Tunable MEMS Neuroprosthetic Electrodes for Nerve Bundle Targeting
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Solution Overview
Problem
Current neural interface and neuromodulation technologies lack stability and specificity to target specific sensory or motor neurons within a nerve bundle, hindering the development of effective chronic neural prosthetic devices.
Innovation Solution
A microelectromechanical system (MEMS) device with tunable microactuators and microelectrodes that can be precisely positioned using a closed-loop control scheme and microbonding technique, allowing for autonomous and precise targeting of neurons within a nerve bundle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current neural interface technologies are used, then device simplicity is maintained, but stability and specificity to target specific neurons are insufficient
Solution Approach 1:
The device segments the neural interface into multiple independently controllable microelectrodes, each capable of targeting specific neurons within the nerve bundle. This segmentation allows precise individual addressing of neurons while maintaining overall system stability through modular control architecture.
Solution Approach 2:
The device incorporates dynamically adjustable microelectrode positions and stimulation parameters, allowing real-time adaptation to target specific neurons. The dynamic control enables the system to optimize stability and specificity by adjusting electrode placement and stimulation characteristics based on neural feedback.
2Reliability
If current neural interface technologies are used, then device simplicity is maintained, but specificity to target specific sensory or motor neurons is insufficient
Solution Approach 1:
The device applies local quality by enabling individual microelectrodes to target specific sensory or motor neurons within different regions of the nerve bundle. Each microelectrode can be independently positioned and controlled to interact with specific neuron types, achieving high specificity through localized neural interface rather than uniform stimulation.
Solution Approach 2:
The device incorporates feedback mechanisms that monitor neural responses and adjust stimulation parameters in real-time. This closed-loop control enhances specificity by identifying and targeting specific neuron populations based on their electrical characteristics and response patterns, while maintaining system manageability through adaptive algorithms.
3Measurement precision
If microelectrodes are positioned precisely in nerve bundle, then neural signal detection accuracy is improved, but device complexity increases
Solution Approach 1:
The device performs preliminary positioning actions during implantation to place microelectrodes in optimal locations within the nerve bundle. This preliminary precise positioning is achieved through controlled insertion mechanisms and initial alignment features, reducing the need for complex post-implantation adjustment mechanisms while maintaining high detection accuracy.
Data Source
AI summary
A microelectromechanical device and method for neuroprosthetics comprises microactuators and microelectrodes. The microelectrodes are to be positioned in a nerve bundle and bonded with the microactuators through an interconnect. The position of each of the microactuators can be individually tuned through control signals so that the microelectrodes are implanted at desired positions in the nerve bundle. The control signals are transmitted to the microactuators and generated with a open-loop or closed-loop control scheme that uses signals acquired by the microelectrodes from the nerve bundle as feedback.