Science drives everything we do
Shen AI is grounded in solid scientific principles, collaborating with leading experts and continuously pushing technology to its limits.
Shen is clinically validated
Our technology prioritizes accuracy and stability, ensuring reliable performance. Rigorous clinical validation studies have been conducted to prepare Shen AI for medical device certification. With the highest level of accuracy, Shen AI sets a new standard in the industry.
Our technology leverages the latest AI advancements
Shen AI is built on a strong scientific foundation, collaborating with leading researchers and continually pushing the boundaries of technology.
Highest accuracy
Shen AI is built on strong science foundations, working closely with numerous scientists and constantly pushing technology to its limits.
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Shen works based on multimodal approach
Remote Photoplethysmography
Shen AI utilizes remote photoplethysmography (rPPG) to extract vital health data from a simple video recording. By analyzing subtle color changes in the skin caused by blood flow, Shen AI can measure heart rate, respiratory rate, and other key vitals—all without the need for physical sensors. This AI-driven technology ensures accurate, contactless health monitoring, making it easy for users to check their health anytime, anywhere, using just their device’s camera.
Remote Ballistocardiography
Shen AI leverages remote Ballistocardiography (rBCG) to analyze tiny face movements caused by the heart’s mechanical activity. Using a device’s camera, rBCG detects subtle vibrations and micro-motions to estimate heart rate, cardiac output, and other vital parameters without physical contact. This advanced AI-driven approach enables seamless, non-invasive heart health monitoring, making it accessible anytime, anywhere.
It’s built on the latest scientific discoveries
Every feature and metric we offer is backed by science.
Estimating heart rate variability using facial video photoplethysmography: a pilot validation study
Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques
Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network
A healthy heart is not a metronome: an integrative review of the heart's anatomy and heart rate variability
Facial video photoplethysmography for measuring average and instantaneous heart rate: a pilot validation study
Collaborating with universities
Wroclaw Medical University
Wroclaw
SWPS University
Warsaw
University of California
San Diego
University of Tartu
Tallin