Literature DB >> 28333650

Validation of Static and Dynamic Balance Assessment Using Microsoft Kinect for Young and Elderly Populations.

Moataz A Eltoukhy, Christopher Kuenze, Jeonghoon Oh, Joseph F Signorile.   

Abstract

Reduction in balance is an indicator of fall risk, and therefore, an accurate and cost-effective balance assessment tool is essential for prescribing effective postural control strategies. This study established the validity of the Kinect v2 sensor in assessing center of mass (CoM) excursion and velocity during single-leg balance and voluntary ankle sway tasks among young and elderly subjects. We compared balance outcome measures (anteroposterior (AP) and mediolateral (ML) CoM excursion and velocity and average sway length) to a traditional three-dimensional motion analysis system. Twenty subjects (10 young: age = y, height cm, weight kg; 10 elderly: age y, height cm, weight kg), with no history of lower extremity injury, participated in this study. Subjects performed six randomized trials; four single-leg stand (SLS) and two ankle sway trials. SLS and voluntary ankle sway trials showed that consistency (ICC(2, k)) and agreement (ICC(3, k)) for all variables when all subjects were considered, as well as when the elderly and young groups were analyzed separately. Concordance between systems ranged from poor to nearly perfect depending on the group, task, and variable assessed.

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Mesh:

Year:  2017        PMID: 28333650     DOI: 10.1109/JBHI.2017.2686330

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  7 in total

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7.  Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint-Node Plots.

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  7 in total

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