Fractal behaviour of heart rate variability reflects severity in stroke patients.

Non-linear parameters obtained from heart rate variability (HRV) analysis has recently been recognized to provide valuable information for physiological interpretation of heart rate fluctuation. Among the numerous non-linear parameters related to the fractal behaviour of the HRV signal, two classes have gained wide interest in the last years: the beta exponent based on the 1/f-like relationship, starting from the spectral power, and that based on fractal dimension. In order to evaluate the relationship between lesion's severity and fractal behaviour, 20 first-ever stroke subjects and 10 healthy subjects were studied. Patients were divided in two groups according to single or multiple medium cerebral artery lesions. All subjects underwent 24-hour Holter recording analysed by fractal and 1/f-like techniques. Differently from methods usually used in literature to evaluate the fractal dimension (FD), in this work the FD was extracted by using the Higuchi's algorithm that permits to calculate the parameter directly from the HRV sequences in the time domain. Results show that fractal analysis contains relevant information related to different HRV dynamics that permits to separate normal subjects from stroke patients. FD is also able to distinguish between normal and stroke subjects with different lesion's severity.