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KMID : 1144120220120030239
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Biomedical Engineering Letters
2022 Volume.12 No. 3 p.239 ~ p.250
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Miniaturization for wearable EEG systems: recording hardware and data processing
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Kim Min-Jae
Yoo Seung-Jae
Kim Chul
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Abstract
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As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices. Recently, because of the intertwined relationship between EEG recording and processing, co-research of EEG recording hardware and data processing has been emphasized for whole-in-one miniaturized EEG systems. This paper introduces miniaturization techniques in analog-front-end hardware and processing algorithms for such EEG systems. To miniaturize EEG recording hardware, various types of compact electrodes and mm-sized integrated circuits (IC) techniques including artifact rejection are studied to record accurate EEG signals in a much smaller manner. Active electrode and in-ear EEG technologies are also researched to make small-form-factor EEG measurement structures. Furthermore, miniaturization techniques for EEG processing are discussed including channel selection techniques that reduce the number of required electrode channel and hardware implementation of processing algorithms that simplify the EEG processing stage.
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KEYWORD
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Electroencephalography (EEG), Miniaturization, Integrated circuits (IC), Active electrode, In-ear EEG, Channel selection, Hardware implementation, Field-programmable gate array (FPGA)
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