Pulse Wave Detection via YIQ Color Space Brightness Correction
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Solution Overview
Problem
Existing pulse wave detection technologies face challenges in robustness against changes in brightness, particularly in practical scenarios such as vehicle environments, where variations in lighting conditions complicate non-contact pulse wave detection.
Innovation Solution
A pulse wave detection device and program that utilize color space components like YIQ and HSV to isolate and correct for brightness changes by distinguishing between skin and non-skin areas, employing eye portion analysis for brightness correction and skin portion analysis for pulse wave extraction, ensuring robustness against environmental disturbances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional pulse wave detection methods are used in practical environments, then detection can be performed, but brightness changes become disturbance elements that make pulse detection difficult
Solution Approach 1:
The invention segments the face image into multiple regions (skin regions and non-skin regions) and processes them differently. By separating the analysis of skin regions and non-skin regions, the method can extract brightness change information from non-skin regions to compensate for illumination changes, while simultaneously extracting pulse wave information from skin regions, thus resolving the contradiction between detection reliability and brightness disturbance
Solution Approach 2:
The invention introduces non-skin regions as an intermediary element that captures pure brightness changes without pulse wave information. This intermediary serves as a reference to estimate and remove illumination changes from the skin region signals, enabling accurate pulse wave detection despite brightness variations
2Measurement precision
If the entire face region is used for pulse wave detection, then more signal data is obtained, but non-skin areas introduce noise that reduces detection accuracy
Solution Approach 1:
The invention divides the face into skin and non-skin segments, analyzing each segment's characteristics separately. This segmentation allows the system to exclude noise from non-skin areas while preserving useful signal information from skin areas, thereby improving measurement precision without losing valuable data
Solution Approach 2:
The invention applies different processing strategies to different local regions: skin regions are processed to extract pulse wave information while non-skin regions are processed to estimate brightness changes. This local quality approach ensures that each region contributes its specific useful information while minimizing its harmful characteristics
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables accurate and robust pulse wave detection even in varying brightness conditions, improving detection accuracy and reliability by isolating the skin area and correcting for brightness fluctuations, thus facilitating real-time monitoring of physiological conditions.
Implementation Method 1
an optical distance that the sunlight is transmitted through the skin is changed, and it appears as a change in reflected light from the face
Implementation Method 2
a web camera... detecting a pulse wave by taking a moving image of the face
Data Source
AI summary
A pulse wave detection device color converts a frame image of a moving image from RBG components to YIQ components, and identifies an eye section using the eye color of a user prepared in advance with a Q component. Next, the pulse wave detection device uses the Y values of the eye section to detect the brightness of the imaging environment. Then, the pulse wave detection device detects a pulse wave signal Qm on the basis of the average of the Q-values of a skin section in the frame image, corrects a change in the brightness by subtracting from Qm the average value Ye of the Y values of the eye section, and thereby outputs a post-brightness-correction Qm. As a result, a pulse wave can be successfully detected even if the brightness is changing because the user is moving in a vehicle or the like.