Closed-Loop Neural Stimulation Stability via Evoked Response Analysis
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Solution Overview
Problem
Maintaining appropriate neural recruitment in closed-loop neural stimulation therapy is challenging due to electrode migration, postural changes, and spinal cord movement, leading to instability in the therapy delivery and potential discomfort or ineffectiveness.
Innovation Solution
An implantable neuromodulation device with electrodes and measurement circuitry analyzes loop variables using time-domain and frequency-domain representations to determine loop stability, adjusting stimulus intensity to maintain therapeutic ranges and improve stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If closed-loop feedback control is used to maintain constant neural recruitment, then therapeutic effectiveness is improved, but loop instability occurs due to electrode migration and postural changes
Solution Approach 1:
The patent implements closed-loop feedback control where the measured neural response intensity is fed back to adjust the stimulus intensity, maintaining constant neural recruitment despite electrode migration or postural changes. The controller continuously monitors the neural response and modifies the stimulus parameters to keep the response within the therapeutic range.
Solution Approach 2:
The system dynamically adjusts stimulus intensity based on real-time neural response measurements. The controller gain and other parameters can be adapted to maintain stability under varying conditions, allowing the system to respond to changing physiological states and electrode positions.
2Reliability
If stimulus intensity is increased to ensure adequate neural recruitment, then therapeutic effect is improved, but discomfort or pain occurs due to over-recruitment of fibres
Solution Approach 1:
The system uses feedback control to maintain stimulus intensity within the therapeutic window. By continuously measuring neural response and adjusting stimulus parameters, the system ensures adequate neural recruitment for therapeutic effect while preventing over-recruitment that causes discomfort or pain.
Solution Approach 2:
The controller dynamically changes stimulus parameters (intensity, pulse width, frequency) based on measured neural response to maintain optimal therapeutic effect without causing discomfort. The system adapts parameters in real-time to stay within the comfortable and effective range.
3Ease of operation
If fixed stimulus parameters are used to simplify device operation, then ease of operation is improved, but therapeutic effectiveness decreases due to inability to compensate for electrode migration and postural changes
Solution Approach 1:
The system performs self-adjustment by automatically monitoring neural response and modifying stimulus parameters without user intervention. The closed-loop controller continuously adapts the stimulation to maintain therapeutic effectiveness, eliminating the need for manual reprogramming when electrode position or patient posture changes.
Solution Approach 2:
The device transitions from static fixed parameters to dynamic adaptive parameters that automatically adjust to physiological changes. The system maintains simplicity of operation while improving effectiveness through real-time parameter adaptation based on neural response feedback.
Data Source
AI summary
An implantable neuromodulation device (100) that includes a plurality of stimulus electrodes, measurement electrodes, a stimulus source and measurement circuitry (128). The device also includes a control unit (116) configured to: control the stimulus source to provide a neural stimulus to a neural pathway (180) according to a stimulus intensity parameter; measure an intensity of the evoked neural response in captured signal windows; determine a feedback variable from the measured intensity of the evoked neural response; implement a feedback loop by using the feedback variable to control the stimulus intensity parameter so as to maintain the feedback variable at a target value; convert (1404) a loop variable of the feedback loop to a representation, where the representation is one of a time-domain representation and a frequency-domain representation; and analyse (1406) the representation to determine a loop stability measure of the feedback loop.