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Multiscale characterization of chronobiological signals based on the discrete wavelet transform

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5 Author(s)
F. H. Y. Chan ; Dept. of Electr. & Electron. Eng., Hong Kong Univ., Hong Kong ; B. M. Wu ; E. K. Lam ; P. W. F. Poon
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To compensate for the deficiency of conventional frequency-domain or time-domain analysis, this paper presents a multiscale approach to characterize the chronobiological time series (CTS) based on a discrete wavelet transform (DWT). We have shown that the local modulus maxima and zero-crossings of the wavelet coefficients at different scales give a complete characterization of rhythmic activities. We further constructed a tree scheme to represent those interacting activities across scales, Using the bandpass filter property of the DWT in the frequency domain, we also characterized the band-related activities by calculating energy in respective rhythmic bands. Moreover, since there is a fast and easily implemented algorithm for the DWT. This new approach may simplify the signal processing and provide a more efficient and complete study of the temporal-frequency dynamics of the CTS. Preliminary results are presented using the proposed method on the locomotion of mice under altered lighting conditions, verifying its competency for CTS analysis.

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IEEE Transactions on Biomedical Engineering  (Volume:47 ,  Issue: 1 )