Multi-axis efficacy visualization for implantable therapy optimization
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Solution Overview
Problem
Current implantable electrical stimulation therapies face challenges in optimizing efficacy due to individual patient differences in age, gender, physiology, and disease state, leading to varying responses to stimulation parameters, and require time-consuming clinician evaluation to balance therapeutic effects with side effects.
Innovation Solution
A patient-individualized efficacy rating system that allows patients and clinicians to assign weighting values to efficacy parameters, generating a customized rating and visualization using a multi-axis graphical representation to prioritize therapeutic outcomes and minimize side effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a clinician manually evaluates various electrode combinations and parameter values to identify an acceptable stimulation program, then the therapy can be customized to balance effectiveness with side effects, but the process becomes time consuming
Solution Approach 1:
The system enables patients to self-monitor and self-report efficacy parameters and side effects, eliminating the need for continuous clinician evaluation. Patients use a user interface to input their own therapy responses, and the system automatically processes this data to identify optimal programs, allowing patients to serve themselves in the therapy optimization process
Solution Approach 2:
The system implements continuous feedback loops where patient-reported efficacy and side effect data are automatically fed back into the analysis engine. This feedback mechanism allows the system to learn from patient responses and automatically adjust program recommendations, replacing manual clinician feedback cycles with automated real-time feedback processing
Solution Approach 3:
The system automatically varies and evaluates multiple stimulation parameters (electrode combinations, amplitudes, pulse widths, rates) according to patient-specific criteria. By systematically changing parameters and evaluating patient responses, the system identifies optimal configurations without requiring manual clinician testing of each parameter combination
2Reliability
If stimulation parameters are optimized for individual patient characteristics, then therapeutic efficacy is improved, but the complexity of parameter selection and evaluation increases
Solution Approach 1:
The system applies patient-specific weighting values to different efficacy and side effect parameters based on individual patient characteristics and priorities. Each patient receives customized weighting that reflects their unique needs, allowing the system to optimize therapy locally for each patient rather than using a one-size-fits-all approach
Solution Approach 2:
The system breaks down the complex therapy optimization problem into separate, independently weightable efficacy parameters and side effect parameters. By segmenting the overall evaluation into discrete components (efficacy parameters, side effect parameters, weighting values), the system simplifies the complexity while maintaining comprehensive individualized optimization
3Adaptability or versatility
If multiple efficacy parameters are monitored and weighted according to patient priorities, then personalized therapy optimization is achieved, but the data processing and visualization requirements increase
Solution Approach 1:
The system introduces a user interface as an intermediary layer between the complex data processing engine and the patient. This interface simplifies data input, presentation, and interaction, allowing patients to easily provide feedback and view results without being overwhelmed by the underlying complexity of processing multiple weighted parameters
Solution Approach 2:
The system uses graphical representations and visual models to copy and present complex efficacy data in simplified formats. By creating visual copies of the data (graphs, charts, summaries), the system makes complex multi-parameter information accessible and understandable to patients without requiring them to directly process the raw complexity
Data Source
AI summary
The disclosure is directed to techniques for providing a visualization of efficacy ratings for a medical therapy. A graphical representation of weighted efficacy parameter values may be displayed to provide a visualization of efficacy for the patient. The graphical representation may include a boundary extending between the efficacy parameter values on multiple axes. If the representation includes three axes, the shape of the boundary may be substantially triangular. The graphical representation may simultaneously display multiple graphical representations. Each of the multiple multi-axis graphical representations corresponds to efficacy parameter values obtained for different sets of therapy parameters or to efficacy parameter values obtained at different times. The graphical representation may be modified so that the efficacy parameter values correspond to values relating to a time reference specified by a user. Multiple graphical representations for different time references may be displayed simultaneously, permitting the user to compare efficacy over time.