Optical Heart Rate Detection with Bayesian Motion Filtering
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Solution Overview
Problem
Current heart rate monitoring methods are invasive, cumbersome, or lack accuracy, particularly during physical activity, as they often require direct contact with the skin or rely on single illumination sources, leading to noise interference and delayed feedback.
Innovation Solution
A non-invasive optical-electronic device that uses spatially-resolved near-infrared spectroscopy with multiple light emitters and detectors to combine optical signals from different wavelengths, processed with Bayesian filters and adaptive noise cancellation, to accurately estimate heart rate in real-time, while accounting for motion artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single illumination source is used for optical heart rate monitoring, then device complexity is reduced, but measurement precision deteriorates due to noise interference
Solution Approach 1:
The patent combines multiple illumination sources emitting at different wavelengths (e.g., 660nm and 940nm LEDs) to create a multi-wavelength optical system. This merging of multiple light sources allows the system to penetrate different tissue depths and reduce noise interference, thereby improving measurement precision while maintaining manageable device complexity through integrated circuit design.
Solution Approach 2:
The patent employs a composite optical system that integrates multiple light sources with different spectral characteristics. By combining illumination sources with distinct wavelengths, the system creates a composite measurement approach that captures both superficial and deep tissue signals, enhancing measurement precision without proportionally increasing device complexity.
2Ease of operation
If non-invasive optical monitoring is used, then ease of operation is improved, but measurement precision deteriorates due to motion artifacts and noise
Solution Approach 1:
The patent implements feedback mechanisms where the optical detection system continuously monitors tissue signals and uses processing algorithms to distinguish between motion artifacts and actual physiological signals. The system provides real-time feedback processing that adjusts for motion interference, maintaining measurement precision while preserving the ease of non-invasive operation.
Solution Approach 2:
The patent introduces signal processing algorithms and computational methods as intermediaries between the optical sensors and the final heart rate measurement. These intermediary processing steps filter out motion artifacts and noise, allowing the system to maintain high measurement precision while keeping the operation simple and non-invasive for the user.
3Productivity
If real-time heart rate monitoring is implemented, then productivity is improved, but measurement precision deteriorates due to delayed feedback in traditional methods
Solution Approach 1:
The patent employs preliminary action by using multiple illumination sources to pre-penetrate different tissue depths simultaneously, capturing physiological signals before motion artifacts can interfere. This preliminary multi-wavelength illumination establishes a baseline that enhances real-time measurement precision while maintaining high productivity through immediate data processing.
Solution Approach 2:
The patent ensures continuity of useful action by implementing continuous multi-wavelength optical monitoring with real-time signal processing. The system maintains uninterrupted measurement of physiological parameters, improving productivity through continuous data streams while preserving measurement precision through ongoing noise filtering and artifact rejection algorithms.
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 device provides more accurate and real-time heart rate monitoring with reduced noise interference, allowing for precise tracking of physiological changes during exercise and other physical conditions, enhancing athlete performance assessment.
Implementation Method 1
spatially-resolved near-infrared spectroscopy with multiple light emitters and detectors
Implementation Method 2
emitting light from a plurality of light emitters into a tissue and receiving a plurality of detected light signals from the tissue
Implementation Method 3
receiving a motion signal from a gyroscope or accelerometer
Data Source
AI summary
Provided herein are methods and devices configured to detect the heart rate of a user. The method includes receiving at least one input signal, separating the input signal into signal components, receiving a motion signal from the user, and applying a Bayesian filter to the signal components and the motion signal to estimate the heart rate of the user. The method further includes calculating a combination of at least two reflected light signals from at least two different wavelengths. The device includes a photodetector configured to detect at least one reflected light signal resulting from the emitted at least two different wavelengths and a motion detector for detecting a motion signal. The device also includes a processing component configured to calculate a combination of the reflected light signals, separate the combination of detected light signals into signal components, and apply a Bayesian filter to the signals.