Neural Response Recording With Adaptive Electrode Parameter Sequencing
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Solution Overview
Problem
Existing neurostimulation systems face challenges in efficiently determining and adjusting stimulation and sensing parameters for evoking and recording neural responses, particularly in procedures like deep brain stimulation, which can be time-consuming and require numerous combinations of electrode settings.
Innovation Solution
A neurostimulation system with a stimulation output circuit, sensing input circuit, and control circuit is used to deliver and sense neural responses, employing a sequence of evoking-recording parameter sets to optimize electrode configurations and minimize evaluation time, utilizing techniques like prior information and spatial-temporal arrangements to reduce measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine stimulation and sensing parameters through numerous electrode setting combinations, then comprehensive coverage of parameter space is achieved, but the procedure becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by using prior information from previous measurements, patient history, and theoretical models to pre-calculate and prioritize promising parameter combinations before actual measurement, thereby reducing the number of measurements needed while maintaining optimization accuracy
Solution Approach 2:
The system creates virtual copies of the measurement process through computer simulations and predictive models that estimate neural responses to different parameter settings, allowing the system to evaluate multiple parameter combinations in silico before performing actual measurements, thus reducing real-world measurement time
2Reliability
If multiple electrode configurations are evaluated to find optimal stimulation and sensing parameters, then therapy effectiveness is improved, but the complexity of the system increases
Solution Approach 1:
The system segments the parameter optimization process into distinct phases: initial screening of electrode configurations using simplified models, followed by detailed optimization of promising candidates using full physiological models. This segmentation allows comprehensive evaluation without overwhelming system complexity at any single stage
Solution Approach 2:
The system dynamically adjusts model parameters and measurement settings based on intermediate results, adapting the complexity of analysis to the specific needs of each electrode configuration. This allows the system to maintain high reliability while managing computational complexity through adaptive parameter adjustment
3Adaptability or versatility
If comprehensive sensing of neural responses is performed to verify lead placement and optimize parameters, then therapy customization is improved, but the quantity of measurements required increases
Solution Approach 1:
The system implements feedback mechanisms where each measurement result immediately informs subsequent measurement decisions. Neural responses are sensed and used to adjust upcoming measurements, allowing the system to focus on the most informative parameter combinations and reduce the total number of measurements needed for effective customization
Solution Approach 2:
The measurement strategy is made dynamic rather than static, with the system continuously adapting which parameters to measure and in what order based on real-time results. This dynamic approach allows comprehensive therapy customization while minimizing the total measurement burden by concentrating resources on the most critical parameters
Data Source
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AI summary
The present invention relates to a system for delivering neurostimulation to a patient using a plurality of electrodes. The system comprises a stimulation output circuit configured to deliver the neurostimulation to evoke responses from the patient using an evoking configuration defining a stimulation electrode set including electrodes selected from the plurality of electrodes; and a sensing input circuit configured to sense one or more signals including the evoked responses using a recording configuration defining a sensing electrode set including electrodes selected from the plurality of electrodes. The system further comprises a control circuit configured to control the delivery of the neurostimulation using stimulation parameters defining the evoking configuration, to control the sensing of the evoked responses using sensing parameters defining the recording configuration, and to adjust the stimulation parameters and the sensing parameters according to a sequence of evoking-recording parameter sets each including a set of the stimulation parameters determined for controlling the stimulation output circuit to deliver the neurostimulation to evoke a target response and a set of the sensing parameters determined for controlling the sensing input circuit to record the evoked target response.