Adaptive cardiac resynchronization therapy system
First Claim
1. An adaptive feed-back controlled cardiac resynchronisation therapy system capable of dynamic AV delay and VV interval pacing related to changes in the data received from at least one hemodynamic sensor continuously monitoring a hemodynamic performance, said system comprising:
- a learning neural network module, for receiving and processing information of said at least one sensor and for learning at least one aspect of said hemodynamic performance body;
a deterministic algorithmic module, receiving parameters of said resynchronisation therapy from said neural network module, anda therapeutic delivery means, for delivering said resynchronisation therapy, said therapeutic delivery means is connected to said deterministic algorithmic module and operated by it;
wherein in a non-adaptive operation mode of said system, said deterministic algorithmic module is used for implementing a supervised learning scheme of said learning neural network module, and wherein said resynchronisation therapy is delivered according to parameters pre-programmed into said deterministic algorithmic module; and
wherein in an adaptive operation mode of said system, said learning neural network module is used for dynamically changing the parameters of said resynchronisation therapy according to the information received from said at least one hemodynamic sensor, and wherein said resynchronisation therapy is delivered according to the parameters provided by said learning neural network module.
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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.
68 Citations
20 Claims
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1. An adaptive feed-back controlled cardiac resynchronisation therapy system capable of dynamic AV delay and VV interval pacing related to changes in the data received from at least one hemodynamic sensor continuously monitoring a hemodynamic performance, said system comprising:
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a learning neural network module, for receiving and processing information of said at least one sensor and for learning at least one aspect of said hemodynamic performance body; a deterministic algorithmic module, receiving parameters of said resynchronisation therapy from said neural network module, and a therapeutic delivery means, for delivering said resynchronisation therapy, said therapeutic delivery means is connected to said deterministic algorithmic module and operated by it; wherein in a non-adaptive operation mode of said system, said deterministic algorithmic module is used for implementing a supervised learning scheme of said learning neural network module, and wherein said resynchronisation therapy is delivered according to parameters pre-programmed into said deterministic algorithmic module; and wherein in an adaptive operation mode of said system, said learning neural network module is used for dynamically changing the parameters of said resynchronisation therapy according to the information received from said at least one hemodynamic sensor, and wherein said resynchronisation therapy is delivered according to the parameters provided by said learning neural network module. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for adaptive biventricular pacing control comprising the steps of:
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obtaining continuous signal from at least one sensor monitoring physiological parameter of said patient; processing said continuous signal by an algorithmic processing module and a learning module and wherein said learning modules carries out adaptive learning in connection with said at least one sensor is first supervised by applying an accepted set of parameters, and delivering a physiological signal by a delivery module in response to said processed signal, wherein said regulation either relates to said algorithmic process or to said learning process, programming initial AV (atriaventricular) delay parameter and VV (interventricular delay) interval parameter of an algorithmic module; providing pacing in a non-adaptive CRT mode wherein an algorithmic deterministic module controls the delivery of pulses, and wherein pacing is provided according to said parameters, switching to an adaptive CRT mode wherein said AV delay and VV interval change dynamically in order to achieve optimal hemodynamic performance, and wherein said adaptive mode is limited to perform above a low limit of hemodynamic performance, and switching back to the non adaptive CRT mode whenever the hemodynamic performance is below a low limit of hemodynamic performance or a sensor failure or any other system failure is detected. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification