Closed-Loop Neural Stimulation for Hypertension
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Solution Overview
Problem
Current neural stimulation systems for treating hypertension are ineffective as they do not adapt to physiologic changes, relying on continuous or intermittent open-loop stimulation, which fails to respond to varying physiological conditions.
Innovation Solution
A closed-loop neural stimulation system comprising a pulse generator, signal processing module, and controller that senses neural traffic and adjusts stimulation parameters in real-time to converge on desired neural activity, using feedback from sensed nerve traffic to modify the stimulation signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If open-loop neural stimulation is used to treat hypertension, then continuous stimulation can be provided, but the system cannot adapt to physiologic changes during therapy
Solution Approach 1:
The patent implements a closed-loop neural stimulation system that senses neural traffic at a neural sensing site and uses this feedback to adjust stimulation parameters at a neural stimulation site. The controller receives feedback control signals indicative of sensed neural traffic and adjusts the neural stimulation control signal to converge on desired neural traffic, enabling the system to adapt to physiologic changes during therapy.
Solution Approach 2:
The system uses the patient's own neural traffic signals as feedback to automatically adjust stimulation parameters. The controller compares the sensed neural traffic to desired neural traffic and self-adjusts the stimulation signal parameters without requiring external intervention, allowing the system to adapt to changing physiological conditions.
2Reliability
If continuous neural stimulation is applied to treat hypertension, then therapeutic effect can be maintained, but the treatment does not respond to varying physiological conditions
Solution Approach 1:
The patent makes the stimulation system dynamic by continuously adjusting stimulation parameters based on real-time neural traffic feedback. The controller modifies pulse amplitude, width, or frequency according to the difference between sensed and desired neural traffic, allowing the system to respond to varying physiological conditions while maintaining therapeutic efficacy.
Solution Approach 2:
The system changes stimulation parameters (amplitude, pulse width, frequency) based on feedback from neural traffic sensing. The controller adjusts at least one parameter of the neural stimulation signal to converge on desired neural traffic, enabling the treatment to adapt to physiological variations while maintaining reliable therapeutic effect.
3Ease of operation
If neural stimulation parameters are fixed, then device operation is simple, but treatment effectiveness decreases when physiological conditions change
Solution Approach 1:
The patent employs feedback control where the controller continuously monitors neural traffic and automatically adjusts stimulation parameters to maintain desired neural activity levels. This closed-loop approach ensures treatment effectiveness varies only minimally with physiological changes while requiring minimal user intervention beyond initial setup.
Data Source
AI summary
Various device embodiments comprise a pulse generator, a signal processing module and a controller. The pulse generator is adapted to provide a neural stimulation signal to be applied at a neural simulation site within an autonomic nervous system (ANS). The signal processing module is adapted to receive and process sensed neural traffic at a neural sensing site within the ANS. The controller is connected to the pulse generator and adapted to provide a neural stimulation control signal to the pulse generator to generate the neural stimulation signal, and to the signal processing module to receive a feedback control signal indicative of the sensed neural traffic. The controller is adapted to adjust the neural stimulation control signal to adjust at least one parameter of the neural stimulation signal to converge on desired sensed neural traffic at the neural sensing site. Other aspects and embodiments are provided herein.