Multiscale characterization of chronobiological signals based on the discrete wavelet transform
Multiscale characterization of chronobiological signals based on the discrete wavelet transform
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DOI：
10.1109/10.817623
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发表时间：
2000-01-01
影响因子：
4.6
通讯作者：
Poon, AMS
中科院分区：
文献类型：
--
作者：
Chan, FHY;Wu, BM;Poon, AMS
为了弥补传统的频域或时域分析方法的不足，提出了一种基于离散小波变换（DWT）的时间生物学时间序列（CTS）的多尺度分析方法。我们已经表明，在不同尺度的小波系数的局部模极大值和零交叉给出了一个完整的特征的节奏活动。我们进一步构建了一个树形图来表示跨尺度的交互活动。利用小波变换在频域中的带通滤波特性，我们还通过计算各个节律带中的能量来表征与带相关的活动。此外，由于有一个快速和易于实现的算法的DWT，这种新的方法可以简化信号处理，并提供了一个更有效和完整的研究的时间-频率动态的CTS，初步结果使用所提出的方法在改变光照条件下的小鼠的运动，验证其能力的CTS分析。
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.