Modeling tripolar concentric ring electrode (TCRE) sensor and acquisition of auditory brainstem response

Abstract

Brain activity generates electrical potentials that are spatio-temporal in nature. Electroencephalography (EEG) is the least costly and most widely used noninvasive technique for diagnosing many brain problems. It has high temporal resolution, but lacks high spatial resolution. The surface Laplacian enhances the spatial resolution and selectivity of the surface electrical activity recording. Tripolar concentric ring electrode (TCRE) sensors have been shown to estimate the surface Laplacian directly and have significantly better spatial resolution than conventional electrodes. The EEG electrodes on the scalp transform ionic currents to electrical currents in biological systems. Modeling the electrode-electrolyte interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. There are previous reports of accurate models for single-element biomedical electrode sensors. In this paper we develop a model for the electrode-electrolyte interface for TCRE sensors as well as acquire auditory evoked potentials to demonstrate the utility of TCRE sensors over conventional disc electrode sensors.