ECAP-Based Dynamic Stimulation Programming for Neural Response Feedback
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Solution Overview
Problem
Existing neurostimulation systems struggle to effectively program dynamic stimulation patterns that utilize time-varying parameters, which are crucial for mimicking natural neural activities and enhancing therapeutic effectiveness, due to the complexity of associating neural recruitment effects with different stimulation parameters.
Innovation Solution
A system and method for determining dynamic stimulation patterns based on targeted modulation of neural responses, using a dynamic pattern composer to modulate stimulation parameters such as pulse amplitude, width, and rate, leveraging sensed neural signals like evoked compound action potentials (ECAPs) to improve efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic stimulation patterns with time-varying parameters are used, then therapeutic effectiveness is improved by mimicking natural neural activities, but programming complexity increases due to the difficulty of associating neural recruitment effects with different stimulation parameters
Solution Approach 1:
The system uses sensed neural signals (ECAPs) as feedback to automatically adjust stimulation parameters. The neural response sensor detects ECAPs, and the programming control circuit uses this feedback to dynamically compose stimulation patterns, eliminating the need for manual programming complexity while maintaining therapeutic effectiveness.
Solution Approach 2:
The system enables self-programming by automatically composing dynamic stimulation patterns based on sensed neural responses. The dynamic pattern composer uses ECAP data to autonomously determine optimal stimulation parameters, allowing the system to program itself without external intervention.
2Ease of operation
If constant stimulation parameters are used, then programming simplicity is maintained, but therapeutic effectiveness is reduced compared to time-varying parameters that resemble natural neural activities
Solution Approach 1:
The system transitions from static constant parameters to dynamic time-varying parameters that automatically adapt based on sensed neural responses. The stimulation parameters change over time according to the dynamic stimulation pattern composed from ECAP data, maintaining simplicity while enhancing effectiveness.
Solution Approach 2:
The feedback loop continuously monitors neural responses and adjusts stimulation parameters in real-time, creating a dynamic system that maintains programming simplicity through automated adaptation while improving therapeutic effectiveness through time-varying stimulation.
3Reliability
If time-varying stimulation parameters are properly programmed, then natural neural activities are more closely resembled, but the difficulty of detecting and measuring neural recruitment effects increases
Solution Approach 1:
The system uses ECAP sensing as feedback to automatically measure neural recruitment effects. The neural response sensor continuously monitors ECAPs, providing real-time data on neural responses to dynamic stimulation, thereby reducing the difficulty of measurement through automated detection.
Solution Approach 2:
The system replaces complex manual measurement methods with automated electronic detection of ECAPs. By using electrical signal sensing and digital processing to detect neural responses, the system simplifies the measurement process while maintaining accurate detection of neural recruitment effects.
Data Source
AI summary
A system for delivering neurostimulation to a patient using a stimulation device may include a programming control circuit and a stimulation programming circuit. The programming control circuit may be configured to generate information for programming the stimulation device to control the delivery of the neurostimulation according to a dynamic stimulation pattern defined by stimulation parameters including at least one time-varying stimulation parameter. The stimulation programming circuit includes a dynamic pattern composer, which may be configured to determine the dynamic stimulation pattern based on a targeted modulation of a neural response by the neurostimulation according to the dynamic stimulation pattern. The neural response is a response of the patient to the delivery of the neurostimulation.