Neuromodulation Programming Algorithm for Patient-Centered Optimization
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Solution Overview
Problem
Current neuromodulation device programming is complex, time-consuming, and often requires multiple hospital visits, failing to adequately address patients' non-motor symptoms and varying needs, leading to suboptimal treatment outcomes.
Innovation Solution
A method and system that allow patients to adjust treatment parameters in a home environment using a user input device and algorithm, which determines optimal settings based on patient feedback and responses to stimulation, adapting settings over time to prioritize patient-centered outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative programming process with multiple hospital visits is used, then treatment parameters can be optimized, but time consumption and clinical resources increase significantly
Solution Approach 1:
The system enables patients to perform self-optimization of treatment parameters through automated algorithms that analyze patient feedback and adjust settings without requiring repeated hospital visits. The neuromodulation device automatically iterates through parameter adjustments based on patient-reported outcomes, transforming the optimization process from provider-dependent to patient-enabled self-service.
Solution Approach 2:
The system implements continuous feedback loops where patients provide feedback on treatment effectiveness, and the automated algorithm uses this feedback to iteratively adjust parameters. This closed-loop feedback mechanism allows real-time optimization of treatment parameters based on actual patient responses, eliminating the need for manual re-programming at subsequent visits.
2Measurement precision
If iterative programming process with multiple hospital visits is used, then treatment parameters can be optimized, but clinical resources are consumed significantly
Solution Approach 1:
The system transfers the resource-intensive optimization task from clinical providers to automated algorithms and patients. The neuromodulation device performs computational analysis and parameter adjustment autonomously, while patients provide necessary feedback inputs, eliminating the need for repeated clinical resource consumption associated with manual programming visits.
Solution Approach 2:
The system replaces the mechanical process of manual provider-based programming with automated electronic algorithms that perform optimization calculations. The computational system substitutes for the clinical expertise and time resources that would otherwise be required for each iterative programming session, enabling continuous optimization without proportional increases in clinical resources.
3Device complexity
If predefined programs with fixed settings are used, then device complexity is reduced, but adaptability to patient's changing symptoms and needs decreases
Solution Approach 1:
The system transforms static predefined programs into dynamic,自适应 parameter settings that automatically adjust based on real-time patient feedback and symptom changes. The automated algorithm continuously modifies treatment parameters in response to evolving patient needs, enabling the device to adapt dynamically rather than requiring manual reconfiguration for each change in symptom profile.
Solution Approach 2:
The system implements feedback-driven adaptability where patient responses to treatment are continuously monitored and fed back into the automated optimization algorithm. This feedback mechanism enables the device to automatically adjust parameters in response to changing symptoms and needs, maintaining adaptability while avoiding the complexity of manual programming by using automated computational processes.
Data Source
AI summary
The present invention relates to a method for programming a neuromodulation device (100), comprising:(a) determining an initial health condition of a patient;(b) determining one or more conditions and/or symptoms and/or expected outcomes for the patient;(c) determining initial settings for the neuromodulation device including one more treatment parameters based on the determined initial health condition of the patient and/or the one or more conditions and/or symptoms and/or expected outcomes, and delivering stimulation to the patient based on the determined initial settings;(d) determining a patient's response with respect to the delivered stimulation(e) implementing an algorithm that is set to modify, based on the determined patient response, the one or more treatment parameters within a predefined range and determine new settings for the neuromodulation device;(f) repeating steps (d) and (e), and(g) maintaining the one or more treatment parameters settings identified as optimal by the algorithm.