Abstract: Computer implemented methods and systems for detecting noise in cardiac activity are provided. The method and system obtain a far field cardiac activity (CA) data set that includes far field CA signals for a series of beats, overlay a segment of the CA signals with a noise search window, and identify turns in the segment of the CA signals. The method and system determine whether the turns exhibit a turn characteristic that exceed a turn characteristic threshold, declare the segment of the CA signals as a noise segment based on the determining operation, shift the noise search window to a next segment of the CA signal and repeat the identifying, determining and declaring operations; and modify the CA signals based on the declaring the noise segments.

Abstract: A computer implemented method and system for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains far field cardiac activity (CA) signals and applies a direction related responsiveness (DRR) filter to the CA signals to produce DRR filtered signals. The method compares a current sample from the CA signals to a prior sample from the DRR filtered signals to identify a direction characteristic of the CA signals and defines the DRR filter based on a timing constant that is set based on the direction characteristic identified. The method analyzes the CA signals in connection with the DRR filtered signals to identify a peak characteristic of the CA signals and determines peak to peak intervals between successive peak characteristic. The method detects at least one of noise or an arrhythmia based on the peak to peak intervals and records results of the detecting.

Abstract: 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.

Abstract: Embodiments describe herein generally pertain to implantable medical device (IMDs), and methods for use therewith, that can be used to automatically switch an IMD from its normal operational mode to magnetic resonance imaging (MRI) safe mode, and vice versa, within increased specificity. A controller of an IMD is configured to use an accelerometer to determine whether a positional condition associated with a patient is detected, and control sampling of a magnetic field sensor or at least one signal output therefrom, such that a first sampling rate is used when the positional condition is detected, and a second sampling rate, that is slower than the first sampling rate, is used when the positional condition is not detected, to thereby conserve power. Based on results of the sampling, the controller determines whether a magnetic field condition is detected, and in response thereto performs a mode switch to an MRI safe mode.

Abstract: An apparatus and method for characterizing a region of interest (ROI) including measuring position and orientation data within the ROI; and generating a geometric data set to include one or more of: length, bifurcation location, angle and curvature characteristics of the ROI. Also, sequentially taking an image of a tool within the ROI; comparing tool dimensions with ROI dimensions; and estimating diameter, length, take-off angle, and/or tortuosity characteristics based on the comparisons.

Abstract: A computer implemented method and system for confirming a device documented arrhythmia in cardiac activity are provided. The method is under control of one or more processors configured with executable instructions. The method obtains a cardiac activity (CA) data set that includes CA signals for a series of cardiac events and includes device documented (DD) markers within the series of cardiac events. The device documented markers are indicative of atrial fibrillation (AF) detected by the ICM utilizing an on-board R-R interval irregularity (ORI) process to analyze the CA signals. The method applies a feature enhancement function to the CA signals to form modified CA signals with enhanced sinus features and analyzes the enhanced sinus features in the modified CA signals. The method utilized a confirmatory feature detection process to identify false AF detection by the ORI process. The method records a result of the analysis identifying false AF detection by the ORI process.

Abstract: A subcutaneous implantable medical device and method (SIMD) provided. A pulse generator (PG) is configured to be positioned subcutaneously within a lateral region of a chest of a patient. The PG has a housing that includes a PG electrode. The PG has an electronics module. An elongated lead is electrically coupled to the pulse generator. The elongated lead includes a first electrode that is configured to be positioned along a first parasternal region proximate a sternum of the patient and a second electrode that is configured to be positioned at an anterior region of the patient. The first and second electrodes are coupled to be electrically common with one another. The electronics module is configured to provide electrical shocks for antiarrhythmic therapy along at least one shocking vector between the PG electrode and the first and second electrodes.

Abstract: Embodiments describe herein generally pertain to implantable medical device (IMDs), and methods for use therewith, that can be used to automatically switch an IMD from its normal operational mode to an MRI safe mode, and vice versa, within increased specificity. In certain embodiments, a controller of the IMD uses a magnetic field sensor to determine whether a first magnetic field condition is detected, and uses an accelerometer to determine whether a positional condition is detected. In response to the first magnetic field condition being detected, and the positional condition being detected, the controller can use the magnetic field sensor to determine whether a second magnetic field condition is detected, which differs from the first magnetic field condition. The controller can then cause the IMD to enter the MRI safe mode based at least in part on the first and second magnetic field conditions and the positional condition being detected.

Abstract: A subcutaneous implantable medical device and method (SIMD) provided. A pulse generator (PG) is configured to be positioned subcutaneously within a lateral region of a chest of a patient. The PG has a housing that includes a PG electrode. The PG has an electronics module. An elongated lead is electrically coupled to the pulse generator. The elongated lead includes a first electrode that is configured to be positioned along a first parasternal region proximate a sternum of the patient and a second electrode that is configured to be positioned at an anterior region of the patient. The first and second electrodes are coupled to be electrically common with one another. The electronics module is configured to provide electrical shocks for antiarrhythmic therapy along at least one shocking vector between the PG electrode and the first and second electrodes.

Abstract: 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.

Abstract: 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.

Abstract: System and methods are provided for determining a stimulation threshold for closed loop spinal cord stimulation (SCS). The system and methods provide a lead coupled to an implantable pulse generator (IPG). The system and methods deliver SCS pulses from the IPG to the lead electrodes in accordance with an SCS therapy and determine an evoked compound action potential (ECAP) amplitude based on an ECAP waveform resulting from the SCS therapy. The system and methods increase the SCS therapy by increasing at least one of an amplitude, a duration, and number of the SCS pulses associated with the SCS therapy. The system and methods also include iteratively repeat the delivering, determining and increasing operations until the ECAP amplitude exhibits a downward trend divergence. The system and methods define a stimulation threshold based on the ECAP amplitude at the trend divergence.

Abstract: A computer implemented method and system for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains cardiac activity (CA) signals at the electrodes of an implantable medical device (IMD) in connection multiple cardiac beats and with different IMD orientations relative to gravitational force. The method obtains acceleration signatures at a sensor of the IMD that are indicative of heart sounds generated during the cardiac beats. The method obtains device location information at the IMD, with respect to the gravitational force during the cardiac beats. The method groups the acceleration signatures associated with the first and second set of cardiac beats into the corresponding one of first and second posture bins based on the device location information.

Abstract: Computer implemented methods and systems for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains a far field cardiac activity (CA) data set that includes far field CA signals for beats. The method applies a feature enhancement function to the CA signals to form an enhanced feature in the CA data set. The method calculates an adaptive sensitivity level and sensitivity limit based on the enhanced feature from one or more beats within the CA data set and automatically iteratively analyzes a beat segment of interest by comparing the beat segment of interest to the current sensitivity level to determine whether one or more R-waves are present within the beat segment of interest.

Abstract: Computer implemented methods, systems and devices are provided to monitor for potential heart failure (HF). Cardiac activity (CA) data is obtained and filtered to obtain respiration data indicative of a respiration pattern. The respiration data is analyzed to determine one or more respiration characteristics of interest (COI) that are recorded along with collection time information to form an HF monitoring log. Additionally or alternatively, the CA data is analyzed to detect an event of interest. The cardiac activity data is filtered to obtain respiration data indicative of a respiration pattern, and the respiration data is analyzed for respiration induced under detection of the event of interest from the CA data.

Abstract: A method of pacing a His bundle of a patient heart using a stimulation system including a memory, a pulse generator, a stimulating electrode and at least one sensing electrode includes applying a plurality of impulses through the stimulating electrode to induce a plurality of responses from the patient heart. Each impulse of the plurality of impulses is delivered at a different impulse energy corresponding to a respective output setting of the stimulation system. The response characteristics for each of the plurality of responses are measured and each impulse is assigned a classification based on whether the respective response characteristics indicate capture of one or both of the His bundle and a ventricle of the patient heart. The output setting and classification for each impulse is then stored in the memory.

Abstract: Methods and devices include making an incision at a single site of a patient. The single site located at an anterior of a chest or abdomen. The method also includes inserting a tunneling tool through the incision at the single site and preparing a first tunnel to a subcutaneous posterior location. A path of the first tunnel at least one of i) extends over a plurality of Intercostal gaps of the chest or ii) extends along and within one of the intercostal gaps. The method also includes positioning a first lead having an electrode within the first tunnel and preparing a second tunnel to a subcutaneous parasternal location along the chest. The method also includes positioning a second lead having an electrode within the second tunnel and positioning a pulse generator within a subcutaneous pocket and operatively coupling the first and second leads to the pulse generator.

Abstract: Computer implemented methods and systems for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains a far field cardiac activity (CA) data set that includes far field CA signals for beats. The method applies a feature enhancement function to the CA signals to form an enhanced feature in the CA data set. The method calculates an adaptive sensitivity level and sensitivity limit based on the enhanced feature from one or more beats within the CA data set and automatically iteratively analyzes a beat segment of interest by comparing the beat segment of interest to the current sensitivity level to determine whether one or more R-waves are present within the beat segment of interest.

Abstract: Computer implemented methods, systems and devices are provided to monitor for potential heart failure (HF). Cardiac activity (CA) data is obtained and filtered to obtain respiration data indicative of a respiration pattern. The respiration data is analyzed to determine one or more respiration characteristics of interest (COI) that are recorded along with collection time information to form an HF monitoring log. Additionally or alternatively, the CA data is analyzed to detect an event of interest. The cardiac activity data is filtered to obtain respiration data indicative of a respiration pattern, and the respiration data is analyzed for respiration induced under detection of the event of interest from the CA data.

Abstract: A method of pacing a His bundle of a patient heart using a stimulation system including a memory, a pulse generator, a stimulating electrode and at least one sensing electrode includes applying a plurality of impulses through the stimulating electrode to induce a plurality of responses from the patient heart. Each impulse of the plurality of impulses is delivered at a different impulse energy corresponding to a respective output setting of the stimulation system. The response characteristics for each of the plurality of responses are measured and each impulse is assigned a classification based on whether the respective response characteristics indicate capture of one or both of the His bundle and a ventricle of the patient heart. The output setting and classification for each impulse is then stored in the memory.