• DocumentCode
    1722098
  • Title

    A gait recognition system for rehabilitation based on wearable micro inertial measurement unit

  • Author

    Li, Zhi ; Zhang, Guanglie

  • Author_Institution
    Coll. of Comput. Sci. & Software Eng., Shenzhen Univ., Shenzhen, China
  • fYear
    2011
  • Firstpage
    1678
  • Lastpage
    1682
  • Abstract
    Gait recognition and analysis is one of the most important biometric methods for medical treatments, virtual reality games and human motion identification. Gait recognition based on wearable MEMS inertial sensors is proposed for medical rehabilitation with Physical Activities Healthcare System (PATHS) in this paper. We use relative wavelet energy as features for support vector machine (SVM) recognition algorithm to discriminate walking pattern from other motion patterns. This method has been proven capable of distinguishing walking gait from other regular physical activities through our experimental validation.
  • Keywords
    bioMEMS; gait analysis; health care; patient rehabilitation; support vector machines; biometric methods; gait recognition system; medical rehabilitation; physical activities; physical activities healthcare system; support vector machine recognition algorithm; walking gait analysis; wavelet energy; wearable MEMS inertial sensors; wearable microinertial measurement unit; Discrete wavelet transforms; Feature extraction; Humans; Legged locomotion; Sensors; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on
  • Conference_Location
    Karon Beach, Phuket
  • Print_ISBN
    978-1-4577-2136-6
  • Type

    conf

  • DOI
    10.1109/ROBIO.2011.6181530
  • Filename
    6181530