Neuromodulation Therapy Adjustment Using Physiological Feedback
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Solution Overview
Problem
Existing neuromodulation therapies struggle to customize treatment for individual users, maintain effective therapy while minimizing power consumption, detect lead migration, identify health risks, and enhance patient comfort and safety.
Innovation Solution
A system that adjusts neuromodulation therapy based on physiological inputs, using a processor to receive and analyze cardiac signals, sensor data, and user feedback to optimize parameters such as stimulation amplitude, frequency, and cycling times, while tracking physiological changes over time to detect events like lead migration and health risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If neuromodulation therapy is continuously delivered to maintain effective treatment, then therapy effectiveness is improved, but power consumption increases
Solution Approach 1:
The system implements cycling therapy delivery with periodic on/off intervals rather than continuous stimulation. The processor controls the pulse generator to deliver therapy in cycles, adjusting the cycling parameters based on physiological inputs to maintain effectiveness while reducing overall power consumption during off periods
Solution Approach 2:
The system dynamically adjusts therapy parameters including cycling ratios, amplitudes, and durations based on real-time physiological inputs. This allows the therapy to adapt its delivery pattern to maintain effectiveness while optimizing power consumption according to the user's current physiological state
2Reliability
If neuromodulation therapy parameters are customized for individual users, then therapy effectiveness is improved, but device complexity increases
Solution Approach 1:
The system uses physiological inputs from sensors as feedback to automatically adjust therapy parameters. The processor receives physiological data, analyzes it to determine therapy response scores, and generates appropriate parameter adjustments, enabling customization without requiring complex manual programming interfaces
Solution Approach 2:
The system performs self-adjustment of therapy parameters based on physiological feedback. The processor automatically modifies stimulation parameters according to detected physiological states, reducing the need for external intervention and simplifying the user interface while maintaining personalized therapy
3Measurement precision
If physiological monitoring is continuously performed to detect lead migration and health risks, then detection accuracy is improved, but power consumption increases
Solution Approach 1:
The system performs physiological monitoring at periodic intervals rather than continuously. The processor analyzes physiological inputs at scheduled times to detect lead migration and health risks, maintaining detection accuracy while consuming power only during monitoring and analysis periods
Solution Approach 2:
The system monitors only the specific physiological parameters necessary for detecting lead migration and health risks rather than all possible parameters. This selective monitoring approach maintains detection accuracy for critical events while reducing overall power consumption
Data Source
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AI summary
Systems and methods for generating and/or applying an adjustment for one or more parameters of a neuromodulation therapy of a user are provided. One or more physiological-based inputs of the user may be received and a therapy response score may be determined based on the one or more physiological-based inputs. At least one adjustment for one or more parameters of the neuromodulation therapy may be generated based on the therapy response score.