It uses image processing technology to detect subtle changes in skin color according to blood flow with smartphone camera.
It extracts heart rate signals through biometric processing algorithms, using detected signals.
It measures the movement of heart rhythm with inertial sensors, and extracts the heart rate.
It measures skin color changes according to blood flow with a camera and extracts photo-plethysmography signals.
Through two extracted signals, the blood flow rate is calculated.
It learns blood flow rate, photo-plethysmography characteristics and personal information (age, height, weight, gender, etc.) through deep learning, and estimates blood pressure.
It measures photo-plethysmography signal from the camera.
It estimates the heart rate variation of 1 to 3 minutes and calculates the autonomic nervous system activity index.
It measures the signal within 10 to 20 seconds of the inertia sensor
It estimates the exact displacement angle using a Kalman filter.
It uses signal processing technology to estimate the breathing signal through noise rejection by non-breathing motion and frequency analysis.