Automatic Sub-Perception Parameter Selection in Neurostimulation
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Solution Overview
Problem
The extensive parameter search space in neurostimulation systems, such as SCS, DBS, and PNS, requires a significant amount of time and effort to find the optimal combination of stimulation parameters, which can be daunting for clinicians.
Innovation Solution
An automated method for neurostimulation systems that prioritizes and systematically varies parameters like stimulation site, electrode spacing, and pulse characteristics to efficiently find the optimal neurostimulation settings, reducing the search time and improving efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If many programmable parameters are offered to customize neurostimulation therapy, then treatment efficacy and adaptability are improved, but the parameter search space increases making the optimization process more time-consuming and complex
Solution Approach 1:
The patent segments the parameter search process into distinct phases: initial broad exploration of parameter space followed by focused refinement of promising regions. This segmentation allows the system to efficiently navigate the large parameter space by dividing it into manageable search stages, reducing overall optimization time while maintaining comprehensive coverage of viable treatment options
Solution Approach 2:
The system performs preliminary actions by pre-defining parameter ranges, constraints, and search strategies before the actual optimization begins. This preliminary configuration enables the automated system to systematically explore the parameter space without requiring clinicians to manually test each parameter combination, significantly reducing the time needed to find optimal settings
2Adaptability or versatility
If many programmable parameters are offered to customize neurostimulation therapy, then treatment efficacy and adaptability are improved, but the complexity of the optimization process increases making it more daunting for clinicians
Solution Approach 1:
The system implements self-service by enabling automated parameter optimization that performs the complex search and evaluation process without requiring extensive clinician intervention. The automated system independently navigates the parameter space, evaluates treatment efficacy, and identifies optimal settings, thereby reducing the perceived complexity for clinicians while maintaining full programmable customization options
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors treatment outcomes and uses this information to guide further parameter optimization. This feedback-driven approach simplifies the optimization process by automatically adjusting parameters based on measured efficacy, reducing the burden on clinicians to manually manage the complexity of multiple programmable parameters
3Ease of operation
If parameters are tested one at a time to find the right combination, then the optimization process becomes more manageable, but the overall search time increases significantly
Solution Approach 1:
The patent merges multiple parameter tests into coordinated search strategies that evaluate several parameters simultaneously or in optimized sequences. By combining parameter exploration with outcome evaluation in an integrated automated process, the system maintains operational manageability while dramatically improving search efficiency compared to sequential one-at-a-time testing
Solution Approach 2:
The system employs dynamic parameter search strategies that adapt the testing sequence and scope based on preliminary results. This dynamic approach allows the system to efficiently identify promising parameter combinations by adjusting the search focus in real-time, thereby improving productivity while keeping the optimization process manageable through automated decision-making
Data Source
AI summary
A method of controlling operation of a neurostimulation device comprises receiving, by the neurostimulation device, an indication of a physiological search area of a subject for delivering electrical neurostimulation and a prioritized search list of neurostimulation parameters for neurostimulation therapy delivered to the search area; delivering the neurostimulation therapy to the search area and varying the neurostimulation parameters according to the parameter priority, wherein a highest priority parameter is varied first while lower priority parameters are held constant; determining the optimum value of the highest priority parameter; delivering neurostimulation to the search area using the determined optimum value of the highest priority parameter and varying one or more lower priority parameters according to the parameter priority; and determining optimum lower priority parameters for the neurostimulation.