The user starts the app and looks at the camera-equipped device.
The user starts the app and looks at the camera-equipped device.
AI technology accurately identifies the presence of a human face.
Deep learning technology is used to focus on the subject's face.
Deep learning technology is used to focus on the subject's face.
It dynamically decides which part of the face to analyze and extracts signals.
Signal processing compensate for any motion to achieve consistent results.
Signal processing compensate for any motion to achieve consistent results.
Light levels are normalized to improve accuracy further.
Binah.ai extracts vital signs using a video taken of the upper cheek region of the face, and analyzes this with advanced AI and deep learning algorithms, including computer vision technology and signal processing. No video of the eyes or any other identifiable features are needed, and the subject does not need to remove glasses, a hat, beard, make-up or a mask. In 2 minutes or less, users have access to Heart rate, Heart Rate Variability, Oxygen Saturation, Respiration Rate and Mental Stress.
Remote Photoplethysmographic imaging (rPPG) is a camera-based solution for non-contact cardiovascular monitoring, proven to be as accurate as traditional PPG devices. Our technology measures the changes in red, green, and blue light reflection from the skin, quantifying the contrast between specular reflection and diffused reflection.
When conditions are not ideal, Binah.ai also implemented a backup solution that extracts a PPG signal by placing the user’s finger on the back camera of a smartphone. Binah.ai automatically detects when conditions are not ideal for rPPG contact-less extraction and moves to the finger-based extraction.
Via accurate HRV (Heart-rate variability) measurements, Binah.ai uses Baevsky’s mental stress index as well as US/European approved index measurements to calculate patient stress levels. With this insight, we provide easy to read stress measurements on a 5 point scale: low, normal, mild, high, and extremely high.
The Binai.ai solution undergoes continuous testing, both in our own in-house labs, and externally via clinical trials in medical labs and academic institutions. Our advanced signal processing allows for clean data with a high level of accuracy, eliminating outlying information and providing a higher signal-to-noise ratio. As a result, we consistently receive a high-level of accuracy against medical-grade equipment, between 95%-98%.
We offer easy integration for iOS, Android and Windows via our SDK, or a white-labeled end-to-end application platform.
