals. A common mode voltage is applied to the stimulation electrodes while sensing during a recharge period where the common mode voltage approximates the stimulation pulse being received at the sensing electrodes. This common mode voltage is determined based on measuring a common mode signal for at least one of the inputs of the amplifier or by deriving the proper common mode from monitoring the output signal of the amplifier to observe the elimination of artifacts during stimulation. Blanking switches may be used to blank the sensing of the peak of the recharge period should that peak be relatively large.

A wearable apparatus and a method for ECG signal collection includes: a main body, including a first ECG sensor electrode provided on a side of the main body away from a wearing position of an individual and a second ECG sensor electrode provided on a side of the main body close to the wearing position, a securing portion, including a third ECG sensor electrode provided on a side of the securing portion away from the wearing position, and an ECG sensor, provided in the main body and configured to: electrically connect to the first ECG sensor electrode and the second ECG sensor electrode, electrically connect to the third ECG sensor electrode through a wire in the securing portion, and collect ECG signals from close circuits formed by the first ECG sensor electrode, the second ECG sensor electrode, and the third ECG sensor electrode.

A method for determining the degree of parallel activation of a heart undergoing pacing includes calculating vectorcardiogram (VCG), or electrocardiogram (ECG), or electrogram (EGM) waveforms from right ventricular pacing (RVp) and left ventricular pacing (LVp). A synthetic biventricular pacing (BIVP) waveform is generated by summing the VCG of the RVp and LVp, or by summing the ECG of the RVp and the LVp, or by summing the EGM of the RVp and the LVp. A corresponding EGM or ECG or VCG waveform from real BIVP is calculated. The method includes comparing the synthetic BIVP waveform and the real BIVP waveform and calculating time to fusion by determining the point in time in which the activation from RVp and LVp meets and the synthetic and the real BIVP curves start to deviate. A delay in time to fusion indicates a higher degree of parallel activation.

A method for determining the degree of parallel activation of a heart undergoing pacing includes calculating vectorcardiogram (VCG), or electrocardiogram (ECG), or electrogram (EGM) waveforms from right ventricular pacing (RVp) and left ventricular pacing (LVp). A synthetic biventricular pacing (BIVP) waveform is generated by summing the VCG of the RVp and LVp, or by summing the ECG of the RVp and the LVp, or by summing the EGM of the RVp and the LVp. A corresponding EGM or ECG or VCG waveform from real BIVP is calculated. The method includes comparing the synthetic BIVP waveform and the real BIVP waveform and calculating time to fusion by determining the point in time in which the activation from RVp and LVp meets and the synthetic and the real BIVP curves start to deviate. A delay in time to fusion indicates a higher degree of parallel activation.

Embodiments of the present disclosure provide a mobile electrocardiogram (ECG) sensor comprising an electrode assembly comprising electrodes, wherein the electrode assembly senses heart-related signals when in contact with a body of a user, and produces electrical signals representing the sensed heart-related signals. The ECG sensor further comprises a processing device, operatively coupled to the electrode assembly, the processing device to provide the sensed heart-related signals to a machine learning module trained to predict a twelve-lead QT interval (QTc) value from the mobile ECG sensor comprising less than twelve leads. The ECG sensor also comprises a housing containing the electrode assembly and the processing device.

A method of estimating fetal electrocardiogram (FECG) signals utilizes a plurality of ECG signals measured along the mother's abdomen. The method includes defining an MECG (ECG) dictionary of symbols and projecting the plurality of abdominal ECG signals onto the MECG dictionary to estimate MECG signals within each of the plurality of abdominal ECG signals. The estimated MECG signals are subtracted from the plurality of measured abdominal ECG signals to estimate FECG signals and the plurality of estimated FECG signals are combined to generate a representation of the FECG source signal.

A method of estimating fetal electrocardiogram (FECG) signals utilizes a plurality of ECG signals measured along the mother's abdomen. The method includes defining an MECG (ECG) dictionary of symbols and projecting the plurality of abdominal ECG signals onto the MECG dictionary to estimate MECG signals within each of the plurality of abdominal ECG signals. The estimated MECG signals are subtracted from the plurality of measured abdominal ECG signals to estimate FECG signals and the plurality of estimated FECG signals are combined to generate a representation of the FECG source signal.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to detect a location of a source of at least one cardiac rhythm disorder in a patient's heart. In some embodiments, electrogram signals am acquired from inside a patient's heart, and subsequently normalized, adjusted and/or filtered, followed by generating a two-dimensional (2D) spatial map, grid or representation of the electrode positions, processing the amplitude-adjusted and filtered electrogram signals to generate a plurality of three-dimensional electrogram surfaces corresponding at least partially to the 2 D grid, one surface being generated for each or selected discrete times, and processing the plurality of three-dimensional electrogram surfaces through time to generate a velocity vector map corresponding at least partially to the 2 D grid. The resulting velocity vector map is configured to reveal the location of the source of the at least one cardiac rhythm disorder, which may be, by way of example, an active rotor in a patient's myocardium and atrium.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to detect a location of a source of at least one cardiac rhythm disorder in a patient's heart. In some embodiments, electrogram signals am acquired from inside a patient's heart, and subsequently normalized, adjusted and/or filtered, followed by generating a two-dimensional (2D) spatial map, grid or representation of the electrode positions, processing the amplitude-adjusted and filtered electrogram signals to generate a plurality of three-dimensional electrogram surfaces corresponding at least partially to the 2 D grid, one surface being generated for each or selected discrete times, and processing the plurality of three-dimensional electrogram surfaces through time to generate a velocity vector map corresponding at least partially to the 2 D grid. The resulting velocity vector map is configured to reveal the location of the source of the at least one cardiac rhythm disorder, which may be, by way of example, an active rotor in a patient's myocardium and atrium.