Implantable Stimulator Controller Interface for Adaptive Pain Management
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Solution Overview
Problem
Existing implanted stimulator devices lack an efficient method for configuring optimal stimulation settings, such as polarity and pulse parameters, to effectively manage pain, often requiring manual adjustment and lacking personalized feedback mechanisms.
Innovation Solution
A computer-assisted method and controller device that present configuration options to users, receive feedback on pain levels, build user profiles, and adjust settings based on historical data to optimize stimulation parameters like polarity, pulse rate, and amplitude, using a learning engine to suggest improved settings for future treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of stimulation settings is used, then device complexity is reduced, but ease of operation deteriorates due to requiring user expertise and time-consuming trial-and-error configuration
Solution Approach 1:
The system performs self-configuration by automatically collecting user feedback on pain levels and stimulation comfort, then using this feedback to iteratively optimize stimulation parameters without requiring manual expert adjustment. The device essentially configures itself based on real-time user responses.
Solution Approach 2:
The system continuously collects feedback from users regarding pain levels and stimulation comfort, processes this feedback through algorithms, and adjusts stimulation parameters accordingly. This closed-loop feedback mechanism enables automatic optimization of configuration settings based on actual user experience.
2Adaptability or versatility
If personalized stimulation settings are implemented, then adaptability improves, but device complexity increases due to requiring feedback collection and processing systems
Solution Approach 1:
The system collects personalized feedback from each user regarding pain levels and stimulation comfort, processes this individual-specific data, and generates personalized stimulation parameter recommendations. This feedback-driven approach enables true personalization without requiring complex pre-programming of individual profiles.
Solution Approach 2:
The system automatically builds and updates individual user profiles through self-service mechanisms, where users simply provide feedback and the system autonomously processes this information to create personalized treatment recommendations without requiring manual profile creation or complex user setup.
3Ease of operation
If automated configuration is implemented, then ease of operation improves, but loss of information increases due to reliance on algorithmic decisions rather than user expertise
Solution Approach 1:
The system captures and utilizes valuable user expertise by collecting detailed feedback on pain levels, comfort, and treatment effectiveness. This feedback serves as a direct transmission of user experience and expertise to the algorithm, ensuring that automated decisions are grounded in actual user needs and responses rather than losing this critical information.
Data Source
AI summary
Some computer-assisted methods include: presenting configuration options to a user of the implanted stimulator device, the configuration options comprising stimulation parameters for the implanted stimulator; receiving a user specification of the configuration options in response to the presented configuration options; receiving user feedback when the user specified configuration options are implemented at the implanted stimulator device, the user feedback comprising a quantitative index of pain resulting from implementing the user specified configuration options on the implanted stimulator device; building a user profile for the user based on the user specified configuration options and the user feedback, the user profile including the user specified configuration options as well as the corresponding quantitative index of pain; and selecting at least one configuration option based on the user profile when the configuration options are subsequently presented to the user for a later treatment.