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Experimental evaluation of a smartphone based Step Length estimation.

Lucia Pepa, Federica Verdini, Luca Spalazzi

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
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    Summary

    This study presents a non-invasive system to accurately estimate Step Length (SL), crucial for monitoring Freezing of Gait (FoG) in patients. The developed architecture shows reliable SL estimation, aiding in the detection of gait abnormalities.

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    Area of Science:

    • Biomedical Engineering
    • Clinical Biomechanics
    • Neurology

    Background:

    • Step Length (SL) is vital for gait analysis, especially in patients with motor disorders like Freezing of Gait (FoG).
    • Freezing of Gait (FoG) significantly alters spatio-temporal gait parameters, including SL, impacting patient mobility.
    • Accurate SL monitoring is essential for early detection and management of FoG events.

    Purpose of the Study:

    • To develop and evaluate a non-intrusive and non-invasive architecture for reliable Step Length (SL) estimation.
    • To assess the accuracy of the proposed system in estimating SL across different walking velocities.
    • To determine the system's suitability for clinical application in Freezing of Gait (FoG) detection.

    Main Methods:

    • Development of a novel non-intrusive, non-invasive system architecture for gait analysis.
    • Evaluation of the system's reliability through Step Length (SL) estimation in 8 healthy subjects.
    • Testing SL estimation accuracy at low, normal, and high walking velocities.

    Main Results:

    • The system achieved mean estimation errors of 7.77% (low velocity), 6.99% (normal velocity), and 6.44% (high velocity).
    • These error margins demonstrate sufficient accuracy for practical clinical application.
    • The non-invasive nature ensures patient comfort and ease of use.

    Conclusions:

    • The proposed architecture provides reliable and accurate Step Length (SL) estimation.
    • This technology holds significant potential for non-invasive monitoring and early detection of Freezing of Gait (FoG).
    • The system's accuracy supports its clinical utility in managing gait disorders.