A system for monitoring the status and/or performance of one or more hearing devices is disclosed. The system comprises a number of access points configured to receive wireless signals transmitted by the hearing devices, wherein the access points are connected to a central unit communicatively connected to the Internet/cloud, wherein the system is configured to automatically monitor the status and/or performance of one or more parameter of the one or more hearing devices received by access points, wherein the monitored parameters are accessible from the central unit and/or from a cloud service.

A method for adjusting parameters of a medical device includes collecting patient data by using the medical device, in which the medical device includes programmable parameters for affecting a function carried out by the medical device, transmitting the patient data to an external device, conducting an analysis of the transmitted patient data by using the external device, and providing an automatically computed proposal for adjusting at least one parameter, several parameters or all of the parameters based on the analysis. A corresponding system is also provided.

Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. Several examples emphasize the use of morphology analysis using correlation to static templates and/or inter-event correlation analysis.

Systems, methods, and computer program product embodiments are disclosed for performing electrophysiology (EP) signal processing. An embodiment includes an electrocardiogram (ECG) circuit board configured to process an ECG signal. The embodiment further includes a plurality of intracardiac (IC) circuit boards, each configured to process a corresponding IC signal. The embodiment further includes a communications interface communicatively coupled to a remote device, and a processor, coupled to the ECG circuit board, the plurality of IC circuit boards, and the communications interface. The processor is configured to receive, via the communications interface, feedback from the remote device. The processor is further configured to control, via the communication interface, the remote device based on the ECG signal, the IC signals, or the feedback from the remote device.

A medical device is configured to detect an atrial tachyarrhythmia episode. The device senses a cardiac signal, identifies R-waves in the cardiac signal attendant ventricular depolarizations and determines classification factors from the R-waves identified over a predetermined time period. The device classifies the predetermined time period as one of unclassified, atrial tachyarrhythmia and non-atrial tachyarrhythmia by comparing the determined classification factors to classification criteria. A classification criterion is adjusted from a first classification criterion to a second classification criterion after at least one time period being classified as atrial tachyarrhythmia. An atrial tachyarrhythmia episode is detected by the device in response to at least one subsequent time period being classified as atrial tachyarrhythmia based on the adjusted classification criterion.

Cardiac activity of the heart can be sensed using, for example, one or more leadless cardiac pacemakers (LCPs) that are implanted in a close proximity to the heart. Sensing cardiac activity by the one or more leadless cardiac pacemakers (LCPs) can help the system in determining an occurrence of cardiac arrhythmia. For treatment purposes, electrical stimulation therapy, for example anti-tachyarrhythmia pacing (ATP) therapy, can be delivered by at least one of the devices of the system. Such therapy can help treat the detected cardiac arrhythmia. In some instances, one of the leadless cardiac pacemakers can instruct one or more of the other devices to assist in providing pacing therapy. In some instances, one of the leadless cardiac pacemakers can instruct one or more of the other devices to temporarily stop providing therapy or to simply shut down while another device provides therapy.

System and method for providing patient-specific models to distinguish between epochs of electrocardiograms (ECGs) located far away from atrial fibrillation rhythms and those located just prior to the onset of those episodes, to provide for the prediction of the onset of an occurrence of atrial fibrillation (AF) in the patient.

A method for identifying cardiac bradycardia behavior may include acquiring pulse volume wave data from a sensor associated with a patient, and calculating metrics associated with peaks detected therein. The metrics may include changes in peak amplitudes of pulse volume peaks and in the times of occurrence of pulse volume peaks. Alternative metrics may include changes in frequency domain parameters derived from the time domain pulse volume wave data. Peak amplitude values may be compared to an amplitude baseline, and differences in successive peak occurrence times may be compared to a time baseline. Cardiac bradycardia behavior may be identified by a combination of a decrease in the pulse volume peak amplitude and an increase in successive peak occurrence times. A system to implement the method may include a computing device in data communication with a photo-plethysmograph. Alternative sensors may include a blood pressure cuff and an ECG device.

The invention discloses a method, a system, a computer program and a device for determining the surface charge and/or dipole densities on heart walls. Using the foregoing, a table of dipole densities (P, t) and/or a table of surface charge densities (P, t) of a given heart chamber can be generated.

A computer implemented method for detecting pocket stability for an implantable cardiac monitor, including under control of one or more processors in the ICM, collecting impedance data over at least one cardiac cycle. The impedance data is processed to separate an impedance waveform that varies over the at least one cardiac cycle in a manner representative of cardiac functionality over the at least one cardiac cycle. A characteristic of interest is analyzed from the impedance waveform over the at least one cardiac cycle. A pocket stability state of the ICM is identified and recorded based on the analyzing operation.