Brain Wave Fluctuation Analysis Using Power Spectrum and S Pedigree
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Solution Overview
Problem
Current electroencephalographic technologies are inadequate for comprehensive and precise analysis of brain wave fluctuations, limiting their clinical utility in diagnosing brain functions and diseases due to the weakness and complexity of brain wave signals, and existing methods fail to provide sufficient information for accurate diagnosis.
Innovation Solution
A method and apparatus for analyzing brain wave signals using PC techniques, which involves dividing signals into subsections, performing power and frequency spectrum analyses, and acquiring data parameters through conventional and S pedigree analyses, including error treatment and sampling with specific electrode configurations, to provide detailed insights into brain function and disease diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional electroencephalogram methods are used, then the device complexity is low, but the measurement precision and information completeness are insufficient
Solution Approach 1:
The patent segments the brain wave signal analysis into multiple independent modules: signal acquisition module, power spectrum analysis module, S pedigree analysis module, and parameter calculation module. Each module processes specific aspects of the signal independently, improving measurement precision through specialized processing while managing complexity through modular design.
Solution Approach 2:
The patent introduces S pedigree analysis as an additional dimension beyond conventional power spectrum analysis. By analyzing brain wave signals in both frequency domain (power spectrum) and S pedigree domain (supra-slow wave analysis), the system achieves comprehensive multi-dimensional characterization of brain function, significantly improving diagnostic information completeness.
2Loss of information
If comprehensive brain wave analysis is performed, then the information completeness for diagnosis is improved, but the loss of time for signal processing increases
Solution Approach 1:
The patent performs preliminary power spectrum analysis on the brain wave signals to identify dominant frequency components and characteristic patterns before conducting the more time-consuming S pedigree analysis. This preliminary processing filters and prioritizes relevant signal features, reducing the overall processing time while maintaining comprehensive diagnostic information.
Solution Approach 2:
The patent introduces an intermediary data processing layer that transforms raw brain wave signals into standardized spectral parameters and S pedigree values. This intermediary representation serves as a bridge between signal acquisition and final diagnosis, enabling efficient computation of multiple diagnostic parameters from a single processed dataset.
3Measurement precision
If detailed spectral analysis is performed, then the measurement precision of brain function parameters is improved, but the device complexity increases
Solution Approach 1:
The patent designs a universal data processing apparatus that performs multiple functions: power spectrum analysis, S pedigree analysis, dominant frequency identification, and various parameter calculations (A/P ratio, L/R ratio, entropy). This multi-functional system achieves detailed spectral analysis precision while managing complexity through integrated processing capabilities that reuse computational results across different analysis functions.
Data Source
AI summary
The present invention applies computer techniques to the power spectrum analysis of brain wave signals, wherein the power spectrum fluctuations of supra-slow wave is obtained by selecting the maximum value of the power amplitude within 0.5 and 50 Hz and performing multiple analysis of the power spectrum and frequency spectrum, and a series of data and parameters are obtained to provide a basis for cerebral functions testing and disease diagnosis by analyzing the fluctuations. The analysis method comprises the analysis of the conventional power spectrum and may also comprises the analysis of the fluctuation signals of brain wave power, fluctuations of brain wave, S pedigree and further multi-item analyses. And the relevant apparatus implementing such method comprises electrodes, brain wave signal amplifier or a brain wave recording box, a Personal Computer, data processor and terminal processors.