Abstract: Techniques and systems for calibrating a blood pressure measuring device are disclosed. They include sensing a first blood pressure by a first device when the first device is at a first height, sensing a second blood pressure by the first device when the first device is at a second height, the second height being different than the first height, and generating the blood pressure calibration factor based on the first blood pressure, the first height, the second blood pressure, and the second height.

Abstract: Techniques and systems disclosed herein are directed to determining pacing attributes for a patient and include determining use of a beta blocker with intrinsic sympathomimetic activity (ISA) by the patient, receiving a current physiological input, and determining pacing attributes based on the determining use of the beta blocker with ISA and the current physiological input. They further include receiving a current physiological input, determining pacing attributes based on the current physiological input, causing a pacing device to output pacing outputs based on the pacing attributes, receiving an updated physiological input after causing the pacing device to output the pacing outputs, determining that a difference between the current physiological input and the updated physiological input does not meet a threshold difference, and generating an indication of a presence or use of a non-ISA beta blocker based on the difference not meeting the threshold difference.

Abstract: A method of therapeutically treating a subject includes the steps of: sensing sympathetic nerve activity; communicating the sensed sympathetic nerve activity to a processor; using machine learning in the processor to identify input data sets correlated to a physiological end point in the subject by processing the input data input sets to experientially optimize an algorithmically defined physiological goal defined in output data sets by the machine learning; and dynamically controlling a therapeutic device in real time with the processor using the output data sets to treat the subject mediated by the therapeutic device by establishing or tending to establish the physiological end point in the subject.

Abstract: The invention is directed to a method of treating a patient with DRH and/or HFpEf including the steps of: treating the patient with angiotensin converting enzyme inhibitor (ACEI) and/or an angiotensin receptor blocking [ARB] drug; and cardiac pacing the patient as controlled by a BaroPace algorithm. Performance is improved by simultaneously withholding administration of any beta-1 selective beta adrenergic blockers. A method of cardiac pacing to treat drug resistant hypertension and heart failure with preserved ejection fraction (HFpEF) includes the steps of administering to a patient a therapeutic amount of a beta blocker having intrinsic sympathomimetic activity (ISA); and pacing the heart of a patient using the BaroPace algorithm.

Abstract: The invention is a method of using thoracic electrical bioimpedance (TEB) as a component in a real-time closed-loop system to treat drug resistant hypertension (DRH) or diastolic heart failure (called HFpEF in patients with pacemakers using machine learning/AI and an algorithm (PressurePace—see the incorporated specifications) utilizing a “micro-interval” or continually updated trending method with the pacemaker's hardware/software as the source of the bioimpedance measurement, e.g. OptiVol. An apparatus for performing the method, and software instructions stored on a tangible medium for controlling a computer or processor to perform the method are included.

Abstract: A method of right atrial pacing of a heart of a patient includes the steps of: stimulating right atrial tissue of the heart using a right atrial lead of a dual chamber cardiac pacemaker to pace the heart with a stimulus architecture protocol; and stimulating local sympathetic and/or parasympathetic tissues with the stimulus architecture protocol proximate to the paced right atrial tissue causing nervous system activity that inhibits the autonomous nervous system to reduce blood pressure. A closed loop system operating according to this method and a cardiac pacing lead for implementing this method also are included within the scope of the illustrated embodiments.

Abstract: A pacemaker control system includes a pacemaker; a plurality of sensors which are internal to the pacemaker, a plurality of sensors which are external to the pacemaker, a circuit for entering patient reports; and a circuit for using artificial intelligence to process outputs from the plurality sensors internal and external to the pacemaker and from the circuit for entering patient reports, which are collectively identified as a labeled dataset, to reiteratsvely learn a function which determines the labeled dataset most likely to provide optimal pacemaker function for the patient. The means for using artificial intelligence comprises a database of archive outputs from the plurality sensors internal and external to the pacemaker and from the means for entering patient reports for the patient used for optimization of rate modulation to intelligently, continuously and physiologically control the pacemaker.