A method and medical device for detecting a cardiac event that includes sensing cardiac signals from a plurality of electrodes forming a first sensing vector sensing a first interval of the cardiac signal during a predetermined time period and a second sensing vector simultaneously sensing a second interval of the cardiac signal during the predetermined time period, identifying each of the first interval and the second interval as being one of shockable and not shockable in response to first processing of the first interval and the second interval and in response to second processing of one or both of the first interval and the second interval, the second processing being different from the first processing, and determining whether to deliver therapy for the cardiac event in response to identifying each of the first interval and the second interval as being one of shockable and not shockable in response to both the first processing and the second processing of the first interval and the second interval.

A method and medical device for detecting a cardiac event that includes sensing cardiac signals from a plurality of electrodes forming a first sensing vector sensing a first interval of the cardiac signal during a predetermined time period and a second sensing vector simultaneously sensing a second interval of the cardiac signal during the predetermined time period, identifying each of the first interval and the second interval as being one of shockable and not shockable in response to first processing of the first interval and the second interval and in response to second processing of one or both of the first interval and the second interval, the second processing being different from the first processing, and determining whether to deliver therapy for the cardiac event in response to identifying each of the first interval and the second interval as being one of shockable and not shockable in response to both the first processing and the second processing of the first interval and the second interval.

A computer implemented method and system are provided for detecting premature ventricular contractions (PVCs) in cardiac activity. The method and system obtain cardiac activity (CA) signals for a series of beats, and, for at least a portion of the series of beats, calculate QRS scores for corresponding QRS complex segments from the CA signals. The method and system calculate a variability metric for QRS scores across the series of beats, calculate a QRS complex template using QRS segments from the series of beats, calculate correlation coefficients between the QRS complex template and the QRS complex segments, compare the variability metric to a variability threshold and the correlation coefficients to a correlation threshold, and designate the CA signals to include a predetermined level of PVC burden based on the determining.

A computer implemented method and system are provided for detecting premature ventricular contractions (PVCs) in cardiac activity. The method and system obtain cardiac activity (CA) signals for a series of beats, and, for at least a portion of the series of beats, calculate QRS scores for corresponding QRS complex segments from the CA signals. The method and system calculate a variability metric for QRS scores across the series of beats, calculate a QRS complex template using QRS segments from the series of beats, calculate correlation coefficients between the QRS complex template and the QRS complex segments, compare the variability metric to a variability threshold and the correlation coefficients to a correlation threshold, and designate the CA signals to include a predetermined level of PVC burden based on the determining.

A medical device includes at least one electrode to sense an electrocardiogram (ECG) signal of a patient, and a controller coupled to the at least one electrode. The controller is configured to generate a first ECG template based on a first ECG signal of the patient received during a first baselining operation. The controller is configured to determine that the patient has been administered a therapeutic shock, and responsive to the determination that the patient has been administered the therapeutic shock, the controller is configured to initiate a second baselining operation and generate a second ECG template based on a second ECG signal of the patient received during the second baselining operation. The controller is configured to determine whether the patient is experiencing a cardiac event based on a comparison of the second ECG template to a real time ECG signal received during real time monitoring of the patient.

A medical device includes at least one electrode to sense an electrocardiogram (ECG) signal of a patient, and a controller coupled to the at least one electrode. The controller is configured to generate a first ECG template based on a first ECG signal of the patient received during a first baselining operation. The controller is configured to determine that the patient has been administered a therapeutic shock, and responsive to the determination that the patient has been administered the therapeutic shock, the controller is configured to initiate a second baselining operation and generate a second ECG template based on a second ECG signal of the patient received during the second baselining operation. The controller is configured to determine whether the patient is experiencing a cardiac event based on a comparison of the second ECG template to a real time ECG signal received during real time monitoring of the patient.

When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as “clean.” If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more pre-determined criteria, the heartbeat is classified as “noisy.”

When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as “clean.” If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more pre-determined criteria, the heartbeat is classified as “noisy.”

The invention provides systems and methods for monitoring the wellbeing of a fetus by the non-invasive detection and analysis of fetal cardiac electrical activity data.

An electrocardiogram information dynamic monitoring method and dynamic monitoring system. The method includes a dynamic monitoring device receiving monitoring reference data input by a user or issued by a server; the data collection on a tested object so as to obtain electrocardiogram data of the tested object; the characteristic identification on the electrocardiogram data so as to obtain characteristic signals of the electrocardiogram data, implementing cardiac activity classification on the electrocardiogram data according to the characteristic signals, obtaining cardiac activity classification information according to electrocardiogram basic rule reference data, and generating electrocardiogram event data, wherein the electrocardiogram event data comprises device ID information of the dynamic monitoring device; the dynamic monitoring device determining corresponding electrocardiogram event information according to the electrocardiogram event data, and determining whether the electrocardiogram event information is electrocardiogram abnormality event information; and outputting alarm information when the electrocardiogram event information is electrocardiogram abnormality event information.