**5.1 Data capturing**

All the sensors are connected via the USB 3 interface to the acquisition computer, which allows capturing the color and depth frames with a 30 fps frame rate at Full HD spatial resolution. The system for the capturing and data processing is designed as GUI running as a web application. The server application is created using Python. This application acquires the depth and RGB color image frames from all sensors and streams the image data to user interface. The RealSense SDK tool is used for controlling the sensors, flask for server operation, and OpenCV framework for image processing. Image acquisition and streaming of the image data run in separated threads. The data flow is reduced due to JPEG encoding of images (depth and also RGB). When the server application receives a request for saving from the user interface, the saving procedure is triggered. Acquired images are stored locally in a temporary folder. When image acquisition process is finalized, the content of the temporary folder is zipped, encrypted, and named by patient identifier and actual time. The script then copies the ZIP to external server storage to collect and backup the data. When the external server is not accessible, the file is queued and sent in the next time [35].
