Step Sequence and Direction Detection of Four Square Step Test

Weisheng Kong, Lauren Wanning, Salvatore Sessa, Massimiliano Zecca, Daniele Magistro, Hikaru Takeuchi, Ryuta Kawashima, Atsuo Takanishi

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    Poor balance control and falls are big issues for older adults that due to aging decline have a lower postural balance and directional control in balance performance than younger age groups. The four square step test (FSST) was developed to evaluate rapid stepping that is often required when changing direction and avoiding obstacles while walking. However, previous researchers used only the total time as the assessment in the test. The aim of this letter is to objectively quantify the sequence and direction of the steps in FSST, by using two inertial sensors placed on both feet. An algorithm was developed to automatically segment the steps performed during the test, and calculate the stepping direction from the linear velocity of the foot. Experiments were conducted with 100 Japanese healthy older adults, where sensor data and video of 20 subjects were randomly subtracted for algorithm verification. The results showed that the algorithm succeeded for 71.7% trials in recognizing both the step sequence and step direction in FSST, while 90.2% of the detection failure could be excluded with an auto verification method.

    Original languageEnglish
    Article number7970186
    Pages (from-to)2194-2200
    Number of pages7
    JournalIEEE Robotics and Automation Letters
    Volume2
    Issue number4
    DOIs
    Publication statusPublished - 2017 Oct 1

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    Keywords

    • Automation in life sciences: biotechnology
    • health care management
    • pharmaceutical and health care
    • sensor fusion

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Human-Computer Interaction
    • Biomedical Engineering
    • Mechanical Engineering
    • Control and Optimization
    • Artificial Intelligence
    • Computer Science Applications
    • Computer Vision and Pattern Recognition

    Cite this

    Kong, W., Wanning, L., Sessa, S., Zecca, M., Magistro, D., Takeuchi, H., Kawashima, R., & Takanishi, A. (2017). Step Sequence and Direction Detection of Four Square Step Test. IEEE Robotics and Automation Letters, 2(4), 2194-2200. [7970186]. https://doi.org/10.1109/LRA.2017.2723929