Neural Prosthetic Control via Eye Position and Neural Signal Integration
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Solution Overview
Problem
Current neural prosthetics lack effective methods to incorporate and utilize measurements of voluntary eye movements, which are crucial for natural behavior and decision-making, limiting their control and accuracy.
Innovation Solution
A method and system that record eye position and neural activity signals to combine and match them with predetermined patterns to control the spatial positioning of prosthetic devices, allowing for more accurate and efficient control by mimicking natural behavior and decision-making processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neural prosthetics are controlled using only neural activity signals, then the device complexity is reduced, but the control accuracy and prediction capability are insufficient
Solution Approach 1:
The patent combines neural activity signals with eye position signals to control prosthetic devices. The system integrates multiple data sources (neural activity from electrodes and eye position from video tracking or search coils) to improve control accuracy. This merging of signal types allows the system to leverage complementary information from both neural activity and eye movements, resolving the contradiction between accuracy and complexity by making the complexity manageable through structured integration.
Solution Approach 2:
The system is designed to accommodate multiple signal types and control modes. The prosthetic device can operate using neural activity alone, eye position alone, or a combination of both, providing versatility. This multi-functionality allows the system to adapt to different user needs and experimental conditions, improving control accuracy without being forced into a single complex configuration.
2Reliability
If voluntary eye movements are incorporated into prosthetic control, then the prediction of behavior is improved, but the measurement and recording requirements become more complex
Solution Approach 1:
The patent introduces eye position signals as an intermediary measurement that bridges the gap between neural activity and behavioral output. Eye position serves as a reliable indicator of intended action and cognitive state, improving behavior prediction. The system uses established eye tracking technologies (video tracking, search coils) as intermediaries to capture this information without requiring direct invasive measurements, thereby managing complexity through well-understood measurement techniques.
Solution Approach 2:
The system records eye position and neural activity in advance to predict upcoming behaviors. By capturing eye movements and neural signals before the actual action occurs, the system can identify patterns and predict behavior. This preliminary recording approach allows the system to anticipate user intentions and improve the reliability of prosthetic control without requiring complex real-time processing during the action itself.
3Measurement precision
If multiple signal types are integrated for prosthetic control, then the control accuracy is improved, but the ease of operation is reduced
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor and adjust the integration of neural and eye position signals. By providing real-time feedback about the quality and relevance of each signal type, the system can dynamically weight and combine signals to optimize spatial positioning accuracy. This feedback approach allows the complex multi-signal system to operate more simply by automatically adapting to changing conditions without requiring manual intervention.
Data Source
AI summary
Prosthetic devices, methods and systems are disclosed. Eye position and/or neural activity of a primate are recorded and combined. The combination signal is compared with a predetermined signal. The result of the comparison step is used to actuate the prosthetic device.