  This work represents the experimental and development process of system
facial expression recognition and facial stress analysis algorithms for an
immersive digital learning platform. The system retrieves from users web camera
and evaluates it using artificial neural network (ANN) algorithms. The ANN
output signals can be used to score and improve the learning process. Adapting
an ANN to a new system can require a significant implementation effort or the
need to repeat the ANN training. There are also limitations related to the
minimum hardware required to run an ANN. To overpass these constraints, some
possible implementations of facial expression recognition and facial stress
analysis algorithms in real-time systems are presented. The implementation of
the new solution has made it possible to improve the accuracy in the
recognition of facial expressions and also to increase their response speed.
Experimental results showed that using the developed algorithms allow to detect
the heart rate with better rate in comparison with social equipment.
