Toward construction of an inexpensive brain computer interface for goal oriented applications

The paper describes the implementation of an offline, low-cost Brain Computer Interface (BCI) alternative to more expensive commercial models. Using inexpensive general purpose clinical EEG acquisition hardware (Truscan32, Deymed Diagnostic) as the base unit, a synchronisation module was constructed to allow the EEG hardware to be operated precisely in time to allow for recording of automatically time stamped EEG signals. The synchronising module allows the EEG recordings to be aligned in stimulus time locked fashion for further processing by the classifier to establish the class of the stimulus, sample by sample. This allows for the acquisition of signals from the subject’s brain for the goal oriented BCI application based on the oddball paradigm. An appropriate graphical user interface (GUI) was constructed and implemented as the method to elicit the required responses (in this case Event Related Potentials or ERPs) from the subject.

Single-trial event-related potential analysis for brain-computer interfaces

Abstract. Different types of mental activity are utilised as an input in Brain-Computer Interface (BCI) systems. One such activity type is based on Event-Related Potentials (ERPs). The characteristics of ERPs are not visible in single-trials, thus averaging over a number of trials is necessary before the signals become usable. An improvement in ERP-based BCI operation and system usability could be obtained if the use of single-trial ERP data was possible. The method of Independent Component Analysis (ICA) can be utilised to separate single-trial recordings of ERP data into components that correspond to ERP characteristics, background electroencephalogram (EEG) activity and other components with non- cerebral origin. Choice of specific components and their use to reconstruct “denoised” single-trial data could improve the signal quality, thus allowing the successful use of single-trial data without the need for averaging. This paper assesses single-trial ERP signals reconstructed using a selection of estimated components from the application of ICA on the raw ERP data. Signal improvement is measured using Contrast-To-Noise measures. It was found that such analysis improves the signal quality in all single-trials.

Collaborative grid infrastructure for molecular simulations: The eMinerals minigrid as a prototype integrated computer and data grid

This paper describes a prototype grid infrastructure, called the eMinerals minigrid, for molecular simulation scientists. which is based on an integration of shared compute and data resources. We describe the key components, namely the use of Condor pools, Linux/Unix clusters with PBS and IBM's LoadLeveller job handling tools, the use of Globus for security handling, the use of Condor-G tools for wrapping globus job submit commands, Condor's DAGman tool for handling workflow, the Storage Resource Broker for handling data, and the CCLRC dataportal and associated tools for both archiving data with metadata and making data available to other workers.