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Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Related Experiment Video

Updated: Jul 20, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
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Exploring crossmodal correspondences for future research in human movement augmentation.

Mattia Pinardi1, Nicola Di Stefano2, Giovanni Di Pino1

  • 1NeXT Lab, Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico di Roma, Rome, Italy.

Frontiers in Psychology
|July 3, 2023
PubMed
Summary

Crossmodal correspondences, consistent sensory mappings, can enhance human augmentation by improving device control. This research explores their potential to aid in integrating information and reducing cognitive load for users of artificial devices.

Keywords:
augmentationcrossmodal correspondenceembodimentmultisensory integrationsensory feedback

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Area of Science:

  • Cognitive Psychology
  • Human-Computer Interaction
  • Neuroscience

Background:

  • Crossmodal correspondences are consistent links between different sensory domains.
  • Human augmentation aims to enhance motor abilities with artificial devices.
  • Effective control of augmented systems requires seamless information relay to users.

Purpose of the Study:

  • To explore the potential of crossmodal correspondences in human augmentation.
  • To identify how crossmodal correspondences can improve device control and user experience.
  • To assess the feasibility of leveraging these correspondences in augmented systems.

Main Methods:

  • Literature review of crossmodal correspondence research.
  • Analysis of multisensory integration principles.
  • Perspective on applying crossmodal correspondences to human augmentation challenges.

Main Results:

  • Crossmodal correspondences may facilitate sensory information integration for better motor control.
  • These correspondences can potentially reduce cognitive load and adaptation time for augmented systems.
  • Maintaining these benefits through sensory substitution is crucial for effective implementation.

Conclusions:

  • Crossmodal correspondences offer a promising avenue for enhancing human augmentation systems.
  • Exploiting these natural sensory links can lead to more intuitive and effective human-device interaction.
  • Further research is needed to fully realize the potential of crossmodal correspondences in this field.