The study of the brain bioelectrical activities in terms of deterministic nonlinear dynamics is
quite recent -. Perspectives of clinical use of the nonlinear tools range from an augmented
predictive classi cation of Alzheimer's desease  to the possibility of controlling epileptic
activity . However, the nonstationarity of the brain states plus the poor Signal-to-Noise
Ratio (SNR) due to the large amount of brain processes active at the same time have forbidden
so far a generally accepted procedure to estimate suitable indicators , , . Whence the
need for a suitably tailored lter able to extract the activity under study to avoid contamination
between noise and bioelectrical activities while maintaining a su cient number of data to
perform indicator calculations.
The reason for this communication is twofold. We apply for the rst time a novel ltering
technique based on the local features of the wavelet transformation  and, second, we propose
a procedure for brain signal processing, making use of available nonlinear tests.
The procedure here suggested estimates the presence of determinism in a magnetoencephalogram
using the newly developed test , then, whenever allowed, it calculates the correlation
dimensions (CD)  and tests the validity of the calculation. We will show that, while the
measured signal contains deterministic activity, it is not possible to reasonably estimate the
CD, for which we nd, however, an upper bound of 7.