Body postural sway analysis in older people with different fall histories
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A cross-sectional study of postural sway analysis in older non-fallers, once-fallers and multiple-fallers using five common standing tests was conducted. Eighty-six older subjects with an average age of 80.4 years (SD ± 7.9) participated in the study. The angular rotation and velocity of the trunk of the participants in the roll (lateral) and pitch (sagittal) planes were recorded using an inertial sensor mounted on their lower backs. The Gaussian Mixture Models (GMM), Expectation-Maximisation (EM) and the Minimum Message Length (MML) algorithms were applied to the acquired data to obtain an index indicative of the body sway. The standing with feet together and standing with one foot in front, sway index distinguished older fallers from non-fallers with specificity of 75.7% and 77.7%, respectively, and sensitivity of 78.6% and 82.1%, respectively. This compares favourably with the Berg Balance Scales (BBS) with specificity of 70.5% and sensitivity of 75.3%. The results suggest that the proposed method has potential as a protocol to diagnose balance disorder in older people.
KeywordsOlder people Postural sway analysis Balance assessment Inertial sensor
The authors thank Melissa Roach, the clinical physiotherapist, for her supervision during the experimental tests. Miss Maryam Ghahramani, the chief investigator, did this study as a part of her PhD. thesis. Her PhD scholarship was funded by Illawarra Shoalhaven Local Health District (ISLHD). The authors wish to acknowledge that Bulli Hospital, Bulli, Australia, and Wollongong Hospital, Wollongong, Australia, provided this study with older participants.
Compliance with ethical standards
The participants were asked to read and sign an informed consent statement. The ethics committee of the University of Wollongong, Wollongong, Australia (HE13/125), approved this study.
- 1.Nashner LM, Woollacott M (1979) The organization of rapid postural adjustments of standing humans: an experimental-conceptual model. Posture Movement 243:257Google Scholar
- 8.Goldie PA, Back TM, Evans OM (1989) Force platform measures for evaluating postural control: reliability and validity. Archive Physical Medicine Rehabilitation 70(7):510–517Google Scholar
- 15.Gill J, Allum JH, Carpenter MG, Held-Ziolkowska M, Adkin AL, Honegger F, Pierchala K (2001) Trunk sway measures of postural stability during clinical balance tests: effects of age. J Gerontology: Medical Sci 56(7):M438–M447Google Scholar
- 16.Berg K, Norman K (1993) Functional assessment of balance and gait. Gait Balance Disorders 12(4):705–723Google Scholar
- 17.Zaiane OR (1999) Principles of knowledge discovery in databases, Department of Computing Science, University of Alberta , 1999Google Scholar
- 18.Silvestre C, Cardoso MGMS, Figueiredoc MA (2014) Identifying the number of clusters in discrete arXiv preprint arXiv 1409.7419Google Scholar
- 19.Douglas R (2015) Gaussian mixture models. In Encyclopedia of biometrics, Springer, Lexington, pp 659–663Google Scholar
- 21.Cheeseman P, Stutz J (1996) Bayesian classication (autoclass): theory and results. In: Advances in knowledge discovery and data mining. AAAI press, Menlo Park, pp 153–180Google Scholar