Haptic perception in interaction with other senses

  • Hannah B. Helbig
  • Marc O. Ernst


Human perception is inherently multisensory: we perceive the world simultaneously with multiple senses. While strolling the farmers market, for example, we might become aware of the presence of a delicious fruit by its characteristic smell. We might use our senses of vision and touch to identify the fruit by its typical size and shape and touch it to select only that one with the distinctive soft texture that signals ‘ripe’. When we take a bite of the fruit, we taste its characteristic flavour and hear a slight smacking sound which confirms that the fruit we perceive with our senses of vision, touch, audition, smell and taste is a ripe, delicious peach. That is, in the natural environment the information delivered by our sense of touch is combined with information gathered by each of the other senses to create a robust percept. Combining information from multiple systems is essential because no information-processing system, neither technical nor biological, is powerful enough to provide a precise and accurate sensory estimate under all conditions.


Haptic Feedback Multisensory Integration Haptic Perception Bayesian Decision Theory Optimal Fashion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Selected readings

  1. Calvert GA, Spence C, Stein BE (2004) The Handbook of Multisensory Processes. Cambridge, MA: The MIT PressGoogle Scholar
  2. Ernst MO (2005) A Bayesian view on multimodal cue integration. In: G Knoblich, M Grosjean, I Thornton, M Shiffrar (eds.): Human body perception from the inside out, chapter 6. New York, NY: Oxford University Press, 105–131Google Scholar
  3. Ernst MO, Bülthoff HH (2004) Merging the senses into a robust percept. Trends in Cognitive Sciences 8(4): 162–169PubMedCrossRefGoogle Scholar
  4. Mamassian P, Landy MS, Maloney LT (2002) Bayesian modeling of visual perception. In: RPN Rao, BA Olshausen, MS Lewicki (eds.): Probabilistic Models of the Brain: Perception and Neural Function. Cambridge, MA: MIT Press, 13–36Google Scholar
  5. Spence C, Driver J (2004) Crossmodal Space and Crossmodal Attention. New York, NY: Oxford University PressGoogle Scholar

Copyright information

© Birkhäuser Verlag 2008

Authors and Affiliations

  • Hannah B. Helbig
    • 1
  • Marc O. Ernst
    • 1
  1. 1.Max Planck Institute for Biological CyberneticsTübingenGermany

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