Fractal Analysis of Spontaneous Fluctuations in Human Cerebral Hemoglobin Content and its Oxygenation Level Recorded by NIRS

Abstract

The NIRS technology provides a non-invasive tool to monitor hemodynamics from the human brain cortex (Jöbsis 1977; Wyatt et al., 1986). Our interest recently has turned toward studies utilizing this technology in understanding the complexity of hemodynamics in the human brain as captured in high resolution hemoglobin time series. In our definition a time series or signal is complex when it is difficult to recognize a pattern such as it is being stable or periodic in its structuring. A complex signal cannot be adequately characterized by descriptive statistical measures such as its mean, standard deviation, etc., or by its frequency spectrum because by doing so other relevant information that is present in these signals are discarded or not revealed. Hence, adequate models, and methods need to be identified for such signals to be characterized in their entirety. Similar to our previous study on red blood cell flux time series acquired from the brain cortex of the rat (Eke et al., 1997) we have applied the fractal model as implemented in a combination of the power spectral density (PSD) and the scaled windowed variance (SWV) methods in the analysis of human cerebrocortical hemoglobin signals in an attempt to assess their temporal pattern.