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

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,...

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Published inInternational journal of precision engineering and manufacturing Vol. 20; no. 3; pp. 443 - 449
Main Authors Kang, Dongwon, Seo, Jeongwoo, Kim, Junggil, Lee, Jinsoo, Choi, Jinseung, Tack, Gyerae
Format Journal Article
LanguageEnglish
Published Seoul Korean Society for Precision Engineering 01.03.2019
Springer Nature B.V
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ISSN2234-7593
2005-4602
DOI10.1007/s12541-019-00024-0

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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.
AbstractList 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.
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.
Author Kim, Junggil
Kang, Dongwon
Tack, Gyerae
Seo, Jeongwoo
Choi, Jinseung
Lee, Jinsoo
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Issue 3
Keywords Inertial sensor
Sensory contributions
Intrinsic variability
Postural sway
Stability coefficient
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Snippet Postural sway typically has high intrinsic variability. Due to high intrinsic variability, the reliability of its clinical application is limited. This study...
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SubjectTerms Adults
Coefficient of variation
Confidence
Engineering
Eye (anatomy)
Industrial and Production Engineering
Inertial sensing devices
Materials Science
Mathematical analysis
Posture
Regular Paper
Title Application of the Stability Coefficient for Considering Intrinsic Variability of Postural Sway
URI https://link.springer.com/article/10.1007/s12541-019-00024-0
https://www.proquest.com/docview/2197971801
Volume 20
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