Abstract: A system including a learning module and an algorithmic module for learning a physiological aspect of a patient body and regulating the delivery of a physiological agent to the body. An embodiment of the invention is an adaptive CRT device performing biventricular pacing in which the AV delay and VV interval parameters are changed dynamically according to the information supplied by the IEGM, hemodynamic sensor and online processed data, in order to achieve optimal hemodynamic performance. A learning module, preferably using artificial neural network, performs the adaptive part of the algorithm supervised by an algorithmic deterministic module, internally or externally from the implanted pacemaker or defibrillator.

Abstract: A system for remotely monitoring cardiac resynchronization therapy (CRT) devices and for optimizing location of implanted leads. The system displays a graph of the right ventricle pacing interval (PRV) vs. left ventricle pacing interval (PLV) diagram at maximal stroke volume and or a graph of a responder curve that demonstrates the stroke volume obtained beat after beat by the implanted hemodynamic sensor with dynamically optimized AV and VV parameters. The system lends itself easily to be used as a remote monitoring means for active and resting patients.

Abstract: An adaptive feed-back controlled system for regulating a physiological function of a heart in which a hemodynamic sensor continuously monitors the physiological performance of the heart. Three implanted electrodes sense and pace the right atrial, right ventricle and left ventricle. A learning neural network module receives and processes information for the electrodes (18) and sensors (22), and is controlled by a deterministic module for limiting said learning module. A pulse generator (16), is also controlled by the deterministic module, and stimulates both the heart and the vagus (20).

Abstract: A development system for a cardiac pacemaker control system, the development system comprising: a cardiac pacemaker prototype including an adaptive control system; and a heart simulator in communication with the cardiac pacemaker prototype comprising: a means for receiving pacing stimulations output from the cardiac pacemaker prototype; and a hemodynamic sensor model responsive to the received pacing stimulations, the hemodynamic sensor model being operable to output a signal simulating a hemodynamic sensor in a plurality of heart states, the hemodynamic sensor model being further operative to output the signal simulating the hemodynamic sensor in the plurality of heart states in a plurality of heart conditions.

Abstract: A system including a learning module and an algorithmic module for learning a physiological aspect of a patient body and regulating the delivery of a physiological agent to the body. An embodiment of the invention is an adaptive CRT device performing biventricular pacing in which the AV delay and VV interval parameters are changed dynamically according to the information supplied by the IEGM, hemodynamic sensor and online processed data, in order to achieve optimal hemodynamic performance. A learning module, preferably using artificial neural network, performs the adaptive part of the algorithm supervised by an algorithmic deterministic module, internally or externally from the implanted pacemaker or defibrillator.