This product is a novel risk assessment tool for carotid artery stenosis and stroke. This is a revolutionary healthcare technology using motion analysis and quantification to extract information from pulses for risk assessments. The entire process is completed by taking a short video clip aimed at the neck with only one simple click on any mobile devices or our apparatus, anywhere, anytime. In less than five minutes, the user receives an evaluation report indicating low to high stroke risk. Our product accuracy stands higher than 90% when compared to the clinical outcome. The future indications of this product can be extended to arrhythmia, venous fistula obstruction, etc. This product has the great potential to achieve our dream of “personalized mobile hospital” in the future world.

The principle of the image-based AFib discriminating system is based on the consistency that irregular cardiac cycles can both be detected on the waveforms of electrocardiographyrPPG. The quantity of the blood varies from time to time is captured by a general camera. Signals from RGB channels are then synthesized through the core algorithm to eliminate noisegenerate stable rPPG signals. The processed signals are then classified as AFibnot by a sample-size model. According to the IRB evaluation in En Chu Kong Hospital, the AFib can be well detected with an accuracy of 97.1.