Brain-Computer Signal Safety Modeling for Subject Harm Prevention
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Solution Overview
Problem
Current Brain-Computer Interface (BCI) technologies lack a unified standard for brain-computer signal safety, leading to insufficient accuracy and precision in safety measures, potentially causing harm to subjects.
Innovation Solution
A brain-computer signal safety system comprising a database module, data acquisition module, analysis module, and safety module, which stores a safety model, acquires signals, analyzes them for compliance with safety constraints, and performs safety processing to enhance signal safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a safety range is defined and signals are monitored for compliance, then safety monitoring is implemented, but the accuracy and precision of safety measures are insufficient
Solution Approach 1:
The patent segments the safety monitoring process into multiple independent modules: a database module storing safety standards, a data acquisition module collecting signal data, an analysis module processing and comparing signals against standards, and a safety module executing safety measures. This segmentation allows each module to specialize in specific tasks, improving overall accuracy and precision of safety monitoring while maintaining reliability.
Solution Approach 2:
The patent introduces an analysis module as an intermediary between the data acquisition module and the safety module. This intermediary analyzes raw signal data against stored safety standards and determines appropriate safety measures, thereby improving the accuracy and precision of safety monitoring by adding a layer of intelligent processing and decision-making.
2Reliability
If existing safety measures are implemented, then safety monitoring is provided, but harm may still occur to subjects
Solution Approach 1:
The patent implements preliminary action by establishing a comprehensive database of safety standards and constraints before actual signal processing occurs. The analysis module continuously compares acquired signals against these pre-established standards, enabling preventive safety measures to be taken before harmful effects can occur, thereby reducing harm to subjects while maintaining reliable safety monitoring.
Solution Approach 2:
The patent establishes a feedback mechanism where the analysis module continuously monitors signal compliance against safety standards and provides feedback to the safety module. When deviations are detected, the system automatically adjusts safety measures or alerts operators, creating a closed-loop system that prevents harm to subjects while maintaining reliable safety monitoring through continuous adaptation.
Data Source
Figure 1
AI summary
The present invention discloses a braincomputer signal safety system and its method of use, which pertains to the technical field of intelligent information processing. The braincomputer signal safety system comprises: An information acquisition module (consistent with the "data acquisition module" elsewhere in this specification) configured to acquire braincomputer signals and safety information related to the braincomputer signals; An analysis module configured to take the braincomputer signals and the safety information of the braincomputer signals as inputs, conduct analysis using a braincomputer signal safety model, determine whether the braincomputer signals meet the safety constraints, and obtain appropriate braincomputer signal safety measures when the safety constraints are met; A safety module configured to perform safety processing on the braincomputer signals according to the appropriate braincomputer signal safety measures. By performing safety processing on the braincomputer signals through the appropriate braincomputer signal safety measures derived from the preestablished braincomputer signal safety model, the safety of the BrainComputer Interface (BCI) can be improved, the usage effect of the BCI can be enhanced, and safety hazards to the subjects affected by the braincomputer signals can be avoided.