Activity-Responsive Neurostimulation for Balanced Therapy Duration
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Solution Overview
Problem
Existing neurostimulation systems lack the ability to dynamically adjust stimulation programs based on patient activity, leading to suboptimal therapy delivery and potential side effects.
Innovation Solution
A neurostimulation system that monitors patient activities using external and implantable devices, generates activity profiles, and adjusts stimulation programs in real-time to align with the patient's schedule and clinician-defined rules, ensuring optimal therapy delivery and minimizing side effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If neurostimulation systems use fixed stimulation programs, then device complexity is reduced, but therapy effectiveness deteriorates due to inability to adapt to patient activities
Solution Approach 1:
The neurostimulation system automatically monitors patient activities via sensors, determines activity profiles, and adjusts stimulation programs without requiring manual intervention. The system serves itself by autonomously adapting therapy based on detected patient states, eliminating the need for continuous clinician programming while maintaining high adaptability.
Solution Approach 2:
The system transitions from fixed, static stimulation programs to dynamic, activity-responsive programming. Stimulation parameters are continuously adjusted based on real-time activity detection and profile matching, allowing the therapy to evolve with patient needs throughout the day while managing complexity through automated algorithms.
2Measurement precision
If neurostimulation systems monitor patient activities continuously, then therapy precision is improved, but energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system uses periodic activity sampling at defined intervals to build activity profiles. Sensors activate at specific times or upon detected state changes, allowing precise activity characterization while minimizing continuous power consumption. The system balances measurement precision with energy conservation through timed monitoring cycles.
Solution Approach 2:
The system performs preliminary activity monitoring and profile determination during initial periods to establish baseline activity patterns. Once profiles are established, the system can reduce monitoring intensity while maintaining therapy effectiveness, as the activity profiles enable prediction and adjustment without requiring constant high-precision detection.
3Reliability
If stimulation programs are adjusted frequently based on activity changes, then therapy effectiveness is improved, but patient comfort deteriorates due to potential over-stimulation
Solution Approach 1:
The system applies different stimulation characteristics to different activity contexts rather than uniform adjustment. Each activity profile triggers specific stimulation parameter modifications tailored to that activity type, allowing effective therapy adaptation while avoiding excessive or inappropriate stimulation. The local quality principle ensures stimulation is optimized for each activity state without causing harmful over-stimulation.
Solution Approach 2:
The system incorporates feedback mechanisms where stimulation responses are monitored and used to refine future adjustments. By observing patient responses to activity-based stimulation changes, the system learns optimal adjustment patterns and avoids modifications that may cause discomfort or side effects, thereby maintaining high reliability while protecting patient comfort.
Data Source
AI summary
This application is generally related to systems and methods for providing a medical therapy to a patient by tracking patient activity and adjusting medical therapy based on occurrence of different types of activities performed by the patient while automatically balancing stimulation program duration.