< Back to previous page

Project

Distributed digital signal processing algorithms for highdensity wireless EEG sensor networks with application to ASSR based objective hearing thresholds estimation

Electroencephalography (EEG) is used to analyze brain activity and detect brain responses to specific stimuli. It offers a high temporal resolution versus a low spatial resolution. A higher spatial resolution may be obtained by adopting a higher electrodes density together with powerful digital signal processing (DSP) algorithms. However, hundreds of electrodes then have to be wired to an output device that collects and processes all the electrode signals, which becomes impractical due to various constraints.

The project aims to design novel distributed DSP algorithms for next generation high-density EEG systems that are conceived as wireless sensor networks (WSNs). A collection of WSN nodes is then used, where each node contains a cluster of electrodes and has communication and processing facilities. Communication and cooperation amongst the nodes then allows distributing the signal processing task over the WSN and reducing the number of signals eventually transmitted from the nodes to the output device. The overall target is to achieve the performance of a fully centralized processing, with a significantly reduced communication as well as computational cost. To assess the potential of the developed algorithms in a concrete context, auditory steadystate response (ASSR) detection is considered to estimate hearing thresholds in newborns. The goal is then to conceive a high-density EEG based detection that is more robust and timeefficient than current systems.

Date:1 Oct 2013 →  30 Sep 2015
Keywords:ASSR based objective hearing, EEG sensor
Project type:PhD project