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Neural Computing and Applications

, Volume 26, Issue 7, pp 1621–1629 | Cite as

Use of the image and depth sensors of the Microsoft Kinect for the detection of gait disorders

  • Aleš ProcházkaEmail author
  • Oldřich Vyšata
  • Martin Vališ
  • Ondřej Ťupa
  • Martin Schätz
  • Vladimír Mařík
Original Article

Abstract

This paper presents a novel method of gait recognition that uses the image and depth sensors of the Microsoft (MS) Kinect to track the skeleton of a moving body and allows for simple human–machine interaction. While video sequences acquired by complex camera systems enable very precise data analyses and motion detection, much simpler technical devices can be used to analyze video frames with sufficient accuracy in many cases. The experimental part of this paper is devoted to gait data acquisition from 18 individuals with Parkinson’s disease and 18 healthy age-matched controls via the proposed MS Kinect graphical user interface. The methods designed for video frame data processing include the selection of gait segments and data filtering for the estimation of chosen gait characteristics. The proposed computational algorithms for the processing of the matrices acquired by the image and depth sensors were then used for spatial modeling of the moving bodies and the estimation of selected gait features. Normalized mean stride lengths were evaluated for the individuals with Parkinson’s disease and those in the control group and were determined to be 0.38 and 0.53 m, respectively. These mean stride lengths were then used as features for classification. The achieved accuracy was >90 %, which suggests the potential of the use of the image and depth sensors of the MS Kinect for these applications. Further potential increases in classification accuracy via additional biosensors and body features are also discussed.

Keywords

Image and depth sensors Gait disorders Motion features MS Kinect Video processing Parkinson’s disease 

Notes

Acknowledgments

Authors would like to thank all patients who signed the informed consent to participate in the project with all the procedures approved by the local ethics committee as stipulated by the Helsinki Declaration. All data were kindly provided by the Movement Disorders Center of the Faculty Hospital in Hradec Králové, Czech Republic.

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Copyright information

© The Natural Computing Applications Forum 2015

Authors and Affiliations

  • Aleš Procházka
    • 1
    • 3
    Email author
  • Oldřich Vyšata
    • 2
  • Martin Vališ
    • 2
  • Ondřej Ťupa
    • 1
  • Martin Schätz
    • 1
  • Vladimír Mařík
    • 3
  1. 1.Department of Computing and Control EngineeringInstitute of Chemical Technology in PraguePrague 6Czech Republic
  2. 2.Department of Neurology, Faculty of Medicine in Hradec KrálovéCharles University in PragueHradec KrálovéCzech Republic
  3. 3.Czech Institute of Informatics, Robotics and CyberneticsCzech Technical University in PraguePrague 6Czech Republic

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