Chapter 2
Preprocessing of EEG
Sung-Phil Kim
Abstract Preprocessing of the EEG signal, which is virtually a set of signal processing steps preceding main EEG data analyses, is essential to obtain only brain activity
from the noisy EEG recordings. It has been shown that the design of preprocessing procedures can affect subsequent EEG data analysis outcomes. Preprocessing of
EEG largely includes a number of processes, such as line noise removal, adjustment
of referencing, elimination of bad EEG channels, and artifact removal. This chapter
presents an overview of the methods available for each process and discusses practical considerations for applying these methods to the EEG signals. In particular,
considerable attention is paid to the state-of-the-art artifact removal methods since
there are still plenty of opportunities to enhance the artifact removal techniques for
EEG, in the perspectives of both signal processing and neuroscience. It is desirable
that this chapter provides the readers an overall view of EEG preprocessing pipelines
and serves as a handbook guide for the practice of EEG preprocessing.
2.1 Introduction
Preprocessing of the EEG signal is an indispensable step for the analysis of EEG in
most circumstances. Although there is still a lack of the standard pipeline of EEG
preprocessing [8, 37, 58] it generally includes any necessary digital signal processing
operations to polish up raw EEG signals with an aim to leave only brain activity
signals for subsequent analyses. Often, EEG preprocessing also involves procedures
to enhance spatiotemporal characteristics of the EEG signal related to the task used
in a study [65].
A number of studies have demonstrated the influences of EEG preprocessing on
the subsequent data analysis results [8, 33, 90, 110, 112]. For instance, the classification of different mental states from EEG or the control performance of a brainS.-P. Kim (B)
School of Design and Human Engineering, Ulsan National Institute of Science and Technology,
Ulsan, Republic of Korea
e-mail: spkim@unist.ac.kr
© Springer Nature Singapore Pte Ltd. 2018
C.-H. Im (ed.), Computational EEG Analysis, Biological and Medical Physics,
Biomedical Engineering, https://doi.org/10.1007/978-981-13-0908-3_2
15
Preprocessing of EEG
Sung-Phil Kim
Abstract Preprocessing of the EEG signal, which is virtually a set of signal processing steps preceding main EEG data analyses, is essential to obtain only brain activity
from the noisy EEG recordings. It has been shown that the design of preprocessing procedures can affect subsequent EEG data analysis outcomes. Preprocessing of
EEG largely includes a number of processes, such as line noise removal, adjustment
of referencing, elimination of bad EEG channels, and artifact removal. This chapter
presents an overview of the methods available for each process and discusses practical considerations for applying these methods to the EEG signals. In particular,
considerable attention is paid to the state-of-the-art artifact removal methods since
there are still plenty of opportunities to enhance the artifact removal techniques for
EEG, in the perspectives of both signal processing and neuroscience. It is desirable
that this chapter provides the readers an overall view of EEG preprocessing pipelines
and serves as a handbook guide for the practice of EEG preprocessing.
2.1 Introduction
Preprocessing of the EEG signal is an indispensable step for the analysis of EEG in
most circumstances. Although there is still a lack of the standard pipeline of EEG
preprocessing [8, 37, 58] it generally includes any necessary digital signal processing
operations to polish up raw EEG signals with an aim to leave only brain activity
signals for subsequent analyses. Often, EEG preprocessing also involves procedures
to enhance spatiotemporal characteristics of the EEG signal related to the task used
in a study [65].
A number of studies have demonstrated the influences of EEG preprocessing on
the subsequent data analysis results [8, 33, 90, 110, 112]. For instance, the classification of different mental states from EEG or the control performance of a brainS.-P. Kim (B)
School of Design and Human Engineering, Ulsan National Institute of Science and Technology,
Ulsan, Republic of Korea
e-mail: spkim@unist.ac.kr
© Springer Nature Singapore Pte Ltd. 2018
C.-H. Im (ed.), Computational EEG Analysis, Biological and Medical Physics,
Biomedical Engineering, https://doi.org/10.1007/978-981-13-0908-3_2
15