| dc.description.abstract |
What role do neuronal oscillations play in shaping computation and communication in physiological networks? There is increasing interest to this question.
One of the most intriguing and challenging phenomena in physiological and biological systems is scale-invariant/fractal patterns in the fluctuations of system outputs. These fractal patterns are robust in healthy physiological systems but are significantly altered or reduced in perturbed systems associated with aging and pathological conditions, indicating important underlying fractal controls that provide system integrity and adaptability. To estimate correlations in the fluctuations, we will utilize a widely accepted analytical tool, namely, detrended fluctuation analysis (DFA). Since the multi-mode modulation is a key feature of sleep EEG, and the short-term fractal property reflects the sympathovagal modulation of heart rate variability (HRV). We show that the properties of electroencephalography (EEG) and HRV are strongly correlated with sleep status and are interesting in clinic diagnosis, and the dynamic properties of sleep EEG and HRV derived by empirical mode decomposition (EMD) and DFA represent important features for cortex and autonomic nervous system (ANS) activities during sleep. On the other side, we also devote to circadian study mainly using animal models. Circadian investigations have mainly focused on understanding the generation of ~24-hour oscillations of the circadian pacemaker (the master clock of the system). Instead of acting as a generator of oscillations at a fixed time scale, our studies reveal that the master clock influences motor activity controls over a wide range of time scales as well.
Apart from the discoveries of temporal structure from the oscillation itself, many recent studies of complex systems have found that cross-frequency coupling (CFC) exists; that is, interactions occur between rhythms at different frequencies that are either within the same signals or in different signals. A generic problem in physiology is nonstationarity in signals that make many conventional analyses unreliable. By approaching using a nonlinear and nonstationary method, we try to better understand the dynamic of physiological phenomena and to disclosure the frequency bands that involved in coupling. For example, parameters derived from the goniometer measures in Pendulum test are insufficient in describing of the function of abnormal muscle activity in the spasticity. To explore a quantitative evaluation of muscle activation-movement interaction, we propose a novel index based on phase amplitude coupling (PAC) analysis with the consideration of the relations between movement and surface electromyography (SEMG) activity for hemiplegic stroke patients. This study indicates the feasibility of using the novel indices based on PAC in the evaluation of the spasticity among the hemiplegic stroke patients with less than 3 swinging cycles. Besides, to increase the available measures in clinical use, we additionally provide evidences to show that the Wii remote may serve as a convenient and cost-efficient tool for the assessment of spasticity as well.
In summary, by utilizing the nonlinear approach, we analyze the biological signals and develop the effective biomarkers for clinical use in this dissertation. | en_US |