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Feature selection of stabilometric parameters based on principal component analysis

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Abstract

This study addresses the challenge of identifying the features of the Centre of pressure (COP) trajectory that are most sensitive to postural performance, with the aim of avoiding redundancy and allowing a straightforward interpretation of the results. Postural sway in 50 young, healthy subjects was measured by a force platform. Thirty-seven stabilometric parameters were computed from the one-dimensional and two-dimensional COP time series. After normalisation to the relevant biomechanical factors, by means of multiple regression models, a feature selection process was performed based on principal component analysis. Results suggest that COP two-dimensional time series can be primarily characterised by four parameters, describing the size of the COP path over the support surface; the principal sway direction; and the shape and bandwidth of the power spectral density plot. COP one-dimensional time series (antero-posterior (AP) and medio-lateral (ML)) can be characterised by six parameters describing COP dispersion along the AP direction; mean velocity along the ML and AP directions; the contrast between ML and AP regulatory activity; and two parameters describing the spectral characteristics of the COP along the AP direction. On the basis of the results obtained, some guidelines are suggested for the choice of stabilometric parameters to use, with the aim of promoting standardisation in quantitative posturography.

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References

  • Acciani, G., Chiarantoni, E., Fornarelli, G., andVergura, S. (2003): ‘A feature extraction unsupervised neural network for an environmental data set’,Neural Netw.,16, pp. 427–436

    Article  Google Scholar 

  • Baratto, L., Morasso, P., Re, C., andSpada, G. (2002): ‘A new look at posturographic analysis in the clinical context: sway-density vs. other parameterization techniques’,Motor Control,6, pp. 248–273

    Google Scholar 

  • Castellano, G., andFanelli, A. M. (2000): ‘Variable selection using neural-network models’,Neurocomputing,31, pp. 1–13

    Article  Google Scholar 

  • Chiari, L., Bertani, A., andCappello, A. (2000a): ‘Classification of human strategies in human postural control by stochastic parameter’,Hum. Mov. Sci.,19, pp. 817–842

    Article  Google Scholar 

  • Chiari, L., Cappello, A., Lenzi, D., andDella, C. U. (2000b): ‘An improved technique for the extraction of stochastic parameters from stabilograms’,Gait Post.,12, pp. 225–234

    Google Scholar 

  • Chiari, L., Rocchi, L., andCappello, A. (2002): ‘Stabilometric parameters are affected by anthropometry and foot placement’,Clin. Biomech. (Bristol, Avon),17, pp. 666–677

    Article  Google Scholar 

  • Cocchi, M., Hidalgo-Hidalgo-De-Cisneros, J. L., Naranjo-Rodríguez, I., Palacios-Santander, J. M., Seeber, R., andUlrici, A. (2003): ‘Multicomponent analysis of electrochemical signals in the wavelet domain’,Talanta,59, pp. 735–749

    Article  Google Scholar 

  • Collins, J. J. andDe Luca, C. J. (1993): ‘Open-loop and closed-loop control of posture: a random-walk analysis of center-of-pressure trajectories’,Exp. Brain Res.,95, pp. 308–318

    Article  Google Scholar 

  • Deluzio, K. J., Wyss, U. P., Zee, B., Costigan, P. A., andSorbie, C. S. (1997): ‘Principal component models of knee kinematics and kinetics: normal vs. pathological gait patterns’,Hum. Mov. Sci.,16, pp. 201–217

    Article  Google Scholar 

  • Diener, H. C., Dichgans, J., Bacher, M., andGompf, B. (1984): ‘Quantification of postural sway in normals and patients with cerebellar diseases’,Electroencephalogr: Clin. Neurophysiol.,57, pp. 134–142

    Google Scholar 

  • Fodor, I. K. (2002): ‘A survey of dimension reduction techniques’. LLNL Technical Report, UCRL-ID-148494

  • Fukunaga, K., andKoontz, W. L. G. (1970): ‘Application of the Karhunen-Loeve expansion to feature selection and ordering’,IEEE Trans. Comput.,19, pp. 311–318

    Google Scholar 

  • Hintze, J. L. (2000): ‘NCSS user's guide’ (NCSS, Kaysville, 2000)

    Google Scholar 

  • Hufschmidt, A., Dichgans, J., Mauritz, K. H., andHufschmidt, M. (1980): ‘Some methods and parameters of body sway quantification and their neurological applications’,Arch. Psychiatr. Nervenkr.,228, pp. 135–150

    Article  Google Scholar 

  • Hyvarinen, A. (1999): ‘Survey on independent component analysis’,Neural Comput. Surv.,2, pp. 94–128

    Google Scholar 

  • Jolliffe, I. T. (1972): ‘Discarding variables in a principal component analysis, I: Artificial data’,Appl. Statist.,21, pp. 160–173

    MathSciNet  Google Scholar 

  • Jolliffe, I. T. (1986): ‘Principal component analysis’ (Springer-Verlag, New York, 1986).

    Google Scholar 

  • Kaiser, H. F. (1960): ‘The application of electronic computers to factor analysis’,Educ. Psychol. Meas.,20, pp. 141–151

    Google Scholar 

  • Kapteyn, T. S., Bles, W., Njiokiktjien, C. J., Kodde, L., Massen, C. H., andMol, J. M. (1983): ‘Standardization in platform stabilometry being a part of posturography’,Agressologie,24, pp. 321–326

    Google Scholar 

  • Karlsson, A., andFrykberg, G. (2000): ‘Correlations between force plate measures for assessment of balance’,Clin. Biomech., Bristol, Avon,15, pp. 365–369

    Google Scholar 

  • Kaufman, K. R., andSutherland, D. H. (1996): ‘Future trend in human motion analysis’ inHarris, G. F., andSmith, P. A. (Eds): ‘Human motion analysis’, (IEEE Press, Piscataway, NJ, 1996), pp. 187–215

    Google Scholar 

  • Maki, B. E., Holliday, P. J., andFernie, G. R. (1990): ‘Aging and postural control. A comparison of spontaneous- and induced-sway balance tests’,J. Am. Geriatr. Soc.,38, pp. 1–9

    Google Scholar 

  • Maki, B. E., Holliday, P. J., andTopper, A. K. (1994): ‘A prospective study of postural balance and risk of falling in an ambulatory and independent elderly population’,J. Gerontol.,49, pp. M72-M84

    Google Scholar 

  • McCabe, G. P. (1984): ‘Principal variables’,Teechnometrics, pp. 137–144

  • McKeown, M. J. andRadtke, R. (2001): ‘Phasic and tonic coupling between EEG and EMG demonstrated with independent component analysis’,J. Clin. Neurophysiol.,18, pp. 45–57

    Google Scholar 

  • Newell, K. M., Slobounov, S. M., Slobounova, E. S., andMolenaar, P. C. (1997): ‘Stochastic processes in postural center-of-pressure profiles’,Exp. Brain Res.,113, pp. 158–164

    Google Scholar 

  • O'malley, M. J. (1996): ‘Normalization of temporal-distance parameters in pediatric gait’,J. Biomech.,29, pp. 619–625

    Article  Google Scholar 

  • Oliveira, L. F., Simpson, D. M., andNadal, J. (1996): ‘Calculation of area of stabilometric signals using principal component analysis’,Physiol. Meas.,17, pp. 305–312

    Article  Google Scholar 

  • Prieto, T. E., Myklebust, J. B., Hoffmann, R. G., Lovett, E. G., andMyklebust, B. M. (1996): ‘Measures of postural steadiness: differences between healthy young and elderly adults’,IEEE Trans. Biomed. Eng.,43, pp. 956–966

    Article  Google Scholar 

  • Rocchi, L., Chiari, L., andHorak, F. B. (2002): ‘Effects of deep brain stimulation and levodopa on postural sway in Parkinson's disease’,J. Neurol. Neurosur. Psych.,73, pp. 267–274

    Google Scholar 

  • Tarantola, J., Nardone, A., Tacchini, E., andSchieppati, M. (1997): ‘Human stance stability improves with the repetition of the task: effect of foot position and visual condition’,Neurosci. Lett.,228, pp. 75–78

    Article  Google Scholar 

  • Vigario, R., Sarela, J., Jousmaki, V., Hamalainen, M., andOja, E. (2000): ‘Independent component approach to the analysis of EEG and MEG recordings’,IEEE Trans. Biomed. Eng.,47, pp. 589–593

    Article  Google Scholar 

  • Viitasalo, M. K., Kampman, V., Sotaniemi, K. A., Leppavuori, S., Myllyla, V. V., andKorpelainen, J. T. (2002): ‘Analysis of sway in Parkinson's disease using a new inclinometry-based method’,Mov. Disord.,17, pp. 663–669

    Article  Google Scholar 

  • Winter, D. A., Prince, F., Frank, J. S., Powell, C., andZabjek, K. F. (1996): ‘Unified theory regarding A/P and M/L balance in quiet stance’,J. Neurophysiol.,75, pp. 2334–2343

    Google Scholar 

  • Yamamoto, S., Suto, Y., Kawamura, H., Hashizume, T., Kakurai, S., andSugahara, S. (1983): ‘Quantitative gait evaluation of hip diseases using principal component analysis’,J. Biomech.,16, pp. 717–726

    Article  Google Scholar 

  • Yamamoto, R., Kinoshita, T., Momoki, T., Arai, T., Okamura, A., Hirao, K., andSekihara, H. (2001): ‘Postural sway and diabetic peripheral neuropathy’,Diabetes Res. Clin. Pract. 52, pp. 213–221

    Article  Google Scholar 

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Rocchi, L., Chiari, L. & Cappello, A. Feature selection of stabilometric parameters based on principal component analysis. Med. Biol. Eng. Comput. 42, 71–79 (2004). https://doi.org/10.1007/BF02351013

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