Amperometric determination of bonded glucose with an MnO(2) and glucose oxidase bulk-modified screen-printed electrode using flow-injection analysis.

A screen-printed amperometric biosensor based on carbon ink double bulk-modified with MnO(2) as a mediator and glucose oxidase as a biocomponent was investigated for its ability to serve as a detector for bonded glucose in different compounds, such as cellobiose, saccharose, (-)-4-nitrophenyl-beta-d-glucopyranoside, as well as in beer samples by flow-injection analysis (FIA). The biosensor could be operated under physiological conditions (0.1M phosphate buffer, pH 7.

Electron binding capabilities of some silylenes having small singlet-triplet splittings or triplet ground states.

Several silyl and alkaline metal substituted silylenes have been investigated using the CAS-ACPF method in conjunction with the aug-cc-pVTZ basis sets. Silylsilylene and disilylsilylene are found to have singlet ground states with DeltaEST(-) values of 0.676 and 0.

Singlet-triplet splittings and ground- and excited-state electron affinities of selected cyanosilylenes, XSiCN (X = H, F, Cl, CH3, SiH3, CN).

Several cyanosilylenes, XSiCN, (X = H, F, Cl, CH3, SiH3, CN) have been investigated using the RHF-ACPF and CAS(2,2)-ACPF methods in conjunction with the aug-cc-pVTZ basis sets. All silylenes are found to have singlet ground states. The ground-state electron affinities are found to be rather high, i.

On-line EEG classification during externally-paced hand movements using a neural network-based classifier.

EEGs of 6 normal subjects were recorded during sequences of periodic left or right hand movement. Left or right was indicated by a visual cue. The question posed was: 'Is it possible to move a cursor on a monitor to the right or left side using the EEG signals for cursor control?' For this purpose the EEG during performance of hand movement was analyzed and classified on-line.

Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns.

The paper describes work on the brain--computer interface (BCI). The BCI is designed to help patients with severe motor impairment (e.g.

Discrimination between phase-locked and non-phase-locked event-related EEG activity.

Differentiation between phase-locked and non-phase-locked event-related EEG activity is an important task in the evaluation of event-related EEG activity. Event-related changes of EEG activity such as event-related desynchronization (ERD) or event-related synchronization (ERS) can be quantified by either instantaneous band power or intertrial variance calculations. In the former case the ERD or ERS can be masked by an event-related potential while in the latter it is not.

40-Hz oscillations during motor behavior in man.

40-Hz oscillations were measured during finger, toe and tongue movement using an electrode array of 56 electrodes over the pre and post central areas. Each movement was made 150 times in intervals of 12 s. The average power increase in narrow frequency bands between 8 and 40 Hz was then calculated and the topographical distribution studied.

EEG classification by learning vector quantization.

EEG classification using Learning Vector Quantization (LVQ) is introduced on the basis of a Brain-Computer Interface (BCI) built in Graz, where a subject controlled a cursor in one dimension on a monitor using potentials recorded from the intact scalp. The method of classification with LVQ is described in detail along with first results on a subject who participated in four on-line cursor control sessions. Using this data, extensive off-line experiments were performed to show the influence of the various parameters of the classifier and the extracted features of the EEG on the classification results.