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Ability of a set of trunk inertial indexes of gait to identify gait instability and recurrent fallers in parkinson’s disease

Sensors, ISSN: 1424-8220, Vol: 21, Issue: 10
2021
  • 22
    Citations
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    Usage
  • 52
    Captures
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    Mentions
  • 1
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    22
  • Captures
    52
  • Social Media
    1
    • Shares, Likes & Comments
      1
      • Facebook
        1

Article Description

The aims of this study were to assess the ability of 16 gait indices to identify gait instability and recurrent fallers in persons with Parkinson’s disease (pwPD), regardless of age and gait speed, and to investigate their correlation with clinical and kinematic variables. The trunk acceleration patterns were acquired during the gait of 55 pwPD and 55 age-and-speed matched healthy subjects using an inertial measurement unit. We calculated the harmonic ratios (HR), percent recurrence, and percent determinism (RQAdet), coefficient of variation, normalized jerk score, and the largest Lyapunov exponent for each participant. A value of ≤1.50 for the HR in the antero-posterior direction discriminated between pwPD at Hoehn and Yahr (HY) stage 3 and healthy subjects with a 67% probability, between pwPD at HY 3 and pwPD at lower HY stages with a 73% probability, and it characterized recurrent fallers with a 77% probability. Additionally, HR in the antero-posterior direction was correlated with pelvic obliquity and rotation. RQAdet in the antero-posterior direction discriminated between pwPD and healthy subjects with 67% probability, regardless of the HY stage, and was correlated with stride duration and cadence. Therefore, HR and RQA in the antero-posterior direction can both be used as age-and-speed-independent markers of gait instability.

Bibliographic Details

Castiglia, Stefano Filippo; Tatarelli, Antonella; Trabassi, Dante; De Icco, Roberto; Grillo, Valentina; Ranavolo, Alberto; Varrecchia, Tiwana; Magnifica, Fabrizio; Di Lenola, Davide; Coppola, Gianluca; Ferrari, Donatella; Denaro, Alessandro; Tassorelli, Cristina; Serrao, Mariano

MDPI AG

Chemistry; Computer Science; Physics and Astronomy; Biochemistry, Genetics and Molecular Biology; Engineering

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