A comparison between healthy and neurological disorders patients using nonlinear dynamic tools
In this paper, we evaluate the differences between Healthy subjects (HS), Parkinson Disease (PDS) subjects, and Epileptic subjects (EBS - Epileptic subject between seizures and ES - epileptic subjects in seizure) by computing some linear, statistic and non-linear features, such as: correlation dimension, maximum Lyapunov exponent and Hurst coefficient. A comparison is made between PDS, EBS, ES and HS groups using non-linear parameters. The EEG data are wavelet multiresolution decomposed into subbands of interest (alpha 8-12 Hz, beta 13-30 Hz, delta 0-4 Hz, theta 4-8 Hz, gamma 30-60 Hz). We applied rescaled range method to estimate the Hurst coefficient of the decomposed signals, with different types of wavelet transforms. The results obtained using the maximum Lyapunov exponent do not highlight very well differences between the 4 groups analyzed (HS, PDS, EBS and ES) but using Hurst coefficient we can make a very good differentiation of EEG signals. The results show that the Hurst coefficient is significant different for delta and theta rhythms extracted from the EEG signal in case of the healthy subjects compared with PDS or EBS subjects. The Hurst coefficient for healthy subjects has a value higher than 0.5 and for PD subjects or epileptic subject between seizures has a value lower than 0.5. Hence, the non-linear parameters such as Hurst coefficient can help in EEG interpretation and in neurological disorders diagnosis.
Estimating the hurst exponent in motor imagery-based brain computer interface
The objective of this paper is to detect sensorimotor rhythms (mu and beta) produced by right and left hand motor imagery. The electroencephalographic (EEG) data were recorded with 8 g.tec active electrodes by means of g.MOBIlab+ module. The EEG data are wavelet multiresolution decomposed into subbands of interest (7.5-15 Hz-mu rhythm, 15-30Hz-beta rhythm). We applied absolute moment and aggregated variance methods to estimate the Hurst exponent of these decomposed signals, with different types of wavelet. We obtained very good discrimination on channels C3 and CP3 for right hand motor imagery signal and on channels C4 and CP4, when left hand was imaginarily moved. The subjects discriminated better the beta rhythm.
VLA stereoscopy of solar active regions. 2: Altitude, relative motion, and center-to-limb darkening of 20 centimeter emission
A newly developed method of stereoscopic correlation is applied to solar radio maps at a wavelength of 20 cm. On the basis of stereoscopic correlations between radio maps obtained on 6 different days we establish the presence of 66 radio source components associated with 22 active regions. We find the following statistical results for active region source structures at 20 cm: 1. The observed lifetime is consistent with an exponential distribution having an e-folding time scale of greater than 18 days. 2. The average altitude of 20 cm sources is 25 +/- 15 Mm; 90% of the sources are found in heights less than 40 Mm. 3. The average diameter of discrete source structures is 48 +/- 15 Mm, implying a vertical/horizontal aspect ratio of q(sub A) approx. = 0.5. 4. No significant source motion has been found with respect to the standard differential rotation rate of Omega = 13.45 deg - ((3 deg (sin(exp 2)B)). 5. We find a statistical limb darkening, which can be described by the relation (T(sub B)(alpha))/T(sub B)(0)) = 0.4 + ((0.6(cos(exp 2) alpha)) for sources with T(sub B) greater than 0.5 MK. 6. The degree of source polarization is 15% +/- 10% and is independent of source location. 7. Bright sources (greater than or approximately equal to 0.5 MK), or equivalently, long-lived sources (greater than or approximately equal to 5 days) show a systematic variation of their altitude as function of the center-limb distance.