A computer implemented method for determining heart arrhythmias based on cardiac activity that includes under control of one or more processors of an implantable medical device (IMD) configured with specific executable instructions to obtain far field cardiac activity (CA) signals at electrodes located remote from the heart, and obtain acceleration signatures, at an accelerometer of the IMD, indicative of heart sounds generated during the cardiac beats. The IMD is also configured with specific executable instructions to declare a candidate arrhythmia based on a characteristic of at least one R-R interval from the cardiac beats, and evaluate the acceleration signatures for ventricular events (VEs) to re-assess a presence or absence of at least one R-wave from the cardiac beats and based thereon confirming or denying the candidate arrhythmia.

In some embodiments, there are provided systems, devices, components, and corresponding methods configured to permit navigation and/or positioning of an intra-cardiac electrophysiological (EP) mapping basket or other EP mapping structure of an EP mapping catheter inside or near an atrium or other heart chamber of a patient's heart using biosignals or intra-cardiac signals. In one embodiment, QRS complexes are extracted or isolated from intra-cardiac signals sensed by electrodes mounted on the EP mapping basket. Using the QRS complexes and a statistical shape or other model of the EP mapping basket or other type of EP mapping structure, one or more computing devices then determine the locations of the electrodes inside or near the patient's atrium that are associated with each isolated or extracted QRS complex, and thereby permit accurate navigation within the heart and/or processing of data acquired using the EP mapping basket or other EP mapping structure. The one or more computing devices can also be used to determine changes in the three-dimensional locations and orientations of the basket and the electrodes thereof as the EP mapping basket is moved around, in, or near the patient's atrium, heart chamber, or other portion of the patient's heart, and to display to a user multiple positions of the basket inside or near the patient's heart.

In some embodiments, there are provided systems, devices, components, and corresponding methods configured to permit navigation and/or positioning of an intra-cardiac electrophysiological (EP) mapping basket or other EP mapping structure of an EP mapping catheter inside or near an atrium or other heart chamber of a patient's heart using biosignals or intra-cardiac signals. In one embodiment, QRS complexes are extracted or isolated from intra-cardiac signals sensed by electrodes mounted on the EP mapping basket. Using the QRS complexes and a statistical shape or other model of the EP mapping basket or other type of EP mapping structure, one or more computing devices then determine the locations of the electrodes inside or near the patient's atrium that are associated with each isolated or extracted QRS complex, and thereby permit accurate navigation within the heart and/or processing of data acquired using the EP mapping basket or other EP mapping structure. The one or more computing devices can also be used to determine changes in the three-dimensional locations and orientations of the basket and the electrodes thereof as the EP mapping basket is moved around, in, or near the patient's atrium, heart chamber, or other portion of the patient's heart, and to display to a user multiple positions of the basket inside or near the patient's heart.

Medical device systems include processing circuitry configured to acquire sensed cardiac signals associated with cardiac activity of a heart of a patient, and to analyze the sensed cardiac signals to determine if a noise signal is present within the cardiac signals.

A process for measuring heart beats fiducial points and classifying heart beats includes sampling a raw ECG signal,—providing a first filtered signal,—providing a second filtered signal, detecting left and right limits data for the beats in said second filtered signal, and receiving the first filtered signal and receiving said left and right limits data, sampling and storing ECG curve data of beats from said first filtered signal synchronized by said left and right limits data and extracting fiducial points of said beats from said ECG curve data, said fiducial points including at least the QRS points values of the beats, and classifying each of said beats in classes based on a correlation of its ECG curve data with respect to average ECG curves data of classes of previously averaged classified beats.

A process for measuring heart beats fiducial points and classifying heart beats includes sampling a raw ECG signal,—providing a first filtered signal,—providing a second filtered signal, detecting left and right limits data for the beats in said second filtered signal, and receiving the first filtered signal and receiving said left and right limits data, sampling and storing ECG curve data of beats from said first filtered signal synchronized by said left and right limits data and extracting fiducial points of said beats from said ECG curve data, said fiducial points including at least the QRS points values of the beats, and classifying each of said beats in classes based on a correlation of its ECG curve data with respect to average ECG curves data of classes of previously averaged classified beats.

A patient monitoring device configured to monitor cardiac activity and sleep stage information of a patient is provided. The device includes a plurality of electrodes to acquire electrocardiogram (ECG) signals from the patient, at least one motion sensor configured to generate a motion signal based upon movement of the patient, and at least one processor. The processor is configured derive motion parameters from the motion signal, derive ECG parameters from the ECG signals, determine whether the patient is in an immobilized sleep stage or a non-immobilized sleep stage based upon the motion parameters and the ECG parameters, adjust one or more cardiac arrhythmia detection parameters such that the device operates in a first monitoring and treatment mode when the patient is in an immobilized sleep stage, and monitor the patient for the cardiac arrhythmia using the first monitoring and treatment mode.

The invention is directed to methods for diagnosing reperfusion/non-reperfusion hemorrhage and predicting cardiac arrhythmias and sudden cardiac death in subjects comprising using imaging techniques to detect regional iron oxide deposition. The invention also provides treatment methods for subject at increased risk of sudden cardiac death.

The invention is directed to methods for diagnosing reperfusion/non-reperfusion hemorrhage and predicting cardiac arrhythmias and sudden cardiac death in subjects comprising using imaging techniques to detect regional iron oxide deposition. The invention also provides treatment methods for subject at increased risk of sudden cardiac death.

A device including an array of electrodes generates one or more electrical signals from a user, extracts one or more noise signals, and generates one or more de-noised electrical signals upon processing the electrical signal(s) with the noise signal(s). The array of electrodes is coupled to a surface of the device, where the device also includes force sensors in mechanical communication with the surface for detecting user weight and other forces. The device can be configured to generate electrical signals from different subportions of the array of electrodes and to extract noise signals from different subportions of the array of electrodes, where the subportion(s) for electrical signal generation may or may not overlap with the subportion(s) of electrodes for noise signal extraction.