Improving mental task classification by adding high frequency band information.

Features extracted from delta, theta, alpha, beta and gamma bands spanning low frequency range are commonly used to classify scalp-recorded electroencephalogram (EEG) for designing brain-computer interface (BCI) and higher frequencies are often neglected as noise. In this paper, we implemented an experimental validation to demonstrate that high frequency components could provide helpful information for improving the performance of the mental task based BCI. Electromyography (EMG) and electrooculography (EOG) artifacts were removed by using blind source separation (BSS) techniques. Frequency band powers and asymmetry ratios from the high frequency band (40-100 Hz) together with those from the lower frequency bands were used to represent EEG features. Finally, Fisher discriminant analysis (FDA) combining with Mahalanobis distance were used as the classifier. In this study, four types of classifications were performed using EEG signals recorded from four subjects during five mental tasks. We obtained significantly higher classification accuracy by adding the high frequency band features compared to using the low frequency bands alone, which demonstrated that the information in high frequency components from scalp-recorded EEG is valuable for the mental task based BCI.

A multi-channel magnetic induction tomography measurement system for human brain model imaging.

This paper proposes a multi-channel magnetic induction tomography measurement system for biological conductivity imaging in a human brain model. A hemispherical glass bowl filled with a salt solution is used as the human brain model; meanwhile, agar blocks of different conductivity are placed in the solution to simulate the intracerebral hemorrhage. The excitation and detection coils are fixed co-axially, and the axial gradiometer is used as the detection coil in order to cancel the primary field. On the outer surface of the glass bowl, 15 sensor units are arrayed in two circles as measurement parts, and a single sensor unit for cancelling the phase drift is placed beside the glass bowl. The phase sensitivity of our system is 0.204 degrees /S m(-1) with the excitation frequency of 120 kHz and the phase noise is in the range of -0.03 degrees to +0.05 degrees . Only the coaxial detection coil is available for each excitation coil; therefore, 15 phase data are collected in each measurement turn. Finally, the two-dimensional images of conductivity distribution are obtained using an interpolation algorithm. The frequency-varying experiment indicates that the imaging quality becomes better as the excitation frequency is increased.

[Analytical method for the potential distribution of head sphere model under the stimulation of point current source].

The 4-layer sphere model of human head was built; the layers from outside to inside represented the scalp, the skull, the CFS and the brain, respectively. The point current source placed on the outmost layer was regarded as the boundary condition, and the method of separation of variables was used to solve the equations. The potential distribution and the current expression were given, and the isopotential-line map and current lines were drawn. The simulation result can be used to analyze head EIT problems.