Physiological Signal Analysis Using Wavelet Scalogram Band Combination
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Solution Overview
Problem
Existing physiological signal analysis methods often rely on single scale bands, which can be influenced by noise and artifacts, leading to inconsistent and inaccurate information, especially when multiple scale bands related to physiological processes are not effectively combined.
Innovation Solution
The method involves analyzing multiple scale bands in a scalogram, assessing their quality, and combining them using weighted combinations or concatenation to improve the accuracy and consistency of physiological information extraction, particularly by identifying related bands associated with integer multiples of a primary scale band and removing undesirable signal characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single scale band analysis is used, then device complexity is reduced, but measurement precision and reliability deteriorate due to noise and artifact influence
Solution Approach 1:
The patent combines multiple scale bands in the scalogram that are related to the same physiological process (e.g., pulse rate, respiratory rate, blood oxygen saturation). By merging information from multiple scale bands including harmonics and sub-harmonics, the system improves measurement precision and reliability while reducing the influence of noise and artifacts on the physiological parameter extraction
Solution Approach 2:
The patent segments the scalogram into multiple scale bands and evaluates each band's quality independently using quality metrics. This segmentation allows the system to identify and weight high-quality bands while reducing the influence of low-quality bands contaminated by noise or artifacts, thereby improving overall measurement precision
2Measurement precision
If multiple scale bands are combined, then measurement precision and reliability improve, but device complexity increases
Solution Approach 1:
The patent introduces quality metrics as additional parameters to evaluate each scale band's suitability for analysis. By calculating quality metrics for each band and using these parameters to weight or select bands for combination, the system improves measurement precision while managing complexity through systematic parameter-based selection rather than arbitrary band inclusion
3Reliability
If quality assessment of scale bands is performed, then reliability of physiological information improves, but processing time increases
Solution Approach 1:
The patent applies quality assessment selectively to scale bands that are most relevant to the physiological process being measured. By focusing quality evaluation on critical bands and using quality metrics to weight their contribution, the system improves reliability of the physiological information while minimizing the time penalty associated with comprehensive quality assessment of all bands
Data Source
AI summary
Methods and systems are disclosed for analyzing multiple scale bands in the scalogram of a physiological signal in order to obtain information about a physiological process. An analysis may be performed to identify multiple scale bands that are likely to contain the information sought. Each scale band may be assessed to determine a band quality, and multiple bands may be combined based on the band quality. Information about a physiological process may determined based on the combined band. In an embodiment, analyzing multiple scale bands in a scalogram arising from a wavelet transformation of a photoplethysmograph signal may yield clinically relevant information about, among other things, the blood oxygen saturation of a patient.