Solution
A Ready-to-Use
Vital Signs Monitoring
Solution for Organizations

remote Photoplethysmography (rPPG )based end-to-end framework Vitalism for remote measurement of vital signs in near real-time using only a face video captured in natural environment using a smartphone camera.

Vitalism Check <br><span class="smaller-title">A Ready-to-Use <br>Vital Signs Monitoring <br> Solution for Organizations</span>

rPPG pipeline

The following pipeline demonstrates an advanced video data processing that includes multiple techniques to extract a robust BVP signal.

Deep Learning Methods

We carried out measurements with deep learning methods using Pulse Rate Detection and UBFC-RPPG Datasets to compare our results, which is our main approach. We hope that deep learning will reduce error rates as a result of these measurements. DeepPyhs provides visualization of physiological information in videos using convolutional attention networks.The main purpose of PhysNet approach is using a Spatio-temporal network for rPPG signals from videos. Then it compares rPPG signals with Ground Truth ECG values

Data Sets Used IN VITALISM

Pulse Rate Detection Dataset PURE data set: consists of 10 persons (8 male, 2 female) that were recorded in 6 different setups.

UBFC :There are 42 videos in UBFC dataset. Each people about 1m away from the camera. 30fps with a resolution of 640x480.

We care about your users’ privacy

The application does not save images or input video streams used for measurement. Final measurement results are saved for historical purposes and user convenience. All results are secured, encrypted and accessible only by users and account admins with permission, which may be managed in account preferences.
Vitalism is fully committed to the privacy and security of our customers and users and operates in compliance with GDPR requirements.

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Solution A Ready-to-Use Vital Signs Monitoring Solution for Organizations