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Abstract-In this paper, a signal processing algorithm to detect eye movements is developed. The algorithm works with two kinds of inputs: derivative and amplitude level of electrooculographic signal. Derivative is used to detect signal edges and the amplitude level is used to filter noise. Depending of movement direction, different kinds of events are generated. Events are associated with a movement and its route. A hit rate equal to 94% is reached. This algorithm has been used to implement an application that allows computer control using ocular movement.

Analytical solutions of dispersion relations in the nucleon-nucleus optical model have been found for both volume and surface potentials. For the energy dependence a standard Brown-Rho function has been assumed for both the volume and surface imaginary contributions multiplied in this later case by a decreasing exponential function. The solutions are valid for any even value of the powers appearing in these functional forms. DOI: 10.1103/PhysRevC.67.067601 PACS number͑s͒: 11.55.Fv, 24.10.Ht Mahaux and co-workers ͓1-5͔ have shown how the study of the nuclear mean field may benefit from the use of dispersion relations. These are mathematical expressions that link certain contributions to the real and imaginary components of the optical model potential ͑OMP͒. The constraint imposed by these dispersion relations helps in reducing ambiguities in the construction of phenomenological potentials from fits to the experimental data. We refer specifically to the so-called dispersive contribution ⌬V, which adds dynamical content to the otherwise static ͑and real͒ Hartree-Fock potential term V HF .Under favorable conditions of analyticity in the complex E plane, the real part ⌬V can be constructed from the knowledge of the imaginary part W of the mean field on the real axis through the dispersion relationwhere we have explicitly indicated the radial and energy dependence of these quantities. Assuming that ⌬V(r,EϭE F ) ϭ0, where E F is the Fermi energy, Eq. ͑1͒ can also be written in the subtracted form ͑2͒This transformation is difficult to implement in practice if the geometry of the dispersive potential depends on the energy. To simplify the problem, however, the shapes of the different components of the OMP are usually assumed to be energy independent and they are expressed in terms of a WoodsSaxon function f WS or its derivative. In such case the radial functions factorize out of the integrals and the energy dependence is completely accounted for by two overall multiplicative strengths ⌬V(E) and W(E). Both of these factors contain, we note, volume and surface contributions. It is customary to represent the variation with energy of the volume and surface components of the imaginary potential by functional forms that are suitable for an optical model analysis that exploits dispersion relations. An energy dependence for the imaginary volume term has been suggested by Brown and Rho in studies of nuclear matter ͓6͔,where A V and B V are constants. Brown and Rho proposed nϭ2, while Mahaux and Sartor ͓2͔ suggest, for the same expression, nϭ4. An energy dependence for the imaginarysurface term has also been investigated by Delaroche et al ͓7͔, who use the formwhere mϭ2,4 and A S ,B S , C S are constants. According to Eqs. ͑3͒ and ͑4͒ the imaginary part of the OMP turns out to be zero at EϭE F and nonzero elsewhere. A more realistic parametrization of W V (E) and W S (E) forces these quantities to be zero in some interval around the Fermi energy. A reasonable range for such a region is measured by the average energy of the si...

A spherical optical model potential ͑OMP͒ containing a dispersive term is used to fit the available experimental database of () and T for nϩ 27 Al covering the energy range 0.1-250 MeV using relativistic kinematics and a relativistic extension of the Schrödinger equation. A dispersive OMP with parameters that show a smooth energy dependence and an energy-independent geometry are determined from fits to the entire data set. A very good overall agreement between experimental data and predictions is achieved up to 150 MeV. Inclusion of nonlocality effects in the absorptive volume potential allows one to achieve an excellent agreement up to 250 MeV.

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Attentional biomarkers in attention deficit hyperactivity disorder are difficult to detect using only behavioural testing. We explored whether attention measured by a low-cost EEG system might be helpful to detect a possible disorder at its earliest stages. The GokEvolution application was designed to train attention and to provide a measure to identify attentional problems in children early on. Attention changes registered with NeuroSky MindWave in combination with the CARAS-R psychological test were used to characterise the attentional profiles of 52 non-ADHD and 23 ADHD children aged 7 to 12 years old. The analyses revealed that the GokEvolution was valuable in measuring attention through its use of EEG–BCI technology. The ADHD group showed lower levels of attention and more variability in brain attentional responses when compared to the control group. The application was able to map the low attention profiles of the ADHD group when compared to the control group and could distinguish between participants who completed the task and those who did not. Therefore, this system could potentially be used in clinical settings as a screening tool for early detection of attentional traits in order to prevent their development.

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