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• Wei, Q
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• Shieh, J
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Entropy 2012, 14(11), 2157-2172; doi:10.3390/e14112157

Article

Multivariate Multiscale Entropy Applied to Center of Pressure Signals Analysis: An Effect of Vibration Stimulation of Shoes

Qin Wei ¹ , Dong-Hai Liu ¹ , Kai-Hong Wang ² , Quan Liu ¹ , Maysam F. Abbod ³ , Bernard C. Jiang ⁴ , Ku-Ping Chen ⁵ , Chuan Wu ⁵  and Jiann-Shing Shieh ^2,6,*

¹ School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, China ² Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Chung-Li, 32003, Taiwan ³ School of Engineering and Design, Brunel University, London, UB8 3PH, UK ⁴ Department of Industrial Engineering & Management, Yuan Ze University, Taoyuan, Chung-Li, 32003, Taiwan ⁵ Taipei Veterans General Hospital, Taoyuan Branch, Taoyuan, 33052, Taiwan ⁶ Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taoyuan, Chung-Li, 32001, Taiwan

* Author to whom correspondence should be addressed.

Received: 7 September 2012; in revised form: 10 October 2012 / Accepted: 29 October 2012 / Published: 2 November 2012

Download PDF Full-Text [437 KB, Updated Version, uploaded 6 November 2012 11:20 CET]

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Abstract: Falls are unpredictable accidents and resulting injuries can be serious to the elderly. A preventative solution can be the use of vibration stimulus of white noise to improve the sense of balance. In this work, a pair of vibration shoes were developed and controlled by a touch-type switch which can generate mechanical vibration noise to stimulate the patient’s feet while wearing the shoes. In order to evaluate the balance stability and treatment effect of vibrating insoles in these shoes, multivariate multiscale entropy (MMSE) algorithm is applied to calculate the relative complexity index of reconstructed center of pressure (COP) signals in antero-posterior and medio-lateral directions by the multivariate empirical mode decomposition (MEMD). The results show that the balance stability of 61.5% elderly subjects is improved after wearing the developed shoes, which is more than 30.8% using multiscale entropy. In conclusion, MEMD-enhanced MMSE is able to distinguish the smaller differences between before and after the use of vibration shoes in both two directions, which is more powerful than the empirical mode decomposition (EMD)-enhanced MSE in each individual direction.

Keywords: center of pressure; vibration; multivariate multiscale entropy; multivariate empirical mode decomposition

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