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.

A system including a sensor interface coupled to a processor. The sensor interface is configured to receive and process an analog electrocardiogram signal of a subject and provide a digitized electrocardiogram signal sampled over a first time period and a second time period that is subsequent to the first time period. The processor is configured to receive the digitized electrocardiogram signal, to analyze a frequency domain transform of the digitized electrocardiogram signal sampled over the first and second time periods and determine first and second metrics indicative of metabolic state of a myocardium of the subject during the first and second time periods, respectively, to compare the first and second metrics to determine whether the metabolic state of the myocardium of the subject is improving, and to indicate administration of an intervention to the subject in response to a determination that the metabolic state is not improving.

The invention relates to the system and method of remote ECG monitoring, remote disease screening, and early-warning system based on wavelet analysis. The system includes a wireless ECG signal acquisition device, a mobile terminal, and a cloud storage platform. The wireless ECG signal acquisition device worn on the user's chest is used to collect ECG signals anywhere and anytime. The method includes transmitting the ECG signals to the mobile terminal using the wavelet analysis algorithm, analyzing and processing the received ECG signal, and uploading the processed ECG signals to the cloud storage platform. The cloud storage platform stores users' personal information and ECG signals. According to the ECG features detection with support vector machine learning algorithm for heart diseases diagnosis and features classification, the system gives feedback report and proposal, and transmits them to the mobile terminal.

A method for processing electrocardiograph (ECG) data using a garment includes determining, by a processor, a current working lead from ECG leads formed in advance using flexible electrodes in the garment based on a current ECG monitor type, and receiving, by the processor through lead wires corresponding to the current working lead, ECG data collected by flexible electrodes corresponding to the current working lead. A wearable apparatus for processing ECG data includes at least two flexible electrodes, in which the at least two flexible electrodes are capable of forming different leads based on predetermined configurations, at least two lead wires, and an ECG data collector configured to receive ECG data collected by the at least two flexible electrodes, in which each of the at least two flexible electrodes connects to the ECG data collector via at least one of the at least two lead wires.

The present invention concerns a method for identifying areas of the heart of a patient able to be involved in the perpetuation of atrial fibrillation. This method takes into account the reference cycle of the arrhythmia and has two variants: a local variant in which the areas of the heart are each analysed separately and a regional variant in which several areas of the heart are analysed together. The invention also concerns device for implementing said method a program and the medium thereof.

A wearable cardioverter defibrillator (WCD) (10) and method (60) comprise a set of electrodes (12) for placement on a subject (14), a mechanism for electrically engaging (16) the set of electrodes to the subject's skin, and at least one non-invasive physiologic sensor (18, 20) configured for placement on the subject. A controller (24) monitors an output of the non-invasive physiologic sensor (18, 20) for detecting a change in a health parameter of the subject being indicative of one or more of a change in subject condition that may be a precursor to potential cardiac arrhythmia or a simultaneously occurring cardiac arrhythmia. Responsive to detecting the change, the controller (24) activates an alarm (26) for requesting a response from the subject (14) within a predetermined time. Responsive to receiving the subject's response within the predetermined time, the controller (24) inhibits the mechanism (16) from electrically engaging the set of electrodes (12) to the subject's skin. Responsive to not receiving the subject's response, the controller (24) initiates the mechanism (16) for electrically engaging the set of electrodes (12) to the subject's skin.

A defibrillator and method for using a defibrillator which adopts an ECG analysis algorithm that can detect a cardiac arrhythmia in the presence of noise artifact induced by cardio pulmonary resuscitation (CPR) compressions. The apparatus and method provides both of a continuous and scheduled mode of operation for interleaving periods of CPR with electrotherapy, in a manner that improves the effectiveness of the rescue, resulting in more CPR “hands-on” time, better treatment of refibrillation, and reduced transition times between CPR and electrotherapy.

A defibrillator and method for using a defibrillator which adopts an ECG analysis algorithm that can detect a cardiac arrhythmia in the presence of noise artifact induced by cardio pulmonary resuscitation (CPR) compressions. The apparatus and method includes a confidence analyzer circuit which determines the confidence level of an electrotherapy shock decision based on the detection. If the confidence level is low, the apparatus adjusts its shock decision criteria.

A defibrillator (AED) using two different ECG analysis algorithms which work sequentially to improve the accuracy of AED shock decisions. A first algorithm, such as (ART), is particularly suited for analysis in the presence of CPR periods. A second algorithm, such as (PAS), is particularly suited for analysis during hands-off periods. The AED switches algorithms depending on the period and on the current analysis of the cardiac rhythm. The inventions thus provide an optimized ECG analysis scheme in a manner that improves the effectiveness of the rescue, resulting in more CPR “hands-on” time, better treatment of refibrillation, and reduced transition times between CPR and electrotherapy.

Intracardiac electrograms are recorded using a multi-electrode catheter and respective annotations established. Within a time window a pattern comprising a monotonically increasing local activation time sequence from a set of electrograms from neighboring electrodes is detected. The set is reordered and displayed for the operator.