Methods and systems for use of the Q-wave to R-wave interval to guide placement of a leadless cardiac pacemaker are disclosed. An implant delivery device is equipped with sensing electrodes to sense R-wave onset in a ventricle of a patient's heart to allow placement at a location of last or latest onset of the R-wave. Guidance tools are provided to assist in determination of the Q-wave to R-wave interval during implantation. For a chronic system, a cooperative approach is disclosed in which an implantable medical device and a leadless cardiac pacemaker exchange data to determine Q-wave to R-wave intervals and enhance cardiac resynchronization therapy delivery by the leadless cardiac pacemaker.

Methods and systems for use of the Q-wave to R-wave interval to guide placement of a leadless cardiac pacemaker are disclosed. An implant delivery device is equipped with sensing electrodes to sense R-wave onset in a ventricle of a patient's heart to allow placement at a location of last or latest onset of the R-wave. Guidance tools are provided to assist in determination of the Q-wave to R-wave interval during implantation. For a chronic system, a cooperative approach is disclosed in which an implantable medical device and a leadless cardiac pacemaker exchange data to determine Q-wave to R-wave intervals and enhance cardiac resynchronization therapy delivery by the leadless cardiac pacemaker.

A biosensor assembly that measures multiple physical parameters is disclosed. The biosensor assembly includes a first implantable probe and a first skin contacting electrode. Wherein a first physiological parameter is measured between the first implantable probe and the first skin contactable electrode.

A leadless pacemaker device configured to provide for an intra-cardiac pacing, including: processing circuitry configured to generate ventricular pacing signals for stimulating ventricular activity, and a reception device for receiving a sensing signal indicative of an atrial activity, wherein the processing circuitry is configured to detect an atrial event derived from said sensing signal, wherein the atrial event is a valid atrial sense event, where a series of atrial events lie within a range for a normal atrial rate, and/or when the atrial rate variability is within a certain range indicating a regular atrial rhythm, wherein in case a valid atrial sense event is detected, the processing circuitry is further configured to: determine ventricular pacing events according to atrial events, calculate ventricular-atrial time delays, determine a correction value based a measured time delay and the calculated time delay, and adjust the ventricular pacing timing based on the correction value.

A subject's Default Mode Network is accessed through corresponding measurements of the Micro-Coherence Oximetry Network Strength (MCO-S). An associated MCO-S system (100) includes a wearable (102), a user device (112) and a processing platform (123). The wearable (102) collects subject information sufficient to enable monitoring and optimization of the subject's Default Mode Network include sensors such as pulse oximetry instrumentation and EEG electrodes to obtain brainwave data, oxygen saturation data, heart rate variability data, and galvanic skin conductance data. Information from the sensors may be communicated to a user device (112), such as a cell phone or VR headset. The user device (112) communicates with a remote processing platform (123) that may execute artificial intelligence functionality and other logic in connection with assessing the patient's micro-coherence network strength and optimizing behavior modification protocols in relation to attributes and objectives of the subject.

There is disclosed herein examples of systems and methods of processing captured heart sounds with frequency-dependent normalization. Based on an amount of attenuation of a first heart sound, a second heart sound can be normalized by modifying portions of the second heart sound by amounts determined based on frequencies of the portions. Accordingly, the systems and methods disclosed herein can result in different amounts of modification of different portions of the second heart sound based on the different frequencies of the portions.

There is disclosed herein examples of systems and methods of processing captured heart sounds with frequency-dependent normalization. Based on an amount of attenuation of a first heart sound, a second heart sound can be normalized by modifying portions of the second heart sound by amounts determined based on frequencies of the portions. Accordingly, the systems and methods disclosed herein can result in different amounts of modification of different portions of the second heart sound based on the different frequencies of the portions.

The invention provides systems and methods for monitoring the wellbeing of a fetus by the non-invasive detection and analysis of fetal cardiac electrical activity data.

Systems and methods for monitoring physiologic response to Valsalva maneuver (VM) are disclosed. An exemplary patient monitor may detect a natural incidence of a VM session occurred in an ambulatory setting using a heart sound (HS) signal sensed from the patient. The patient monitor may include a physiologic response analyzer to sense patient physiologic response during the detected VM session, and generate a cardiovascular or autonomic function indicator based on the sensed physiologic response to the VM. Using the physiologic response to the VM, the system may detect a target physiologic event using the sensed physiologic response to the VM.

Techniques and devices for implementing the techniques for adjusting atrial arrhythmia detection based on analysis of one or more P-wave sensing windows associated with one or more R-waves. An implantable medical device may determine signal characteristics of the cardiac signal within the P-wave sensing window, determine whether the cardiac signal within the sensing window corresponds to a P-wave based on the determined signal characteristics, determine a signal to noise ratio of the cardiac signal within the sensing window, update the arrhythmia score when the P-wave is identified in the sensing window and the determined signal to noise ratio satisfies a signal to noise threshold.