Transforming any smartphone, tablet, or laptop into a video-based medical-grade sensor without wearables.
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Immersively.care uses machine learning algorithms to detect regions of interest in your face where light reflections are the most relevant to compute health data. Ambient light penetrates the skin and reflects off blood vessels in the skin of your face back to your computer's camera during a video call.
Immersively.care uses computer vision algorithms to compute the variance of red, green, and blue light reflection changes from the skin of the face. Noises due to poor light conditions and head movements are filtered using signal processing techniques.
Because light reflection varies by blood volume changes, peak values correspond to heartbeats. Immersively.care uses those peaks to compute inter-beat intervals. The elapsed time between two consecutive peaks is a direct measure of heart rate in real-time.
Immersively.care estimates wellbeing using heart rate variability, which is literally the variance in time between the beats of your heart over a period. This metric offers a noninvasive way to signal imbalances or states of the resilience of your autonomic nervous system in real time. If the system is in a more relaxed state, the variation between beats may be higher.
Immersively.care implements the Baevsky Stress Index to calculate users’ stress levels using inter-beat intervals.
We also apply advanced mathematical transformations and deep learning on the amplitude of light reflection on the human face to estimate blood pressure, oxygen saturation, and breathing rate.
"Immersively.care's application of facial video-based frameworks to estimate physiological data using Remote Photoplethysmography is a revolution in the field of virtual meetings. I tested it with my Smart Watch on my wrist. Give it a try!"
"I was quite skeptical at the beginning, because of the lack of scientific consensus on the definition of emotions. Immersively.care found a way to ethically offer emotions as an additional language of communication during a video call. Great job!"
"I like how the technology doesn't try to read people's minds but instead seeks to copy the human action of looking at someone's face to guess how they're feeling. This extra context can be helpful during a remote call"
DigIntu Tech Ltd
Hermanova 61
17000 Prague
Czech Republic
EU VAT-ID CZ05233518
Registered in Commercial Register with the Municipal Court in Prague, section C, folder 260406.
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Virtual backgrounds
Stress level tracking
Blood pressure tracking
Oxygen level tracking
Breathing rate tracking