Excitation Time Map for Biological Signal Simulation
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Solution Overview
Problem
Current biological signal simulation methods are time-consuming, particularly in modeling the propagation of electrical signals between cells, which is a clinically significant challenge due to the complexity of partial differential equations and large multidimensional meshes.
Innovation Solution
The technique employs an excitation time map (ETM) generated using ordinary differential equations to represent the propagation of electrical signals, replacing the Laplacian operator with a map representing cell excitation, allowing for faster computation by solving the reaction function over a time-dependent multidimensional domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If partial differential equations are solved on large multidimensional meshes to model biological signal propagation, then simulation accuracy is improved, but computational time increases significantly
Solution Approach 1:
The patent extracts the essential dynamics of electrical signal propagation by separating the spatial diffusion component (Laplacian operator) from the temporal reaction component. By representing spatial propagation through pre-computed excitation time maps and using only ordinary differential equations for temporal dynamics, the method retains accurate simulation of action potential propagation while dramatically reducing computational complexity and time requirements.
Solution Approach 2:
The patent performs preliminary computation of the excitation time map, which encodes the spatial propagation characteristics of electrical signals. This pre-computed map serves as input to the ordinary differential equation solver, allowing the system to focus computational resources on solving the time-dependent reaction dynamics rather than recomputing spatial propagation at each time step, thus reducing overall computational time while maintaining accuracy.
2Manufacturing precision
If the number of elements in the mesh is increased to represent detailed tissue structure, then model fidelity is improved, but calculation time increases to several days or weeks
Solution Approach 1:
The patent extracts the critical information needed for accurate simulation from the detailed mesh structure and encodes it in the excitation time map. This allows the system to maintain high model fidelity by preserving the essential spatial propagation characteristics while eliminating the need to solve PDEs across the entire detailed mesh at each time step, thereby dramatically improving calculation speed.
Solution Approach 2:
The patent creates a simplified representation (copy) of the spatial propagation dynamics through the excitation time map, which captures the essential information about action potential propagation without requiring the full detailed mesh. This simplified representation is then used in the ordinary differential equation formulation, maintaining model fidelity while reducing computational complexity to achieve clinically meaningful calculation times.
3Reliability
If the propagation of electrical signals between cells is modeled in detail, then biological accuracy is improved, but computational time becomes the most time-consuming part of the simulation
Solution Approach 1:
The patent extracts the temporal dynamics of electrical signal propagation by formulating the reaction function as an ordinary differential equation that depends only on time and the membrane potential. This separation allows the system to maintain biologically accurate modeling of action potential dynamics while avoiding the computationally intensive PDE solving required for spatial propagation, thereby reducing computational time without sacrificing biological accuracy.
Solution Approach 2:
The patent substitutes the mechanical PDE-based spatial propagation modeling with a time-dependent ODE approach driven by the excitation time map. This substitution replaces the computationally intensive spatial discretization and PDE solving with a more efficient temporal integration method, maintaining biological accuracy in modeling electrical signal propagation while significantly reducing computational time requirements.
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
This approach significantly reduces computational time for simulating biological signal propagation, achieving results comparable to partial differential equation methods with lower CPU time and maintaining high accuracy, enabling real-time medical simulations.
Implementation Method 1
generating, by the analysis device, an excitation time map by solving a diffusion reaction of electrical signals calculated from the time-series medical images
Data Source
AI summary
There is provided an analysis device for generating an excitation time map, which includes an interface device configured to receive time-series medical images of a subject and a computing device configured to generate an excitation time map by solving a diffusion reaction of electrical signals calculated from the time-series medical images using a solution of an ordinary differential equation. The excitation time map indicates excitation times at grid points of the time-series medical image.