The objective of this study was to explore suitable spatial filters for inverse estimation of cortical potentials from the scalp electroencephalogram. The effect of incorporating noise covariance into inverse procedures was examined by computer simulations. The parametric projection filter, which allows inverse estimation with the presence of information on the noise covariance, was applied to an inhomogeneous three-concentric-sphere model under various noise conditions in order to estimate the cortical potentials from the scalp potentials. The present simulation results suggest that incorporation of information on the noise covariance allows better estimation of cortical potentials, than inverse solutions without knowledge about the noise covariance, when the correlation between the signal and noise is low. The method for determining the optimum regularization parameter, which can be applied for parametric inverse techniques, is also discussed.

In the present paper we shall examine the real-time restoration of biomedical signals under additive noises. Biomedical signals measured by instruments such as catheter manometers, ambulatory electrocardiographs and thermo-dilution sensors are susceptible to distortion and noise. Therefore, such signals must be restored to their original states. In the present study, nonstationary biomedical signals are observed and described using a mathematical model, and several restoration filters that are composed of a series of applications of this model are proposed. These filters restored band-limited approximations of the original signals in real-time. In addition, redundancy is introduced into these restoration filters in order to suppress additive noise. Finally, an optimum filter that accounts for restoration error and additive noise is proposed.

A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two surface electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Four directional cursor movements --up, down, right, and left-- and one selected operation were realized by logically combining the two detected channel signals based on threshold settings specific to the individual. Letter input experiments were conducted on a virtual screen keyboard. The method's usability was enhanced by minimizing the number of electrodes and applying training to both the subject and the device. As a result, an accuracy of 90.1 3.6% and a processing speed of 7.7 1.9 letters/min. were obtained using our method.

We investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.