Video Vital Sign Detection With Skin-Tone Adaptive Camera Gain
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Solution Overview
Problem
Existing image-based vital sign detection technologies face challenges in optimizing camera settings for accurate and reliable determination of vital signs, particularly in varying light conditions and for diverse skin tones, leading to inefficiencies and reduced reliability.
Innovation Solution
An apparatus and method that adapt camera settings by determining specific gain values for color channels based on skin tone and environmental luminance, using detectors to identify relevant image areas, and adjusting gains to optimize image properties for vital sign detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If camera settings are optimized for visually realistic images, then image quality for human perception is improved, but accuracy of vital sign detection deteriorates
Solution Approach 1:
The patent applies parameter changes by modifying camera settings specifically for vital sign detection. The system adjusts color channel gains (R, G, B) and exposure time to enhance the visibility of physiological signals in the image data, rather than optimizing for general visual realism. This allows the camera to capture subtle color variations in skin tissue that correspond to pulse and respiratory rates, improving measurement precision while maintaining acceptable image quality.
2Measurement precision
If camera settings are adapted for specific skin tones, then detection accuracy for that skin tone is improved, but adaptability to diverse skin tones deteriorates
Solution Approach 1:
The patent applies local quality by processing different color channels (R, G, B) with different gain values tailored to specific skin tone characteristics. The system determines skin tone from the image data and applies customized gain adjustments to each color channel based on the detected skin tone, allowing optimal detection accuracy for each individual's skin tone while maintaining the ability to adapt to diverse skin tones through the same framework.
Solution Approach 2:
The system dynamically adjusts camera parameters including color channel gains and exposure time based on real-time analysis of the captured image data. This dynamic adaptation allows the camera settings to be optimized for each specific skin tone detected in the scene, enabling both high detection accuracy and broad adaptability to diverse skin tones through automated parameter adjustment.
3Reliability
If exposure time is increased to improve signal to noise ratio, then detection reliability is improved, but sensitivity to light variations deteriorates
Solution Approach 1:
The system dynamically adjusts exposure time based on the detected light conditions and skin tone characteristics. By automatically adapting the exposure time to each specific scenario, the system maintains high detection reliability while reducing sensitivity to light variations. The dynamic parameter adjustment allows the camera to optimize signal-to-noise ratio for each recording condition without manual intervention.
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
Improves the accuracy and reliability of vital sign detection by reducing sensitivity to light variations and enhancing image quality for diverse skin tones, facilitating efficient capture and processing.
Implementation Method 1
each color channel representing a digitization of an optical sensor signal from a color channel optical sensor
Data Source
AI summary
An apparatus estimates vital signs of a person from video images with color channels representing a digitization of optical sensor signals. A first detector (203) detects a first image area being a skin area of the person and a second detector (205) detect a second image area corresponding to a different area of the person than the first image area. A determiner (207) determines color channel distributions for pixels of the first image area. A processor (209) provides a skin tone indication and a reference processor (211) provides a reference color channel distribution property for the skin tone. A gain processor (213) determines gains for the optical sensor signals in dependence on a luminance property of the second image area and on a comparison of the reference distribution property and a property of the color channel distributions. A gain controller (215) accordingly controls gain values applied to the optical sensor signals and a vital sign determiner (217) estimates a vital sign property for the person from the images.