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Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds
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User identification using gait patterns on UbiFloorII.

Jaeseok Yun1

  • 1U-embedded Convergence Research Center, Korea Electronics Technology Institute, 68 Yatap-dong Bundang-gu, Seongnam, Korea. jaeseok@keti.re.kr

Sensors (Basel, Switzerland)
|December 14, 2011
PubMed
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This study introduces a novel gait recognition system for identifying individuals in domestic settings. The system accurately distinguishes users by analyzing walking and stepping patterns captured by the UbiFloorII biometric sensor.

Area of Science:

  • Biometrics
  • Human-Computer Interaction
  • Pattern Recognition

Background:

  • Gait analysis offers a unique biometric identifier.
  • Current biometric systems often require active user participation.
  • Unobtrusive identification methods are crucial for ubiquitous computing.

Purpose of the Study:

  • To develop and evaluate a gait recognition system for domestic environments.
  • To explore the effectiveness of distinguishing between walking and stepping patterns.
  • To assess the feasibility of using the UbiFloorII sensor for user identification.

Main Methods:

  • Utilized the UbiFloorII biometric sensor to collect gait data.
  • Extracted distinguishable gait features, categorized into walking and stepping patterns.
Keywords:
UbiFloorIIgait recognitionstepping patternuser identificationwalking pattern

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  • Employed a multilayer perceptron neural network for user classification.
  • Investigated fusing classifiers at the matching score level.

    • Main Results:

    • Gait patterns (walking and stepping) collected by UbiFloorII were found to be sufficiently distinguishable for user identification.
    • Fusing classifiers significantly improved recognition accuracy.
    • The system demonstrated effectiveness under assumed domestic conditions with fewer than 10 users.

    Conclusions:

    • The proposed system provides an unobtrusive and automatic method for user identification in domestic settings.
    • Gait recognition using the UbiFloorII sensor is a viable biometric solution.
    • The fusion of multiple classifiers enhances the robustness of gait-based identification systems.