Biomimetic MEMS-Transformer for Neurological Disorder Detection
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Solution Overview
Problem
Current artificial neuronal networks lack connection to neuroscience, particularly in mimicking biological neural processing systems' low-power consumption and flexibility, and struggle to differentiate normal from pathological high-frequency oscillations, which is crucial for diagnosing and predicting neurological disorders like Alzheimer's and epilepsy.
Innovation Solution
Development of a new generation of mem-transformers with memresistive/memcapacitive/meminductive characteristics using biomimetic organic polymer membranes that mimic normal and mutated acetylcholinesterase (ACHE) gorge structures, enabling the creation of Energy-Sensory brain circuitry images to dynamically display synaptic changes and detect biomarkers for neurological disorders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If artificial neuronal networks are developed through electric circuitry architectures, then computational functionality is achieved, but connection to neuroscience and biological neural processing features are lost
Solution Approach 1:
The patent copies biological neural structures by creating toroidal devices with membrane-bound compartments that mimic neuronal morphology, including dendritic trees and axonal projections. The membrane itself is designed to replicate the lipid bilayer structure of biological membranes, enabling direct仿生 modeling of neuronal behavior rather than abstract circuitry approximation
Solution Approach 2:
The patent changes the fundamental parameters of neural network implementation by transitioning from rigid electronic circuitry to soft, deformable membrane structures that can dynamically alter their physical and electrical properties. The membrane's capacitance, resistance, and ion channel conductance can be modulated to match biological neural parameters
2Measurement precision
If conventional sensors are used to detect neurological biomarkers, then basic detection is achieved, but differentiation between normal and pathological high-frequency oscillations is lost
Solution Approach 1:
The toroidal devices incorporate dynamic elements including voltage-gated ion channels, ligand-gated channels, and mechanically-sensitive channels that can actively respond to and differentiate various oscillation patterns. The membrane structure allows for dynamic redistribution of charge and ion flow that mirrors biological neuronal responses to different stimulus frequencies
Solution Approach 2:
The patent introduces membrane-bound ion channels and receptors as intermediary elements between the external electrical signals and the detection system. These intermediaries selectively respond to specific frequency ranges and signal patterns, enabling differentiation of normal from pathological oscillations through their distinct response characteristics
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the identification and prediction of neurological disorders, including early signs of Alzheimer's and epilepsy, by dynamically displaying circuitry changes and sensing energy changes in biological fluids with high sensitivity and temporal resolution, facilitating early diagnosis and monitoring of neuronal dysfunction.
Implementation Method 1
Nano-biomimetic MEMS-transformer devices of making and an application in energy-sensory images thereto relates to the field of electromagnetic systems and induction
Data Source
AI summary
An electromagnetic mems-transformer includes arrays of nanostructured first toroid winding by a self-assembled organic conductive membrane on an electrode, and a second toroid winding with “donut” shape cyclodextrins (CDs) comprising of different electronegativity functional groups was inserted in the first toroid; a hydrophobic laminate agent forms a linen lining the first cavity of the toroid in perpendicular to the first and second toroid with air gaps for adjusting, upon applying a DC potential crosses two electrodes in a fluid medium for initiation of the device, a changing current flows until reached the s-s state in a nano Ampere level. When held the nano Ampere current in constant for spontaneous discharge voltage pulses, the current induced an electromagnetic flux change with orders of magnitude higher output voltage produced compared with the initiation potential. Embedded on-off switches promoted hysteresis i-V curves for memory function. Applications in sensing neuronal dysfunctions in an Energy-Sensory Image were demonstrated.