Neuromodulation System Pseudo-Random Parameter Variation
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Solution Overview
Problem
Current neuromodulation systems face challenges with neurological accommodation, particularly in sub-threshold therapy, where patients may not experience paresthesia, making it difficult to determine if accommodation has occurred, leading to ineffective treatment due to continuous electrical stimulation.
Innovation Solution
The system delivers electrical energy at a sub-threshold level with pseudo-random variation of modulation parameters, such as pulse rate, amplitude, and width, based on previous values and Bayesian algorithms, to mimic physiologically relevant signals and prevent accommodation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous electrical stimulation is delivered to provide neuromodulation therapy, then therapeutic benefit is achieved, but neurological accommodation occurs leading to treatment ineffectiveness
Solution Approach 1:
The system dynamically varies one or more modulation parameters (amplitude, pulse width, frequency, or electrode configuration) over time according to a pseudo-random sequence, transforming the static continuous stimulation into a dynamic variable stimulation pattern that prevents neurological accommodation while maintaining therapeutic efficacy
Solution Approach 2:
The system implements periodic variation of modulation parameters through pseudo-random sequences, where parameters are systematically changed at defined intervals rather than remaining constant, thereby preventing the neural tissue from adapting to a fixed stimulation pattern
2Reliability
If modulation parameters are varied to prevent accommodation, then treatment efficacy is maintained, but determining if accommodation has occurred becomes difficult without paresthesia feedback
Solution Approach 1:
The system incorporates feedback mechanisms where modulation parameters are adjusted based on detected physiological responses, allowing the system to adapt to changing neural conditions and maintain therapeutic efficacy while automatically compensating for accommodation without requiring patient subjective feedback
Solution Approach 2:
The system performs self-adjustment of modulation parameters based on embedded sensors and algorithms that detect neural response changes, enabling the device to automatically prevent accommodation without external intervention or patient feedback about paresthesia
Data Source
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AI summary
A neuromodulation system configured for providing sub-threshold neuromodulation therapy to a patient. The neuromodulation system comprises a plurality of electrical terminals configured for being respectively coupled to a plurality of electrodes, modulation output circuitry configured for delivering electrical energy to the electrical terminals in accordance with at least one modulation parameter, thereby providing therapy to the patient at a sub-threshold level and control circuitry configured for controlling the modulation output circuitry in a manner that pseudo-randomiy varies a value of the at least one modulation parameter based on a previous value of the at least one modulation parameter, such that the delivered electrical energy is continually maintained at the sub-threshold level.