Closed Loop Control in Spinal Cord Stimulation Therapy

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Solution Overview

Problem

Existing implantable neurostimulator devices, such as Spinal Cord Stimulation (SCS) systems, face challenges in efficiently adjusting stimulation parameters to optimize neural response without causing patient discomfort or perception of paresthesia.

Innovation Solution

The integration of an accelerometer with the implantable stimulator device allows for the reception of accelerometer signals, which are used to predict neural features indicative of the neural response to stimulation. These predicted neural features are then utilized to adjust the stimulation parameters, maintaining them within a set-range or relative to a set-point, using control models such as Kalman filtering or PID controllers.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If stimulation parameters are increased to improve neural response efficacy, then therapeutic effect is enhanced, but patient discomfort and perception of paresthesia increase

Engineering Contradiction:

Improveneural response efficacyVSAvoidpatient discomfort

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system employs closed-loop feedback control where ECAP signals are continuously monitored and fed back to adjust stimulation parameters. The controller compares the measured ECAP amplitude against a target range and dynamically modifies stimulation amplitude, pulse width, or frequency to maintain optimal neural response while preventing patient discomfort from excessive stimulation.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically changes stimulation parameters (amplitude, pulse width, frequency) based on real-time ECAP measurements. By adjusting these parameters within optimal ranges, the system maximizes therapeutic effect while keeping stimulation below the patient's perception threshold, thus avoiding discomfort.

Inventive Principle:

Principle #35Parameter changes

2Object-affected harmful factors

If stimulation parameters are decreased to avoid patient discomfort, then paresthesia-free therapy is achieved, but neural response efficacy is reduced

Engineering Contradiction:

Improvepatient discomfortVSAvoidneural response efficacy

Core Design Contradiction:

Object-affected harmful factorsVSReliability

Solution Approach 1:

The feedback control system ensures that even at lower stimulation intensities, the neural response remains within the therapeutic range by continuously monitoring ECAP signals and adjusting parameters to maintain optimal efficacy without causing discomfort.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically adapts stimulation parameters based on real-time neural response measurements. Rather than using fixed low-intensity settings, the system optimizes parameters moment-to-moment to achieve maximum therapeutic effect at the lowest effective intensity, maintaining sub-perception levels while ensuring adequate neural activation.

Inventive Principle:

Principle #15Dynamics

3Reliability

If ECAP signals are used for closed loop control, then stimulation optimization is improved, but ECAP signals must be detectable which limits applicability

Engineering Contradiction:

Improvestimulation optimizationVSAvoidapplicability to all patients

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system uses ECAP signals as an intermediary measure of neural response when detectable, but provides alternative optimization methods when ECAPs are not detectable. This allows the system to maintain adaptability across different patient populations while still achieving stimulation optimization through available physiological markers or algorithmic approaches.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Measurement precision

If closed loop control is implemented with real-time ECAP monitoring, then stimulation precision is improved, but device complexity increases

Engineering Contradiction:

Improvestimulation precisionVSAvoiddevice complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system combines stimulation delivery, ECAP sensing, signal processing, and control algorithms into an integrated implantable device. By merging these functions into a single system rather than separate components, the patent reduces overall system complexity while maintaining high measurement precision for closed-loop control.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS12337182B2Closed loop control in spinal cord stimulation therapy with non-detectable neural responses

Publication Date: 2025.06.24 BOSTON SCI NEUROMODULATION CORP

AI summary

Methods and systems for providing closed loop control of stimulation provided by an implantable stimulator device are disclosed herein. The disclosed methods and systems use a neural feature prediction model to predict a neural feature, which is used as a feedback control variable for adjusting stimulation. The predicted neural feature is determined based on one or more signals from an accelerometer configured in contact with the patient. The disclosed methods and systems can be used to provide closed loop feedback in situations, such as sub-perception therapy, when neural features cannot be readily directly measured.