Affective Computing Demonstrators

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.

Prosody Analysis
Analysis of speech features such as intonation, rhythm, and articulation to detect emotional states and cognitive load
Macro Motion Analysis
Evaluation of gross body movements and posture dynamics to identify behavioral markers of stress, distraction, or fatigue
Micro Motion Analysis
Detection of subtle facial expressions, micro-expressions, and fine-grained motion patterns that reveal affective and cognitive states
Peripheral & Central Physiological Biosignals
Integration of EEG, ECG, EDA, PPG and other biosignals to capture both peripheral responses and central neural activity for a comprehensive psychophysiological profile

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