Neural Response Interpolation for Adaptive Deep Brain Stimulation
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Solution Overview
Problem
Existing deep brain stimulation (DBS) systems face challenges in optimizing electrode placement and stimulation parameters due to non-selective activation of neural elements, leading to potential cognitive impairments and fluctuating therapeutic effects, especially in conditions like Parkinson's disease, where brain dynamics and medication states impact treatment efficacy.
Innovation Solution
A method and device for monitoring neural activity using electrode leads with multiple electrodes, capable of recording, stimulating, and interpolating neural signals to determine optimal stimulation parameters, incorporating techniques such as waveform feature interpolation and closed-loop feedback to adjust stimulation based on brain dynamics and medication states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electrical stimulation is applied to treat neurological disorders, then therapeutic efficacy is improved, but cognitive side effects and non-selective activation of neural elements worsen
Solution Approach 1:
The patent employs multiple independently controllable electrode contacts arranged in three-dimensional arrays, allowing different regions of the brain to receive differentiated stimulation patterns. Each electrode contact can be selectively activated or deactivated, and stimulation parameters (amplitude, pulse width, frequency) can be independently adjusted for each contact, enabling precise targeting of specific neural pathways while sparing adjacent cognitive regions.
Solution Approach 2:
The stimulation system divides the treatment into multiple discrete electrode contacts that can be individually controlled. By segmenting the stimulation delivery across multiple contacts rather than applying uniform stimulation, the system can target specific neural elements responsible for motor symptoms while avoiding activation of neural populations involved in cognitive functions.
2Reliability
If stimulation parameters are increased to improve treatment efficacy, then therapeutic benefit is enhanced, but energy consumption and side effects increase
Solution Approach 1:
The system applies stimulation at different intensities to different electrode contacts based on local therapeutic needs. By adjusting amplitude and pulse width parameters independently for each contact, the system delivers minimum effective dosage to each targeted region, avoiding excessive energy consumption while maintaining treatment efficacy.
Solution Approach 2:
The system uses trial stimulation with sub-threshold or threshold-level parameters to elicit neural responses for monitoring, rather than continuously applying full therapeutic intensity. This allows the system to gather feedback information at lower energy levels and adjust full therapy parameters accordingly, reducing overall energy consumption.
3Measurement precision
If multiple electrode contacts are used to improve selectivity, then precision of neural element targeting is enhanced, but device complexity increases
Solution Approach 1:
The same electrode contacts serve multiple functions: they can be used for both stimulation delivery and neural response monitoring. The system alternates between stimulation phases and sensing phases, using the identical hardware infrastructure for both therapeutic and diagnostic purposes, thereby avoiding the need for separate sensing electrodes and reducing overall device complexity.
Solution Approach 2:
The patent combines stimulation and sensing capabilities within the same electrode contacts and lead structure. By merging these functions into a single integrated system rather than using separate components, the patent reduces device complexity while maintaining the ability to deliver precise, selective stimulation.
4Adaptability or versatility
If neural responses are monitored continuously to adapt stimulation parameters, then adaptability to brain dynamics is improved, but system complexity and processing requirements increase
Solution Approach 1:
The system implements a closed-loop feedback mechanism where neural responses are monitored during or between stimulation deliveries, and this information is used to adjust subsequent stimulation parameters. The feedback loop operates by comparing expected vs. actual neural responses and modifying amplitude, frequency, or pulse width parameters to optimize therapeutic effect while minimizing side effects.
Solution Approach 2:
The system performs trial stimulation with standardized parameters before delivering full therapy, using the neural responses from these preliminary trials to determine optimal stimulation settings. This preliminary characterization of neural responses allows the system to pre-calculate appropriate therapy parameters without requiring continuous complex processing during actual treatment.
Data Source
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AI summary
Methods and systems for using evoked neural response to inform aspects of deep brain stimulation therapy are disclosed. According to some embodiments, a series of evoked neural response signals are recorded, and one or more waveform features are extracted from each of the signals. The waveform features can be used as biomarkers and or control signals for informing aspects of the therapy, such as lead implantation/localization, optimization of stimulation parameters, and/or closed loop feedback for maintaining chronic therapy. Embodiments include a check to determine and classify if any of the recorded neural response signals or portions thereof are corrupted. In the event that any of the signals are corrupted, values for the waveform features for the corrupted signals are interpolated using uncorrupted neural response signals in the series and/or uncorrupted portions of the problem neural response signal.