Spinal Cord Stimulation Fitting Algorithm Using Supra-Perception Search

Solution Overview

Problem

Spinal Cord Stimulation (SCS) therapy often causes paresthesia, a sensation that can be uncomfortable, and achieving sub-perception therapy without paresthesia is challenging, requiring longer electrode selection times and increased power consumption.

Innovation Solution

Using supra-perception stimulation during the sweet spot search to quickly determine effective electrodes, followed by titrating to sub-perception levels, and employing Multiple Independent Current Control (MICC) to optimize stimulation parameters, including frequency and pulse width, to reduce paresthesia and power consumption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If sub-perception stimulation is used to avoid paresthesia, then patient comfort is improved, but electrode selection time and power consumption increase

Engineering Contradiction:

ImproveparesthesiaVSAvoidelectrode selection time

Core Design Contradiction:

Object-affected harmful factorsVSLoss of time

Solution Approach 1:

The system performs preliminary supra-perception stimulation during the sweet spot search phase to quickly identify effective electrodes, before transitioning to sub-perception levels for final therapy. This preliminary action at higher intensity accelerates electrode selection while the subsequent reduction to sub-perception levels ensures patient comfort during ongoing therapy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The stimulation system dynamically adjusts between supra-perception and sub-perception levels based on the operational phase. During initial electrode selection, supra-perception stimulation is applied for rapid identification, then the system transitions to sub-perception stimulation for comfortable ongoing therapy, making the intensity adaptive rather than static.

Inventive Principle:

Principle #15Dynamics

2Object-affected harmful factors

If sub-perception stimulation is used to avoid paresthesia, then patient comfort is improved, but power consumption increases

Engineering Contradiction:

ImproveparesthesiaVSAvoidpower consumption

Core Design Contradiction:

Object-affected harmful factorsVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary supra-perception stimulation during the sweet spot search phase to quickly identify effective electrodes, before transitioning to sub-perception levels for final therapy. This preliminary action at higher intensity accelerates electrode selection while the subsequent reduction to sub-perception levels ensures patient comfort during ongoing therapy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The stimulation system dynamically adjusts between supra-perception and sub-perception levels based on the operational phase. During initial electrode selection, supra-perception stimulation is applied for rapid identification, then the system transitions to sub-perception stimulation for comfortable ongoing therapy, making the intensity adaptive rather than static.

Inventive Principle:

Principle #15Dynamics

3Device complexity

If traditional stimulation parameter selection is used, then device complexity is reduced, but therapy effectiveness is compromised due to paresthesia

Engineering Contradiction:

Improvestimulation controlVSAvoidparesthesia

Core Design Contradiction:

Device complexityVSObject-affected harmful factors

Solution Approach 1:

The system changes the stimulation parameter regime based on the operational phase. During sweet spot search, supra-perception parameters (higher intensity) are used for rapid electrode identification. During ongoing therapy, sub-perception parameters (lower intensity) are applied to eliminate paresthesia while maintaining therapeutic benefit, thus managing the trade-off between complexity and effectiveness.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20240245920A1Fitting Algorithm to Determine Best Stimulation Parameter from a Patient Model in a Spinal Cord Stimulation System

Publication Date: 2024.07.25 BOSTON SCI NEUROMODULATION CORP

AI summary

Methods for determining stimulation for a patient having a stimulator device are disclosed. A model is received at an external system indicative of a range or volume of preferred stimulation parameters, which model is preferably specific to and determined for the patient. The external system receives a plurality of pieces of fitting information for the patient, including information indicative of a symptom of the patient, information indicative of stimulation provided by the stimulator device during a fitting procedure, and/or phenotype information for the patient. The external system determines one or more sets of stimulation parameters for the patient using the pieces of fitting information. In one example, training data is applied to the pieces of fitting information to select the one or more sets of stimulation parameters from the range or volume of preferred stimulation parameters in the model.