The core principle of the integrated heart rate monitoring function of sunglasses is mainly based on photovolumetric pulse wave tracing (PPG), and its technical implementation relies on the synergistic effect of optical sensors and algorithm processing. The following is the specific principle analysis:
First, signal acquisition by optical sensors
Light source emission
The miniature LED light source (usually green light) built into the sunglasses continuously illuminates the skin surface. After the light penetrates the skin tissue, part of it is absorbed by static tissues such as veins and muscles. Meanwhile, due to the periodic dilation and contraction of arteries, the amount of light absorbed varies with the blood flow.
Photoelectric signal reception
The reflected or transmitted light is received by photosensitive sensors (such as photodiodes) and converted into electrical signals. Due to the pulsation of arterial blood flow, the received light intensity signals show periodic fluctuations, forming PPG signals.
Second, signal processing and heart rate calculation
Noise filtering
The original PPG signal contains noises such as ambient light interference and motion artifacts, and the effective pulse components need to be extracted through digital filtering algorithms (such as bandpass filtering).
Feature extraction
The peak detection algorithm is used to identify the peaks of the PPG signal (corresponding to the cardiac systolic period), and the number of peaks within a unit of time can be counted to calculate the heart rate (unit: times per minute). Some systems may combine frequency-domain analysis (such as FFT) to verify the accuracy of the results.
Third, technical challenges and optimization directions
Motion artifact suppression
Head movement or limb shaking can cause unstable contact between the sensor and the skin, introducing noise. The anti-interference ability can be enhanced through multi-sensor fusion (such as accelerometer assistance) or adaptive filtering algorithms.
Ambient light adaptability
In a strong light environment, external light may overwhelm the PPG signal. Adopting a shading structure design or dynamically adjusting the intensity of the light source can optimize the signal quality.
Individual difference adaptation
Factors such as skin color and subcutaneous fat thickness affect the degree of optical signal attenuation, and parameters for different populations need to be calibrated through machine learning algorithms.
Fourth, application scenarios and limitations
Advantages of real-time monitoring
The non-invasive design is suitable for sports, outdoor and other scenarios. Users can obtain heart rate data at any time to assist in adjusting the intensity of exercise.
Precision limitation
Limited by the sensor size and wearing position, its accuracy is usually lower than that of medical-grade devices (such as ECG chest straps), and the error range may be within ±3 to 5 bpm.
Potential for functional expansion
Combined with blood oxygen sensors or skin electrical response modules, health management functions such as pressure monitoring and fatigue early warning can be further achieved.
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