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Application of the Stability Coefficient for Considering Intrinsic Variability of Postural Sway

  • Dongwon Kang
  • Jeongwoo Seo
  • Junggil Kim
  • Jinsoo Lee
  • Jinseung Choi
  • Gyerae TackEmail author
Regular Paper

Abstract

Postural sway typically has high intrinsic variability. Due to high intrinsic variability, the reliability of its clinical application is limited. This study proposed the modified stability coefficient considering the intrinsic variability of postural sway for reducing its high level of variability, and calculated the contribution of major sensory systems (somatosensory, visual and vestibular) for its possible clinical application. The subjects of this study were composed of 25 healthy young (HY) adults in their 20 s and 33 healthy older (HO) adults over 65 years of age. Each subject maintained four standing conditions (eyes open and eyes closed on a firm surface, and a foam surface) for 1 min each, and postural sway was measured using the inertial sensor that was attached to their waist. Postural sway was calculated using seven variables that reflect the changes in spatial movements (Mean distance, Root mean square, Path length, Range of acceleration, Mean velocity, Mean frequency, 95% confidence ellipse area). The stability coefficient proposed in this study was calculated using the variables that showed significant difference between groups, and sensory contributions were calculated. The indices on the statistics (p value) and practical significance (effect size: Cohen’s d) between the groups, and the coefficient of variation (CV) within each group were calculated by the calculated sensory contribution. By introducing the stability coefficient, the average CV was reduced to 28.13% in HY and 27.20% in HO with a high level of variation, compared to 36.67% in HY and 39.30% in HO with a very high level of variation. The average CV of sensory ratios was 12.79% in HY and 12.92% in HO with a medium level of variation. As the sensory ratios utilizing stability coefficient show statistical and practical differences of age-related changes in balance and the average CVs with a medium level of variation, these results indicate the possibility of clinical use about the sensory ratios.

Keywords

Stability coefficient Postural sway Intrinsic variability Inertial sensor Sensory contributions 

List of Symbols

HY

Healthy young

HO

Healthy older

CV

Coefficient of variation

EO

Eyes open, firm surface

EC

Eyes closed, firm surface

EO-foam

Eyes open, foam surface

EC-foam

Eyes closed, foam surface

DIST

Mean distance

RMS

Root mean square

PATH

Path length

RANGE

Range of acceleration

MV

Mean velocity

MF

Mean frequency

AREA

95% confidence ellipse area

Notes

Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A2A2A03014511 and 2016R1D1A3B03930135).

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Copyright information

© Korean Society for Precision Engineering 2019

Authors and Affiliations

  • Dongwon Kang
    • 1
  • Jeongwoo Seo
    • 1
  • Junggil Kim
    • 1
  • Jinsoo Lee
    • 1
  • Jinseung Choi
    • 1
    • 2
  • Gyerae Tack
    • 1
    • 2
    Email author
  1. 1.Department of Biomedical EngineeringKonkuk UniversityChungju-siSouth Korea
  2. 2.BK21 Plus Research Institute of Biomedical EngineeringKonkuk University, KoreaChungju-siSouth Korea

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