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A Review on Accelerometry Based Gait Analysis and Emerging Clinical Applications

  • Delaram Jarchi
  • , James Pope
  • , Tracey K.M. Lee
  • , Larisa Tamjidi
  • , Amirhosein Mirzaei
  • , Saeid Sanei

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    205 Citations (Scopus)

    Abstract

    Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modelling, and many other fields. There are established methods using various sensors for gait analysis, of which, accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. The commonly used gait phases and parameters are enumerated. The details of extracting the papers for review are provided. We also review several gait analysis software. Then, we provide an extensive report of accelerometry based gait analysis systems and applications with additional emphasis on trunk accelerometry. We conclude this review with future research directions.

    Original languageEnglish
    JournalIEEE Reviews in Biomedical Engineering
    Early online date16 Feb 2018
    DOIs
    Publication statusE-pub ahead of print - 16 Feb 2018

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Acceleration
    • accelerometer
    • Accelerometers
    • Capacitance
    • Diseases
    • gait
    • inertial measurement unit
    • Microstructure
    • Sensors
    • Spinal cord
    • trunk

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