Abstract:
A system comprises processing circuitry and memory comprising program instructions that, when executed by the processing circuitry, cause the processing circuitry to: apply a first set of rules to first patient parameter data for a first determination of whether sudden cardiac arrest of a patient is detected; determine that a one or more context criteria of the first determination are satisfied; and in response to satisfaction of the context criteria, apply a second set of rules to second patient parameter data for a second determination of whether sudden cardiac arrest of the patient is detected. At least the second set of rules comprises a machine learning model, and the second patient parameter data comprises at least one patient parameter that is not included in the first patient parameter data.
Abstract:
An intracardiac ventricular pacemaker having a motion sensor is configured to produce a motion signal including an atrial systolic event and a ventricular diastolic event indicating a passive ventricular filling phase, set a detection threshold to a first amplitude during an expected time interval of the ventricular diastolic event and to a second amplitude lower than the first amplitude after an expected time interval of the ventricular diastolic event. The pacemaker is configured to detect the atrial systolic event in response to the motion signal crossing the detection threshold and set an atrioventricular pacing interval in response to detecting the atrial systolic event.
Abstract:
Techniques for minimizing rate of depletion of a non-rechargeable power source, to extend the operational lifetime of an implantable medical device that includes the non-rechargeable power source, by enforcing operational-mode-specific communication protocols whereby inter-device communication between the implantable medical device and another implantable medical device is such that level of power draw from the non-rechargeable power source by the implantable medical device is less than level of power draw from the rechargeable power source by the another implantable medical device for the implantable medical devices to engage in communication with each other.
Abstract:
The exemplary systems and methods may monitor one or more signals to be used to assess the hemodynamic status of a patient. The one or more signals may be used to calculate, or determine, a plurality of pulse transit times. The plurality of pulse transit times may be used to determine hemodynamic status values that may be indicative of a patient's aggregate hemodynamic status.
Abstract:
An implantable medical device includes a housing having a proximal end and a distal end, a control module enclosed by the housing, and a pressure sensor electrically coupled to the control module. A fixation member is coupled to the housing distal end for anchoring the housing distal end at a fixation site within a cardiovascular system of a patient, and the pressure sensor is spaced apart proximally from the fixation member.
Abstract:
A leadless pacing device (LPD) includes a motion sensor configured to generate a motion signal as a function of heart movement. The LPD is configured to analyze the motion signal within an atrial contraction detection window that begins an atrial contraction detection delay period after activation of the ventricle, and detect a contraction of an atrium of the heart based on the analysis of the motion signal within the atrial contraction detection window. If the LPD does not detect a ventricular depolarization subsequent to the atrial contraction, e.g., with an atrio-ventricular (AV) interval beginning when the atrial contraction was detected, the LPD delivers a ventricular pacing pulse.
Abstract:
A system comprises processing circuitry and memory comprising program instructions that, when executed by the processing circuitry, cause the processing circuitry to: apply a first set of rules to first patient parameter data for a first determination of whether sudden cardiac arrest of a patient is detected; determine that a one or more context criteria of the first determination are satisfied; and in response to satisfaction of the context criteria, apply a second set of rules to second patient parameter data for a second determination of whether sudden cardiac arrest of the patient is detected. At least the second set of rules comprises a machine learning model, and the second patient parameter data comprises at least one patient parameter that is not included in the first patient parameter data.
Abstract:
A system comprising an implantable medical device and processing circuitry. The implantable medical device comprises one or more sensors configured to continuously sense one or more physiological characteristics of a body of a maternal patient, and sensing circuitry operably connected to the one or more sensors and configured to issue one or more output signals indicative of the one or more physiological characteristics. The processing circuitry is configured to define one or more patient attributes using the one or more output signals; and generate an output based on the one or more patient attributes, the output configured to cause a computing device to provide an indication of preeclampsia of the maternal patient to a user.
Abstract:
A method of detecting sleep apnea includes generating a cardiac signal indicating activity of a heart of a patient. The method further includes determining a short-term average heart rate and a long-term average heart rate. The method further includes determining a start and end of a heart rate cycle based on the short-term average heart rate and the long-term average heart rate. The method further includes determining physiological parameter values occurring during the heart rate cycle. The method further includes determining whether patient has or has not experienced a sleep apnea event based on whether one or more conditions are satisfied by one or more parameter values for one or more heart rate cycles and responsively generating an indication that patient has or has not experienced a sleep apnea event.
Abstract:
A system for sensing one or more physiological traits and obstetric conditions, such as a fertility phase, pregnancy, labor, post-partum conditions, and other conditions related to the reproductive system of the patient. The system may use the one or more physiological traits sensed to define one or more patient attributes for the patient, such as a hormone level, heart rate, blood pressure, respiration rate, temperature, oxygen saturation level, uterine contractions, fluid level, and/or other patient attributes. The system is configured to compare the one or more patient attributes to one or more attribute signs describing a threshold for the one or more patient attributes. The system is configured to issue a communication to the patient and/or a clinician based on the comparisons. The system may be configured to assess and indicate reproductive phases for the patient over a life-cycle from the fertility phase to the post-partum phase.