Systems and techniques for managing biological signals. In one implementation, a method includes receiving a cardiac biological signal that includes information describing events, determining a merit of each event based on one or more of a severity of a cardiac condition associated with the event and a quality of the event, and handling a subset of the events that meet a merit criterion. The subset can be handled for medical purposes.

A system and method for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer is provided. Cutaneous action potentials of a patient are recorded over a set period of time as ECG data and a difference between recording times of successive pairs of R-wave peaks are recorded as R-R intervals. A heart rate is associated with each time difference. An R-R interval plot of the ECG data is generated. A presence of a cardiac event is displayed by presenting a presence of sinus tachycardia or a presence of bradycardia via the R-R interval plot.

A computer implemented method and system for labeling types of heart arrhythmias based on cardiac activity are provided. The method is under control of one or more processors of an implantable medical device (IMD) configured with specific executable instruction. The method obtains cardiac activity (CA) signals at electrodes of the IMD during cardiac beats, declares a ventricular tachycardia (VT) episode based on the CA signals and obtains acceleration signatures, at an accelerometer of the IMD, indicative of heart sounds generated during the cardiac beats. The method analyzes an S1 characteristic of interest (COI) from the acceleration signature to identify the VT episode as a stable or non-stable VT episode and labels the VT episode as stable or non-stable based on the analyzing operation.

A computer-implemented method for contact photoplethysmography, abbreviated contact PPG, comprises obtaining during a time interval plural PPG signals for sub-regions of a lens or video frame; and combining the plural PPG signals to thereby obtain a multi-region PPG signal.

Apparatus and methods remove a voltage offset from an electrical signal, specifically a biomedical signal. A signal is received at a first operational amplifier and is amplified by a gain. An amplitude of the signal is monitored, by a first pair of diode stages coupled to an output of the first operational amplifier, for the voltage offset. The amplitude of the signal is then attenuated by the first pair of diode stages and a plurality of timing banks. The attenuating includes limiting charging, by the first pair of diode stages, of the plurality of timing banks and setting a time constant based on the charging. The attenuating removes the voltage offset persisting at a threshold for a duration of at least the time constant. Saturation of the signal is limited to a saturation recovery time while the saturated signal is gradually pulled into monitoring range over the saturation recovery time.

Techniques are disclosed for using a computing system to selectively implement different review workflows for different categories of episodes, e.g., arrhythmia episodes, stored by medical devices. The different workflows may include different combinations of one or more human and/or machine reviewers, and different decision logic for determining whether and when to present an episode to the reviewers. Machine reviewers may utilize one or more machine learning models to annotate, e.g., classify, episodes.

Techniques are disclosed for explaining and visualizing an output of a machine learning system that detects cardiac arrhythmia in a patient. In one example, a computing device receives cardiac electrogram data sensed by a medical device. The computing device applies a machine learning model, trained using cardiac electrogram data for a plurality of patients, to the received cardiac electrogram data to determine, based on the machine learning model, that an episode of arrhythmia has occurred in the patient and a level of confidence in the determination that the episode of arrhythmia has occurred in the patient. In response to determining that the level of confidence is greater than a predetermined threshold, the computing device displays, to a user, a portion of the cardiac electrogram data, an indication that the episode of arrhythmia has occurred, and an indication of the level of confidence that the episode of arrhythmia has occurred.

A method of monitoring cardiac activity of a user is provided. Heart beat time data is detected by a PPG sensor (110) in a health sensor (100) worn by the user (1). Motion data is detected by a motion sensor (120) in the health sensor (100). The output data of the PPG sensor (110), which comprises heart beat time data, is analyzed to detect arrhythmia periods. The detected heart beat time data, the detected motion data and the detected arrhythmia are forwarded to an external device, where the data can be stored. The output data of the PPG sensor (110) comprising the heart beat time data, the detected motion data and the detected arrhythmia periods are displayed such that a medical professional (2) can analyze this data to determine whether a suspected arrhythmia period is valid.

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.

This disclosure relates to active implantable medical devices. Some such devices include a pulse generator and at least one detection electrode. A processor of the pulse generator is configured to collect via the detection electrode at least two EGM signals, combine the EGM signals into two time components, and combine the components into a single 2D parametric characteristic representing the cardiac cycle. During a tachyarrhythmia episode, the device stores the consecutive values of the cycle-to-cycle variation in the amplitude of one EGM signal, distributes same into a plurality of classes each corresponding to an amplitude interval, and performs a statistical analysis of the totals for each class so as to output, selectively, on the basis of at least one predetermined criterion applied to the distribution of the amplitude variations into the various classes, an indicator of a suspected extracardiac artifact or an indicator of tachyarrhythmia.