Non-linear Signal Separation via Time Domain Projection
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Solution Overview
Problem
Conventional non-linear state space projection methods for separating fetal electrocardiogram signals from a mother's body are inefficient due to high computational requirements and difficulty in accurately processing signals with low S/N ratios, especially when noise components change rapidly or are widespread, limiting their applicability in real-time measurements.
Innovation Solution
The method employs a time domain high-speed non-linear state space projection technique that stabilizes data by shifting cyclic signals and calculating summation averages, allowing for rapid noise removal and signal extraction without requiring extensive dimensional expansion or neighborhood definitions, thus reducing processing time significantly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional non-linear state space projection method is used to separate fetal electrocardiogram signals, then signal separation capability is improved, but processing time increases significantly (100 times slower)
Solution Approach 1:
The patent segments the complex non-linear signal processing into distinct stages: cyclic signal identification, summation average calculation, and noise removal. This segmentation allows each stage to be optimized independently, with the summation average providing a stable reference that simplifies subsequent noise removal operations, thereby reducing overall processing time while maintaining separation capability
Solution Approach 2:
The patent performs preliminary stabilization of the signal by calculating summation averages of cyclic components before conducting noise removal. This preliminary action creates a stable reference framework that simplifies the subsequent signal separation task, allowing faster processing in the final stage while maintaining high separation accuracy
2Measurement precision
If high-dimensional state space projection is used to handle low S/N ratio signals, then signal extraction accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent transforms the low S/N ratio signal into a higher-dimensional space by calculating summation averages across multiple cyclic periods. This dimensional transformation concentrates the signal energy while distributing noise, effectively improving S/N ratio without requiring complex high-dimensional state space projections, thus reducing computational complexity
Solution Approach 2:
The patent changes the temporal parameter by accumulating signals over multiple cyclic periods to form summation averages. This parameter transformation converts weak, noise-dominated individual cycles into a stable, high-S/N reference signal, improving extraction accuracy while avoiding the need for computationally intensive high-dimensional projections
3Object-affected harmful factors
If conventional noise removal methods are used, then noise reduction is achieved, but signal quality deteriorates (all signals become dull)
Solution Approach 1:
The patent introduces summation averages of cyclic signals as an intermediary reference. This intermediary serves as a stable template that guides the noise removal process, allowing selective elimination of noise components while preserving the characteristic features of the fetal electrocardiogram signal, thus maintaining signal quality while achieving noise reduction
4Productivity
If real-time processing is implemented for clinical applications, then measurement speed is improved, but processing accuracy may deteriorate
Solution Approach 1:
The patent exploits the periodic nature of cardiac cycles by accumulating signals over multiple periods to form summation averages. This periodic approach allows real-time processing because each cycle contributes incrementally to the growing accuracy of the reference signal, enabling fast processing while maintaining high accuracy through the stabilizing effect of periodic accumulation
Data Source
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AI summary
There is provided a non-linear signal separation method using the non-linear state space projection method capable of separating an effective non-linear signal even if the S/N ratio is low by performing the time domain high speed non-linear state space projection when a signal is a multi-channel signal and has a periodicity. In the non-linear signal separation method using the non-linear state space projection method, an original signal having a complex signal which is a multi-channel and cyclic signal measured from one phenomenon is processed by using the time domain high-speed non-linear state space projection method so as to estimate a noise in the original signal and subtract the estimated noise from the original signal, thereby separating the signal to be measured in the original signal as a non-linear signal even when the S/N ratio is low.