A UNIQUE MIX OF

Signal Processing
and AI Technologies

Artificial Intelligence
Technologies
Proprietary
Mathematical
Backend
Signal
Processing
Signal
Processing

How Our Technology Works

Video Capture

The user starts the app and looks at the camera-equipped device.

1

Video Capture

The user starts the app and looks at the camera-equipped device.

2

Face Detection

AI technology accurately identifies the presence of a human face.

Face Tracking

Deep learning technology is used to focus on the subject's face.

3

Face Tracking

Deep learning technology is used to focus on the subject's face.

4

Skin Region Selection

It dynamically decides which part of the face to analyze and extracts signals.

Motion Compensation

Signal processing compensate for any motion to achieve consistent results.

5

Motion Compensation

Signal processing compensate for any motion to achieve consistent results.

6

Illumination Normalization

Light levels are normalized to improve accuracy further.

How Do We Extract Vital Signs?

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.

Non-contact Video-based rPPG

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.

Contact-based PPG

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.

Mental Stress

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.

Proven Performance
and Medical-grade Accuracy

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%.

Ready to give it a try?

We offer easy integration for iOS, Android and Windows via our SDK, or a white-labeled end-to-end application platform.