Discrete wavelet and modified PCA decompositions for postural stability analysis in biometric applications
Dhouha Maatar, Regis Fournier, Zied Lachiri, Amine Nait-Ali
DOI: 10.4236/jbise.2011.48070   PDF    HTML     4,396 Downloads   8,504 Views   Citations

Abstract

The aim of this study is to compare the Discrete wavelet decomposition and the modified Principal Analysis Component (PCA) decomposition to analyze the stabilogram for the purpose to provide a new insight about human postural stability. Discrete wavelet analysis is used to decompose the stabilogram into several timescale components (i.e. detail wavelet coefficients and approximation wavelet coefficients). Whereas, the modified PCA decomposition is applied to decompose the stabilogram into three components, namely: trend, rambling and trembling. Based on the modified PCA analysis, the trace of analytic trembling and rambling in the complex plan highlights a unique rotation center. The same property is found when considering the detail wavelet coefficients. Based on this property, the area of the circle in which 95% of the trace’s data points are located, is extracted to provide important information about the postural equilibrium status of healthy subjects (average age 31 ± 11 years). Based on experimental results, this parameter seems to be a valuable parameter in order to highlight the effect of visual entries, stabilogram direction, gender and age on the postural stability. Obtained results show also that wavelets and the modified PCA decomposition can discriminate the subjects by gender which is particularly interesting in biometric applications and human stability simulation. Moreover, both techniques highlight the fact that male are less stable than female and the fact that there is no correlation between human stability and his age (under 60).

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Maatar, D. , Fournier, R. , Lachiri, Z. and Nait-Ali, A. (2011) Discrete wavelet and modified PCA decompositions for postural stability analysis in biometric applications. Journal of Biomedical Science and Engineering, 4, 543-551. doi: 10.4236/jbise.2011.48070.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Ekhdahl, C., Jarnlo, G. and Andersson, S. (1989) Stand- ing balance in healthy subjects. Scand J Rehabil Med 21:187-195.
[2] Juntunen, J., Ylikoski, J., Ojala, M., Matikainen, E., Ylikoski, M. and Vaheri, E. (1987) Postural body sway and exposure to high-energy impulse noise. Lancet 11: 261-264.
[3] Gagey, P., Agey B., Webber A. (1995) Entrées du système postural fin, ED. Masson.
[4] Fournier, R., Deléchelle, E. and Lemoine, J. (2001) Décomposition et analyse du signal stabilométrique, 18e colloque GRETSI’01, Toulouse, 10-13, p 7.
[5] Fournier, R., Deléchelle, E. and Lemoine, J. (2002) Méthodes de calibrage d’un système électromagnétique pour l’étude et l’évaluation de mesure posturale, Revue I.T.B.M., R.B.M. 2002; 23: 303-315. Editions scientifiques et médicales ELSEVIER SAS.
[6] Fournier, R., (2002) Analyse stochastique modale du signal stabilométrique. Application à l'étude de l'équilibre chez l'Homme. PhD thesis, Université Paris-12.
[7] Fournier, R., Deléchelle, E. and Lemoine, J. (2004) Stabilogram phase estimation, ISIE'2004 IEEE Interna- tional Symposium on Industrial Electronics, Ajaccio (France), 4-7 mai.
[8] Carroll, J. P. and W. Freedman, Nonstationary properties of postural sway, Journal of Biomechanics, Vol. 26, No. 4-5, pp. 409-416, 1993.
[9] Amoud, H., Snoussi H., Hewson, D. and Duchêne, J. (2007) Hilbert-Huang Transformation: Application to Postural Stability Analysis, IEEE EMBC, Lyon.
[10] Amoud, H., Snoussi H., Hewson, D. and Duchêne, J. (2008) Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis, EURASIP Journal on Advances in Signal. Processing.
[11] Huang, N.E., Shen, Z., Long, SR., M.L.C., Shih, H.H., Zheng, Q.N., Yen, N.C., Tung, C. and Liu, H. (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. Roy. Soc. LOND A MAT, 454, pp. 903-995.
[12] Davis, JR., Campbell, AD., Adkin, AL., Carpenter, MG. (2009) The relationship between fear of falling and human postural control, Gait Posture 29: 275-279.
[13] Uetake, T., Tanaka, H., Shindo M. and Okada, M. (2004) Two new methods applicable to center of pressure swing analysis. Anthropol Sci 112:187-193.
[14] Martínez-Ramírez, A., Lecumberri, P., Gómez, M. (2010) Wavelet analysis based on time-frequency information discriminate chronic ankle instability, Clinical Biomechanics, Vol. 25, No. 3, pp. 256-264.
[15] Bardet, M. and Bertrand, P. (2007) Definition, properties and wavelet analysis of multiscale fractional Brownian motion, Fractals, Vol. 15, No. 1, pp.1-15.
[16] Bertrand, P., Bardet M., Dabonneville, M. and Mouzat, A. (2001) Automatic Determination of the Different Control Mechanisms in Upright Position by a Wavelet Method. IEEE Engineering in Medicine and Biology Society, Istambul, 25-28.
[17] HongBo, Zhang. (2007) Use of Statistical Mechanics Methods to Assess the Effects of Localized Muscl Fatigue on Stability during Upright Stance, PhD thesis.
[18] Chagdes, J., Rietdyk, S., Haddad M., Zelaznik, N., Raman, A., Rhea, K., Silver, A., (2009) Multiple timescales in postural dynamics associated with vision and a secondary task are revealed by wavelet analysis, Experimental brain research, Vol. 197, No. 3, pp. 297-310.
[19] Black, FO., Wall, C., Rockette, H; and Kitch R. (1982) Normal subject postural sway during the Romberg Test, Am J Otolaryngol, 3: 309–318.
[20] Thanh-Thuan, Le., Kapoula Z. (2008) Role of ocular convergence in the Romberg quotient, Gait & posture ISSN 0966-6362, Vol. 27, No. 3, pp. 493-500.
[21] Andrea Berencsi, A., Masami Ishihara, B. and Kuniyasu, I. (2008) The functional role of central and peripheral vision in the control of posture, Gait & Posture 27, 493-500.
[22] Balasubramaniam R., Riley, M., Turvey, M. (2000) Specificity of postural sway to the demands of a precision task, Gait and Posture 11, 12-24.
[23] Ivanenko, Y., Grasso, R. and F. Lacquaniti (1999) Effect of gaze on postural responses to neck proprioceptive and vestibular stimulation in humans. Journal of Physiology, 519.1, pp. 301-314.
[24] McIlroy, WE., Maki, BE. (1997) Preferred placement of the feet during quiet stance: development of a standardized foot placement for balance testing, Clin Biomech, 12: 66-70.
[25] Abrahámova, D. and Hlava?ka, F. (2008) Age-related changes of human balnce during quiet stance. Physiol Res. 57: 957-964.
[26] Du Pasquier, RA., Blanc, Y., Sinnreich, M., Landis, T., Burkhard P., Vingerhoets FJG. (2003) The effect of aging on postural stability: a cross sectional and longitudinal study. Clin Neurophysiol 33: 213-218.
[27] Fujita ,T., Nakamura, S., Ohue, M., Fujii, Y., Miyauchi, A., Takagi, Y. and Tsugeno, H. (2005) Effect of age on body sway assessed by computerized posturography. J Bone Miner Metab 23: 152-156.
[28] Hyt?nen, M., Pyykk? I., Aaalto, H. and Strack, J. (1993) Postural control and age, Acta Otolaryngol (Stockh) 113: 119-122.
[29] Hageman, PA., Leibowitz, JM. and Blanke, D. (1995) Age and gender effects on postural control measures, Arch Phys Med Rehabil, 76: 961-965.
[30] Kinney LaPier, L., Liddle, S. and Bain C. (1997) A comparison of static and dynamic standing balance in older men versus women. Physiotherapy Canada 49: 207-213.
[31] Ojala, M., Matikainen, E., and Juntunen, J. (1998) Posturography and the dizzy patient: a neurological study of 133 patients. Acta Neurol Scand 80:118-122.

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