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Current Development in Theory and Applications of Wavelets

Current Development in Theory and Applications of Wavelets
Volume 1, Issue 3, Pages 251 - 272 (December 2007)

TWO-STEP WAVESTRAPPING: SIMULATING NON-STATIONARY ACCELERATION DATA IN THE MOBILE COMPUTING CONTEXT Ji Soo Yi (USA), Yoon Young Jung (Korea), Julie A. Jacko (USA), François Sainfort (USA) and Brani Vidakovic (USA) Received November 12, 2007 References:
[1] P. Abry, P. Flandrim, M. Taqqu and D. Veitch, Self-similarity and long-range dependence through the wavelet lens, Theory and Applications of Long-Range Dependence, P. Doukhan, G. Oppenheim and M. Taqqu, eds., Birkhäuser, Boston, 2003. [2] P. Abry, D. Veitch and P. Flandrim, Long-range dependence: revisiting aggregation with wavelets, Journal of Time Series Analysis 19(3) (1998), 256-266. [3] R. G. Andrzejak, A. Kraskov, H. Stögbauer, F. Mormann and T. Kreuz, Bivariate surrogate techniques: necessity, strengths and caveats, Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics 68(6) (2003), 066202. [4] C. Angelini, D. Cava, G. Katul and B. Vidakovic, Resampling hierarchical processes in the wavelet domain: A case study using atmospheric turbulence, Physica D: Nonlinear Phenomena 207(1-2) (2005), 24-40. [5] L. Bao and S. S. Intille, Activity recognition from user-annotated acceleration data, Proceedings of the 2nd International Conference on Pervasive Computing (PERVASIVE’04), Linz/Vienna, Austria, Springer, 2004. [6] L. Barnard, J. S. Yi, J. A. Jacko and A. Sears, An empirical comparison of use-in-motion evaluation scenarios for mobile computing devices, International Journal of Human-Computer Studies 62(4) (2005), 487-520. [7] L. Barnard, J. S. Yi, J. A. Jacko and A. Sears, Capturing the effects of context on human performance in mobile computing systems, Personal and Ubiquitous Computing 11(2) (2007), 81-96. [8] J. Beran, Statistics for Long Memory Processes, Chapman & Hall, 1994. [9] M. Breakspear, M. Brammer and P. A. Robinson, Construction of multivariate surrogate sets from nonlinear data using the wavelet transform, Physica D: Nonlinear Phenomena 182(1-2) (2003), 1-22. [10] P. Bühlmann, Bootstraps for time series, Statistical Science 17(1) (2002), 52-72. [11] E. Bullmore, J. Fadili, M. Breakspear, R. Salvador, J. Suckling and M. Brammer, Wavelets and statistical analysis of functional magnetic resonance images of the human brain, Statistical Methods in Medical Research 12 (2003), 375-399. [12] E. Bullmore, C. Long, J. Suckling, J. Fadili, G. Calvert, F. Zelaya, T. A. Carpenter and M. Brammer, Colored noise and computational inference in neurophysiological (fmri) time series analysis: Resampling methods in time and wavelet domains, Human Brain Mapping 12(2) (2001), 61-78. [13] M. M. Clayton and H. C. Schamhardt, Measurement techniques for gait analysis, Equine Locomotion, W. Back and H. M. Clayton, eds., W. B. Saunders Company, 2000. [14] A. Crossan, R. Murray-Smith, S. Brewster, J. Kelly and B. Musizza, Gait phase effects in mobile interaction, Conference on Human Factors in Computing Systems (CHI’05), Portland, OR, USA, 2005, ACM Press, pp. 1312-1315. [15] A. C. Davison and D. V. Hinkley, Bootstrap Methods and their Application, Cambridge University Press, 1997. [16] B. Efron, Bootstrap methods: Another look at the jackknife, The Annals of Statistics 7 (1979), 1-26. [17] B. Efron and R. Tibshirani, An introduction to the bootstrap, Chapman and Hall, 1993. [18] P. Fladrin, Wavelet analysis and synthesis of fractional brownian motion, IEEE Transactions on Information Theory 38(2) (1992), 910-917. [19] M. J. Griffin, Handbook of Human Vibration, Academic Press, 1996. [20] S. S. Intille, L. Bao, E. M. Tapia and J. Rondoni, Acquiring in situ training data for context-aware ubiquitous computing applications, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’04), Vienna, Austria, 2004, ACM Press, pp. 1-8. [21] Y. Kim, J. Yi and K. Rhee, Acceleration patterns of the body center in level walking: Normal and hemiplegic patients, World Congress on Medical Physics and Biomedical Engineering, Sydney, Australia, 2003. [22] H. R. Künsch, The jackknife and the bootstrap for general stationary observations, The Annals of Statistics 17(3) (1989), 1217-1241. [23] N. Mordant, J. Delour, E. Leveque, O. Michel, A. Arnedo and J. Printon, Lagrangian velocity fluctuations in fully developed turbulence: scaling, intermittency, and dynamics, Journal of Statistical Physics 113(5/6) (2003), 701-717. [24] D. Percival, S. Sardy and A. Davison, Wavestrapping time series: adaptive wavelet-based bootstrapping, Nonlinear and Nonstationary Signal Processing, W. Fitzgerald, R. Smith, A. Walden and P. Young, eds., Cambridge University Press, 1992. [25] D. N. Politis and J. P. Romano, The stationary bootstrap, Journal of the American Statistical Association 89(428) (1994), 1303-1313. [26] J. Theiler, S. Eubank, A. Longtin, B. Galdrikian and J. D. Farmer, Testing for nonlinearity in time series: the method of surrogate data, Physica D 58(1-4) (1992), 77-94. [27] M. Uiterwaal, E. Glerum, H. Busser and R. van Lummel, Ambulatory monitoring of physical activity in working situations, a validation study, Journal of Medical Engineering & Technology 22(4) (1998), 168-172. [28] B. Vidakovic, Statistical Modeling by Wavelets, Wiley Series in Probability and Statistics, John Wiley & Sons, Inc., 1999. [29] B. Vidakovic and C. Lozoya, On time-dependent wavelet denoising, IEEE Transactions on Signal Processing 46(9) (1998), 2549-2554. [30] J. S. Yi, Y. S. Choi, J. A. Jacko and A. Sears, Context awareness via a single device-attached accelerometer during mobile computing, Proceedings of the 7th International Conference on Human Computer Interaction with Mobile Devices and Services (Mobile HCI’05), Salzburg, Austria, 2005, pp. 303-306.

Keywords and phrases: wavelet, wavestrapping, acceleration data.

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