User-defined graphical shapes for neurostimulation target programming
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Solution Overview
Problem
Current neurostimulation systems for treating conditions like Parkinson's Disease face challenges in precisely defining the stimulation target region, leading to laborious programming processes and variability in treatment effectiveness due to differing anatomical targets among researchers.
Innovation Solution
A system that allows users to define a stimulation target region using user-defined graphical shapes, which can be three-dimensional, customizable, and registered with anatomical references, enabling more flexible and precise programming of neurostimulation devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional neurostimulation programming systems use fixed anatomical targets, then programming is standardized, but treatment effectiveness varies due to differing anatomical targets among researchers and patients
Solution Approach 1:
The system transitions from fixed, static anatomical targets to dynamic, user-definable graphical shapes that can be customized for each patient and programming session. The graphical shape interface allows clinicians to dynamically adjust target regions based on individual patient anatomy and treatment responses, resolving the contradiction between standardization and adaptability.
Solution Approach 2:
The system allows modification of key parameters including graphical shape geometry, position, size, and orientation to define custom stimulation targets. By enabling parameter changes in target definition, the system achieves both consistency through structured parameters and flexibility through customizable values, addressing the reliability-adaptability contradiction.
2Measurement precision
If neurostimulation programming uses detailed anatomical targeting, then treatment precision is improved, but programming time and complexity increase
Solution Approach 1:
The system uses graphical shapes as simplified representations (copies) of complex anatomical target regions. Instead of requiring detailed anatomical modeling and segmentation, clinicians work with geometric shape copies that capture the essential spatial characteristics of target regions, achieving precision without excessive time investment.
Solution Approach 2:
The programming process is segmented into discrete, manageable steps: selecting graphical shape type, positioning the shape, adjusting size and orientation parameters, and finalizing the target. This segmentation breaks down complex target definition into routine operations, improving precision while controlling programming time.
3Measurement precision
If multiple programming sessions are conducted to define stimulation targets, then treatment accuracy is improved, but patient burden and treatment cost increase
Solution Approach 1:
The system performs preliminary target definition using graphical shapes during the initial programming session, establishing a baseline target that can be refined in subsequent sessions. This preliminary action reduces the need for extensive re-programming by providing a solid starting point that captures the essential target geometry and position.
Solution Approach 2:
The system incorporates feedback mechanisms where programming results from one session inform and refine targets in subsequent sessions. The graphical shape interface allows quick adjustment and comparison of target definitions across sessions, enabling efficient convergence to optimal targets and reducing the total number of sessions required.
Data Source
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AI summary
A system for programming a neurostimulation device coupled to one or more electrodes. The system comprises a user interface configured for allowing a user to select a set of stimulation parameters and to define a graphical shape representative of an anatomical region of interest. The system further comprises memory configured for storing the graphical shape in registration with an anatomical reference, and output circuitry configured for communicating with the neurostimulation device. The system further comprises a controller configured for recalling the registered graphical shape and anatomical reference from the memory, generating display signals capable of prompting the user interface to concurrently display a representation of the electrode(s) relative to the recalled graphical shape and anatomical reference, and programming the neurostimulation device with the selected stimulation parameter set via the output circuitry.