Neuromodulation Controller Circuit for State Determination
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Solution Overview
Problem
Existing medical systems struggle to accurately determine and normalize patient states using sensed signals, which can lead to suboptimal therapy delivery and increased side effects.
Innovation Solution
A system comprising an electrostimulator, a sensing circuit, and a controller circuit that delivers electrostimulation to a neural target, senses evoked responses, and determines patient parameters to classify and associate features with states, allowing for adjusted therapy settings and medication schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional medical systems use fixed therapy settings, then device complexity is reduced, but treatment efficacy decreases due to inability to adapt to varying patient states
Solution Approach 1:
The system continuously monitors patient physiological signals (such as neural activity, muscle response, or other biometric data) and uses this feedback to automatically adjust therapy parameters. The controller circuit receives real-time data from sensors, compares it against target ranges, and modifies stimulation settings accordingly, creating a closed-loop control system that adapts to patient state changes without requiring complex manual reconfiguration
Solution Approach 2:
The medical device performs self-adjustment of therapy parameters based on its own sensing capabilities. The embedded controller automatically normalizes signals, determines patient state, and modifies electrostimulation settings without external intervention, allowing the device to serve itself in optimizing treatment while maintaining simplicity for the user
2Measurement precision
If therapy settings are manually adjusted based on observations, then ease of operation is maintained, but measurement precision of patient state deteriorates
Solution Approach 1:
The system replaces manual observation and judgment with automated electronic sensing and processing. Sensors objectively measure physiological parameters, and the controller circuit automatically analyzes these signals to determine patient state, eliminating the subjectivity and imprecision of manual assessment while requiring minimal user interaction beyond initial setup
3Object-affected harmful factors
If therapy parameters are fixed, then device complexity is reduced, but side effects increase due to suboptimal therapy delivery
Solution Approach 1:
The system transitions from static, fixed therapy parameters to dynamic, continuously adjustable settings. The controller circuit modifies pulse amplitude, frequency, width, and other parameters in real-time based on sensed patient response, allowing the therapy to adapt to changing physiological conditions and prevent side effects that arise from inappropriate fixed settings
4Productivity
If real-time signal sensing is implemented, then treatment efficacy is improved, but use of energy increases
Solution Approach 1:
The system employs periodic sensing and adjustment cycles rather than continuous operation. The controller circuit senses patient signals at optimized intervals, processes data in batches, and adjusts parameters periodically based on accumulated information. This approach maintains treatment efficacy by capturing meaningful physiological changes while significantly reducing the energy burden of constant monitoring and processing
Data Source
AI summary
Systems and methods for state determination and normalization using adaptive neuromodulation based on biopotentials and/or electrophysiology (e.g., evoked responses) are disclosed. An exemplary system comprises at least one lead, an electrostimulator to provide electrostimulation to a neural target, a sensing circuit to sense ERs to electrostimulation, and a controller circuit. In response to electrostimulation delivered to the neural target in accordance with a stimulation setting via a stimulating electrode, the controller circuit may collect sensed ERs to the electrostimulation using at least one sensing electrode. The controller circuit may determine at least one parameter associated with the electrostimulation or an affect of the electrostimulation to the neural target. The controller circuit may associate at least one feature of a first set of the sensed ERs with the parameter to classify the parameter.


