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Project

Distributed signal processing algorithms for auditory attention detection with chronic EEG sensor networks

Electroencephalography (EEG) is a non-invasive neuromonitoring technique, with potential use for chronic daily-life monitoring. A variety of miniature EEG devices have been proposed for chronic use, but these typically measure only a few EEG channels over a highly localized area, which is insufficient for many potential chronic-EEG applications. In this project, we aim to overcome this problem by deploying a multitude of such miniature EEG modules onto the scalp, and let them communicate over wireless links in a sensor network-like architecture. To reduce energy consumption to viable levels, we will develop distributed EEG signal processing algorithms where the EEG signals are processed locally at each module, while exchanging compressed data with the other modules. For the algorithm design, we will focus on the use case of EEG-based auditory attention dete ction, which has applications in future neuro-steered hearing prostheses.
Date:1 Oct 2016 →  30 Sep 2020
Keywords:auditory attention detection
Disciplines:Modelling, Biological system engineering, Signal processing