Vital Signal Extraction via Dimensional Reduction
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Solution Overview
Problem
Current methods for extracting vital signals from electromagnetic radiation data streams face challenges such as high computational requirements, susceptibility to noise and disturbances, and the need for obtrusive measurement techniques, especially in mobile and everyday applications where signal-to-noise ratios are poor and ambient conditions are unfavorable.
Innovation Solution
A device and method that utilize dimensional reduction techniques to align characteristic index elements with the reference motion direction, reducing noise and computational demands by eliminating disturbing components orthogonal to the desired signal, allowing for unobtrusive and efficient extraction of vital signals like respiration rates under varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dimensional reduction techniques are applied to align characteristic index elements with reference motion direction, then signal quality and noise reduction are improved, but computational complexity increases
Solution Approach 1:
The patent applies dimensional reduction by projecting 2D image frame data onto a 1D reference motion direction vector. This transforms the problem from analyzing full 2D spatial data to analyzing 1D projection data along the motion direction, reducing computational complexity while preserving vital signal information.
Solution Approach 2:
The patent extracts only the characteristic index elements that are aligned with the reference motion direction from the full image data. By taking out and processing only the relevant directional components, the system reduces computational load while maintaining measurement precision for vital signs.
2Measurement precision
If advanced signal processing methods are used to extract vital signals from noisy data, then measurement precision improves, but processing time increases
Solution Approach 1:
The patent performs preliminary dimensional reduction by projecting image data onto the reference motion direction before detailed signal analysis. This preprocessing step simplifies the data structure in advance, making subsequent signal extraction faster and more efficient while maintaining accuracy.
Solution Approach 2:
The patent segments the image data processing into distinct stages: first projecting onto reference directions to extract characteristic index elements, then analyzing these elements for vital signals. This segmentation allows efficient processing at each stage rather than attempting complex analysis on the full data set.
3Ease of operation
If unobtrusive remote monitoring is implemented, then ease of operation improves, but signal-to-noise ratio deteriorates
Solution Approach 1:
The patent focuses analysis on local directional components along the reference motion direction rather than processing the entire image uniformly. By concentrating computational resources on the specific directional region where vital signals appear, the system maintains high signal-to-noise ratio ratios while using simple unobtrusive remote monitoring.
Data Source
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AI summary
The present invention relates to a device and a method for extracting information from detected characteristic signals. A data stream (26) derivable from electromagnetic radiation (20) emitted or reflected by an object (10) is received. The data stream (26) comprises a continuous or discrete characteristic signal (68) including physiological information (30) indicative of desired object motion to be detected and utilized so as to extract at least one at least partially periodic vital signal of interest. A plurality of characteristic index elements (60) can be derived from the data stream (26) through a dimensional reduction (66). The plurality of characteristic index elements (60) comprises a directional motion component (70) associated with a disturbance-reduced index element (40) having a determined orientation substantially aligned with a reference motion direction (41) indicative of the desired object motion. Consequently, dimensional reduced data can be utilized for detecting the vital signal of interest.