Affective Computing

Affective Computing: Enabling Emotional Intelligence in Machines

Emotions play a fundamental role in human cognition, perception, decision-making, and learning – significantly influencing the core processes underlying rational thought.

To develop intelligent computers capable of natural interaction with humans, it is essential to teach machines how to recognize, understand, experience, and express emotions. Affective computing – also known as emotional computing – is the scientific field dedicated to creating emotionally aware technologies that can automatically analyze affective and expressive behaviors.

A key objective within affective computing is the quantification of expressive behaviors – such as facial muscle activations and speech patterns – to detect mood disorders like depression and enhance human–machine communication.

Facial Landmarks Recognition
Detect and learn facial expressions or movements to recognize specific patterns of mental and physical level
Mental Workload Measurement
Measurement of mental and physiological workload of subjects when performing different tasks
Socio-Emotional Training
Develop and design the learning exercise to enhance socio-emotional competencies and practical skills
Psychological & Cognitive Assessment
Identify and evaluate future success rate based on collective performance data

Successful Projects