Camera-Based Heart Rate Tracking via Optical Blood Flow Analysis
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Solution Overview
Problem
Conventional methods for measuring heart rate are invasive, expensive, and lack accuracy, with non-invasive methods being susceptible to noise and providing limited detail.
Innovation Solution
A camera-based system using machine learning to track heart rate by analyzing hemoglobin concentration changes in image sequences, applying band-pass filters, and performing Hilbert transforms to determine instantaneous heart rates, which are then averaged for accurate BPM measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional electrocardiogram equipment is used to measure heart rate, then measurement accuracy is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces the mechanical/electrical ECG system with an optical camera-based system. Instead of using electrodes to detect electrical signals from the heart, the invention uses a standard camera to capture optical variations in skin color caused by blood flow changes, thereby substituting a complex medical device with a simple optical sensor.
Solution Approach 2:
The patent creates an optical copy of the physiological signal. By capturing video images of the skin and analyzing color variations in the red and green channels, the system generates a photoplethysmogram (PPG) signal that replicates the information from traditional sensors without requiring physical contact or specialized equipment.
2Measurement precision
If invasive electrodes are placed on the skin to measure heart rate, then measurement accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system allows the subject to serve themselves by simply being filmed. The camera captures passive optical changes in the skin without requiring the subject to attach any devices, prepare the skin, or follow complex procedures. The subject remains completely passive while the system automatically extracts heart rate information from video images.
3Ease of operation
If strapless wearable devices with infrared sensors are used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent extracts the useful signal from the video data by selectively processing specific color channels (red and green) and specific bitplanes. By isolating the relevant optical information that correlates with blood flow changes and discarding irrelevant data, the system achieves high measurement accuracy using a simple camera without specialized sensors.
4Ease of operation
If conventional heart rate monitors are used, then ease of operation is improved, but reliability deteriorates due to noise susceptibility
Solution Approach 1:
The patent segments the video signal into multiple bitplanes and processes each bitplane separately to identify those containing the most useful physiological information. By dividing the signal processing into discrete components and selecting only the relevant segments, the system achieves noise resistance while maintaining ease of operation.
Solution Approach 2:
The patent introduces an intermediary processing stage that converts raw video data into a photoplethysmogram signal through color channel analysis and bitplane selection. This intermediary representation serves as a robust bridge between the simple camera input and the final heart rate measurement, filtering out noise while preserving the essential physiological information.
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 system provides a robust and accurate heart rate measurement, resistant to noise interference, with BPM estimates consistent within +/-2 BPM of electrocardiogram data, and capable of continuous updates at video frame rates.
Implementation Method 1
receiving a captured image sequence of light re-emitted from the skin of the human subject
Implementation Method 2
applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals
Implementation Method 3
applying a Hilbert transform to each of the blood flow data signals
Data Source
AI summary
A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.