Improved Usability of Locomotion Devices Using Human-Centric Taxonomy

Abstract

This thesis investigates how early taxonomies of locomotion fail to provide a comprehensive enough framework to facilitate usable locomotion devices due to a failure of understanding the human component in interaction. It then proposes an alternative human-centric taxonomy for locomotion that grounds itself on the physiological, physical and extra-physical cues the human body is capable of providing rather than only the input existing interaction devices are capable of receiving. Through the realization that interaction begins with the human, not the machine, this thesis is able to determine a cue from the body that is able to provide enough information for use by an algorithm to recognize walking and running forward, sidestepping, back stepping, and jumping with a minimal amount of sensors and associated hardware. This thesis then develops and performs initial tests on a fully implemented locomotion device using input from two inertial sensors on the legs in conjunction with the locomotion recognition algorithm for use in any commercial-off-the-shelf (COTS) video game for PCs that use keypresses for locomotion input.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA496741

Entities

People

  • Alex T. Mabini

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Cognition
  • Cognitive Systems Engineering
  • Computers
  • Energy Conversion
  • Human Body
  • Human Factors Engineering
  • Human-Computer Interaction
  • Musculoskeletal System
  • Psychology
  • Task Performance And Analysis
  • Taxonomy
  • Three Dimensional
  • United States Naval Academy
  • Video
  • Video Games
  • Virtual Reality

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Robotics and Automation.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.