Neural Recording Artifact Removal via Electrode Correlation
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Solution Overview
Problem
Current methods for removing stimulation artifacts from neural recordings are inadequate, especially in high pulse rate stimulation scenarios, as they either result in signal loss or are unreliable due to variations in artifact amplitude and duration, making them unsuitable for closed-loop applications and multichannel paradigms.
Innovation Solution
The method estimates stimulation artifacts by leveraging the statistical interdependence across multiple recording electrodes, using a mathematical relationship to predict and subtract artifact signals, allowing for accurate measurement of neural responses without requiring temporal synchronization or assumptions about artifact shape or parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If template subtraction is used to remove stimulation artifact, then artifact removal is achieved, but reliability deteriorates due to variations in artifact amplitude and duration across pulses
Solution Approach 1:
The patent segments the artifact removal process into two distinct phases: (1) a training phase where artifact templates are learned from initial pulses, and (2) a processing phase where the learned templates are applied to remove artifacts from subsequent pulses. This segmentation allows the system to adapt to varying artifact characteristics while maintaining consistent removal performance.
Solution Approach 2:
The patent performs preliminary action by acquiring and storing artifact template characteristics during a training phase before actual neural signal processing begins. The system pre-learns the artifact patterns from initial stimulation pulses, creating a reference model that can be applied to subsequent pulses without requiring real-time template generation.
2Object-affected harmful factors
If blanking is used to remove stimulation artifact, then artifact is eliminated, but neural signals are lost during the blanking interval
Solution Approach 1:
The patent extracts only the artifact component from the composite signal using pre-learned templates, rather than discarding the entire signal during a blanking period. By separating and removing only the artifact portion while preserving the neural response components, the system eliminates information loss while still achieving artifact removal.
3Productivity
If high pulse rate stimulation is used to increase productivity, then stimulation throughput increases, but stimulation artifact contamination increases
Solution Approach 1:
The patent enables continuous artifact removal processing by using pre-learned templates that can be applied to each pulse independently and rapidly. This allows the system to maintain high pulse rates without requiring extended blanking periods or complex real-time template generation, thus preserving productivity while effectively removing artifacts from high-rate stimulation.
Data Source
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AI summary
Stimulation of nervous system components by electrodes can be used in many applications, including in the operation of brain-machine interfaces, bidirectional neural interfaces, and neuroprosthetics. The optimal operation of such systems requires a means of accurately measuring neural responses to such stimulations. However, currently the measurement of neural responses is difficult due to heavy stimulation artifacts arising from stimulatory pulses. The invention encompasses novel methods of estimating stimulation artifacts in measurements attained by recording electrodes and the effective removal of these artifacts. This provides improved neural recording systems and enables the deployment of closed-loop neural stimulation systems.