Anonymized Global Matrix for Brain Stimulation Simulation
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Solution Overview
Problem
Current brain stimulation simulation methods are inefficient and time-consuming, especially when performing simulations for multiple users, due to limited computing performance in medical institutions, and face legal challenges related to personal information protection when transmitting medical data externally.
Innovation Solution
A brain stimulation simulation system and method using an anonymized data-based external server, where a global matrix is generated and transmitted to perform simulations on multiple users, ensuring anonymity and utilizing a high-performance external server for faster and more accurate processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If brain stimulation simulation is performed using medical data of multiple users, then simulation accuracy is improved, but personal information protection is compromised
Solution Approach 1:
The patent extracts and removes personally identifiable information from medical data before performing brain stimulation simulations. Only anonymized data elements necessary for simulation accuracy are retained, separating identifiable information from simulation-relevant data to resolve the contradiction between accuracy and privacy protection
Solution Approach 2:
The patent introduces an intermediary anonymization process that transforms original medical data into simulated data. This intermediary step acts as a mediator between the need for accurate simulation results and the requirement to protect personal information, allowing simulations to proceed without exposing identifiable data
2Reliability
If brain stimulation simulation is performed using internal computing devices, then data security is improved, but simulation speed deteriorates
Solution Approach 1:
The patent segments the simulation process into two parts: data preparation and anonymization performed internally on secure devices, and actual simulation computation performed externally on high-performance devices. This segmentation allows data security requirements to be met during data handling while utilizing external computing power for speed-intensive simulation tasks
Solution Approach 2:
The patent introduces anonymized simulation data as an intermediary that can be safely transmitted to external computing devices. This intermediary form of data maintains the essential characteristics needed for accurate simulation while removing security concerns, enabling fast external processing without compromising data protection
3Productivity
If brain stimulation simulation is performed for multiple users simultaneously, then productivity is improved, but computing resource requirements increase
Solution Approach 1:
The patent merges simulation computations for multiple users onto external high-performance computing devices. By consolidating multiple simulation tasks on powerful external hardware rather than distributing them across multiple internal devices, the system achieves higher throughput while reducing the total computing resources required at the medical institution
Solution Approach 2:
The patent uses anonymized global matrices as intermediaries that aggregate information from multiple users. These matrices serve as a compressed representation that enables parallel processing of multiple user simulations simultaneously on external devices, increasing productivity while reducing the computational burden compared to processing individual user data separately
Data Source
AI summary
A brain stimulation simulation system and method according to a preset guide system using an anonymized data-based external server are provided. According to various embodiments of the present invention, provided is a brain stimulation simulation method according to a preset guide system using an external server, the method performed by a computing device, the method including: a first server generating a global matrix for performing brain stimulation simulation on a plurality of objects by using a plurality of brain models for each of the plurality of objects; and a second server being provided with the generated global matrix from the first server and performing the brain stimulation simulation on the plurality of objects by using the provided global matrix.