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  • Research Article
  • Open Access

Gait Recognition Using Wearable Motion Recording Sensors

EURASIP Journal on Advances in Signal Processing20092009:415817

  • Received: 1 October 2008
  • Accepted: 26 April 2009
  • Published:


This paper presents an alternative approach, where gait is collected by the sensors attached to the person's body. Such wearable sensors record motion (e.g. acceleration) of the body parts during walking. The recorded motion signals are then investigated for person recognition purposes. We analyzed acceleration signals from the foot, hip, pocket and arm. Applying various methods, the best EER obtained for foot-, pocket-, arm- and hip- based user authentication were 5%, 7%, 10% and 13%, respectively. Furthermore, we present the results of our analysis on security assessment of gait. Studying gait-based user authentication (in case of hip motion) under three attack scenarios, we revealed that a minimal effort mimicking does not help to improve the acceptance chances of impostors. However, impostors who know their closest person in the database or the genders of the users can be a threat to gait-based authentication. We also provide some new insights toward the uniqueness of gait in case of foot motion. In particular, we revealed the following: a sideway motion of the foot provides the most discrimination, compared to an up-down or forward-backward directions; and different segments of the gait cycle provide different level of discrimination.


  • User Authentication
  • Gait Cycle
  • Motion Record
  • Acceleration Signal
  • Publisher Note

Publisher note

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Authors’ Affiliations

Norwegian Information Security Laboratory, Gjøvik University College, P.O. Box 191, 2802 Gjøvik, Norway


© D. Gafurov and E. Snekkenes. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.