F1 Room

Human Sensory Perception and Action

F1 establishes empirical foundations for principles of expectancy and situation guided multisensory perception and action to advance digital technologies for users of different ages and skill levels.

Key Questions

A kinematic database will be built to train ML algorithms that anticipate grasping movements, focusing on complex and collaborative actions with multiple agents.

The influence of expectation and sensory congruence on the plausibility of compressed or replaced multimodal signals will be studied, extending haptic research to include smell and social touch.

The differences in neural signals related to age (such as 1/f noise) will be explored to assess their impact on human-machine communication.

Approach

  • Psychophysical studies on complex actions and collaboration with different age and ability groups.
  • Extension of research on smell and social-affective touch.
  • Analysis of age-related differences in digital communication.

Expected Results

  • Experimental paradigms and data from young adults.
  • Extension to other age groups and skill levels.
  • Linking age-related neuronal gain differences to noise effects in formal communication theories.