Pupillary Response Cardiac Parameter Detection via Vision
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Solution Overview
Problem
Current vital signal monitoring (VSM) technologies face challenges in measuring physiological signals like heart rate and brain activity without causing inconvenience, stress, or increasing costs, particularly due to the need for invasive and obstructive sensors, which restrict movement and are costly.
Innovation Solution
A non-invasive method using a vision-based system that captures pupil images to extract time-domain cardiac parameters by analyzing pupil size variation, allowing for the detection of heart rate and other cardiac parameters without physical restrictions or psychological pressure, utilizing a video capturing unit and computer architecture for processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are attached to the body to measure physiological signals, then measurement precision is improved, but ease of operation deteriorates due to inconvenience and stress to patients
Solution Approach 1:
The patent replaces mechanical sensor attachment with an optical imaging system. Instead of using physical sensors that contact the body, the system uses a camera to capture images of the body surface, processes these images to extract physiological signals. This substitution eliminates the need for physical contact, thereby maintaining measurement precision while significantly improving patient comfort and ease of operation.
2Measurement precision
If sensors are attached to the body to measure physiological signals, then measurement precision is improved, but device complexity increases due to attached sensor hardware
Solution Approach 1:
The patent replaces complex mechanical sensor hardware with a simpler optical imaging system. The system uses standard imaging devices to capture body surface images, then employs image processing algorithms to extract physiological information. This approach reduces device complexity by eliminating specialized sensor hardware while maintaining measurement capability through computational methods.
Solution Approach 2:
The patent creates a visual copy of the physiological phenomena by capturing body surface images that contain embedded physiological information. Instead of directly measuring physiological signals with sensors, the system captures optical images that serve as copies containing the desired information, which are then processed to extract cardiac and respiratory parameters. This copying approach simplifies the measurement system while preserving measurement accuracy.
3Measurement precision
If sensors are attached to the body to measure physiological signals, then measurement precision is improved, but loss of time increases due to sensor attachment and removal
Solution Approach 1:
The patent replaces time-consuming sensor attachment procedures with rapid optical imaging. The system captures physiological information through images that can be acquired instantly without physical contact. This eliminates the time required for sensor application and removal, significantly reducing loss of time while maintaining measurement precision through image-based physiological signal extraction.
4Ease of operation
If non-contact methods are used to measure physiological signals, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent creates detailed visual copies of physiological phenomena through high-resolution body surface imaging. The imaging system captures subtle variations in body surface characteristics that correspond to physiological signals. By processing these visual copies with specialized algorithms, the system achieves accurate detection of cardiac and respiratory parameters through non-contact methods, thereby maintaining measurement precision while improving ease of operation.
Solution Approach 2:
The patent transforms physiological information from one parameter domain to another by converting internal physiological signals into external optical patterns visible on the body surface. The system detects changes in body surface optical properties that correlate with cardiac and respiratory activities. This parameter transformation enables non-contact measurement while preserving measurement precision through the relationship between internal physiology and external optical manifestations.
Data Source
AI summary
Provided are a method and system for detecting time-domain cardiac information, the method comprising: obtaining moving images of a pupil from a subject; extracting a pupil size variation (PSV) from the moving images; calculating R-peak to R-peak intervals (RRIs) in a predetermined frequency range from the PSV; and obtaining at least one time-domain cardiac parameter by processing the RRIs.