Pupillary Variation Detection for Brain-Heart Connectivity
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Solution Overview
Problem
Current vital signal monitoring (VSM) technologies face challenges in measuring physiological signals like ECG and EEG due to inconvenience, cost, and movement restrictions, necessitating the development of non-invasive, non-obtrusive, and low-cost methods for detecting brain-heart connectivity.
Innovation Solution
A method and system that utilize pupil size variation (PSV) from moving images to detect brain-heart connectivity by extracting alpha powers at specific frequencies, using a video capturing unit and computer architecture for analysis, allowing for non-invasive and cost-effective monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are attached to the body to measure physiological signals like ECG and EEG, then measurement precision is improved, but ease of operation deteriorates due to inconvenience, stress, and movement restrictions
Solution Approach 1:
The patent replaces mechanical sensor attachment systems with an optical vision-based system. Instead of using ECG and EEG sensors that require physical contact with the body, the invention uses a camera to capture pupillary response images and processes these images to extract physiological information, thereby eliminating the mechanical intrusion while maintaining measurement capability
Solution Approach 2:
The patent creates an optical copy of physiological information through pupillary response imaging. Rather than directly measuring electrical signals from the body, the system captures visual information about pupil dynamics and uses this optical copy to infer physiological states, avoiding direct physical measurement that requires sensor attachment
2Measurement precision
If sensors are attached to the body for physiological signal measurement, 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 simple optical imaging system. Instead of requiring ECG electrodes, EEG caps, or other physiological sensors, the invention uses a standard camera to capture pupillary responses and processes the visual data to extract physiological information, dramatically simplifying the device architecture
Solution Approach 2:
The patent makes the imaging system universal by using a standard camera that can capture multiple types of physiological information through pupillary response analysis. The same optical system can potentially measure heart rate, respiratory rate, and other physiological parameters by analyzing different aspects of pupil dynamics, eliminating the need for specialized sensors for each measurement type
3Measurement precision
If sensors are attached to the body for physiological signal measurement, then measurement precision is improved, but cost increases due to sensor hardware expenses
Solution Approach 1:
The patent replaces expensive physiological sensors with inexpensive optical imaging equipment. Instead of using costly ECG and EEG sensor systems, the invention uses a standard camera to capture pupillary responses and processes these images to extract physiological information, significantly reducing hardware costs while maintaining measurement precision
Solution Approach 2:
The patent employs inexpensive, readily available camera hardware instead of expensive medical-grade sensors. The system uses standard imaging equipment that can be easily manufactured and distributed, making the technology accessible and cost-effective compared to traditional sensor-based physiological monitoring systems
Data Source
AI summary
Provided are a method and system for detecting information of brain-heart connectivity, the method comprising: obtaining moving images of a pupil and an electrocardiogram (ECG) signal from a subject; acquiring a pupil size variation (PSV) from the moving images by separating the moving images at a predetermined time range after R-peak of the ECG signal; extracting signals of a first period and a second period from the PSV; calculating alpha powers of the signals of the first and second periods at predetermined frequencies respectively.