We use features such as asymmetric expression and crooked eyes to assess the risk of facial stroke. Observing the micro vibration of the head caused by the contraction of the heart, and develop a zero-contact facial heart rate and respiration rate detection technology in conjunction with the camera. The technology can accurately measure heart rate and respiration rate in real time, thereby reducing the risk of infection. This technology has obtained two ROC patents (M590433, I689285), two US patents (HEART RATE DETECTION METHOD AND DEVICE THEREOF,MOUTH AND NOSE OCCLUDED DETECTING METHOD AND SYSTEM THEREOF). The possibility of detecting strokes through AI machine learning methods is not only accurate, but also find out signs of stroke early to grasp the best time to seek medical treatment.

The proposed "zero-contact" detection technology combines face stroke, heart rate, and respiration detection. Through observing the symmetry of facial features of subjects' faces to estimate the risk of stroke. And observing the micro-vibration caused by the heartbeat and breathing to estimate the subject's heart rate and breathing rate. Compared with the facial skin color method, this technology can overcome the influence of ambient light and accurately detect heart rate and respiration rate. This technology can be practically applied to negative pressure isolation wards, postpartum confinement centers, and homes.

This technology is the world's first "zero- contact " detection technology, which can estimate the risk of facial stroke and measure heart rate and breathing rate at the same time. This technology has obtained 4 patents (2 US patents, 2 ROC patents). The technology can achieve real-time measurement to reduce the risk of infection of medical staff. This technology can be integrated into systems or devices such as physiological signal measurement systems, baby monitors, and magic mirrors, and is actually used in hospital negative pressure isolation wards, postpartum confinement centers, and homes.