Biosignal Frequency Determination Using Extrema Point Matching
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Solution Overview
Problem
Existing methods face challenges in reliably extracting useful information from biosignals due to low amplitudes and noise, making it difficult to determine frequencies such as heart rate and respiration rate accurately.
Innovation Solution
A method that identifies extrema points in biosignals and compares them with sets of reference points corresponding to different frequencies, determining the best fit by assigning values based on offset, allowing for efficient frequency determination without the need for calibration signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used to extract information from biosignals, then the information can be obtained, but the reliability is low due to low amplitudes and noise
Solution Approach 1:
The method segments the biosignal analysis by identifying individual extrema points (peaks and troughs) rather than analyzing the entire continuous signal. This segmentation allows for focused comparison of discrete points against reference patterns, improving reliability by isolating meaningful features from noisy portions of the signal.
Solution Approach 2:
The patent creates multiple copies of the detected extrema points by generating sets of reference points through applying offsets to represent different frequencies. These reference copies are then compared against the actual extrema to determine the most likely frequency, enabling reliable frequency determination even when the original signal is noisy.
2Measurement precision
If complex signal processing methods are used to handle noisy biosignals, then measurement precision may improve, but device complexity increases
Solution Approach 1:
The method extracts only the essential features from the biosignal - the extrema points - and discards the rest of the noisy signal. By taking out only the relevant information (peaks and troughs) and comparing these against simplified reference patterns, the method achieves good measurement precision with reduced computational complexity compared to full-signal processing approaches.
Solution Approach 2:
The patent generates multiple sets of reference points (excessive action) by applying various offsets to the extrema, then compares these against the detected signal. This partial approach of generating reference copies for different frequency possibilities allows the system to achieve precise frequency determination without requiring complex signal processing algorithms.
3Measurement precision
If calibration signals are used to improve frequency determination accuracy, then measurement precision improves, but the process requires additional time and resources
Solution Approach 1:
The method uses the biosignal itself to generate the reference points needed for comparison. By detecting extrema points from the actual signal and creating reference sets through systematic offset application, the system performs self-calibration without requiring external calibration signals or additional setup time, achieving accurate frequency determination directly from the measured signal.
Data Source
AI summary
A method, apparatus and computer program wherein the method comprises: identifying a plurality of extrema points in a detected biosignal; comparing the identified extrema points with a plurality of sets of reference points wherein different sets of reference points correspond to different frequencies of the biosignal; and identifying the set of reference points that most closely fit the identified extrema points to determine a frequency of the biosignal.