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A calibration method for smartphone camera photophlethysmography.
Yinan Xuan1,2, Colin Barry1,2, Nick Antipa1
1Electrical and Computer Engineering, UC San Diego, La Jolla, CA, United States.
Frontiers in Digital Health
|December 11, 2023
Summary
Smartphone camera photoplethysmography (cPPG) offers non-invasive measurements. A new calibration method linearizes camera data, improving cPPG accuracy and device transferability for better health monitoring.
Area of Science:
- Biomedical Engineering
- Optical Sensing
Background:
- Smartphone camera photoplethysmography (cPPG) enables non-invasive physiological measurements.
- Default camera settings introduce non-linearities, hindering cPPG consistency and cross-device application.
Purpose of the Study:
- To identify key parameters affecting cPPG accuracy.
- To develop a calibration method for linearizing camera measurements.
- To enhance the consistency and transferability of cPPG across devices.
Main Methods:
- Identified tone mapping and sensor threshold as critical parameters.
- Developed a novel calibration technique to linearize camera data.
- Created a benchtop calibration system using a microcontroller and LEDs.
Main Results:
- Calibrated cPPG achieved 74% higher accuracy compared to default settings.
- The calibration method demonstrated effectiveness across different smartphone models.
- Cross-device calibration was successful for identical smartphone models.
Conclusions:
- A novel calibration method significantly improves cPPG accuracy and consistency.
- This approach enhances the scalability and transferability of smartphone-based health monitoring.
- Linearizing camera measurements is crucial for reliable cPPG applications.
