Chapter 3
EEG Spectral Analysis
Do-Won Kim and Chang-Hwan Im
Abstract Electroencephalogram (EEG) spectral analysis quantifies the amount of
rhythmic (or oscillatory) activity of different frequency in EEGs. Based on numerous
studies that reported significant relationship between the EEG spectrum and human
behavior, cognitive state, or mental illnesses, EEG spectral analysis is now accepted
as one of the principal analysis methods in the field of neuroscience. Despite the
tremendous amount of research related to its usefulness, EEG spectral analysis still
exhibits inconsistent results among studies. This might be partly because of the
various methodological decisions the researchers have to make during EEG spectral
analysis. Indeed, there is no standardized analysis procedure. In this chapter, we cover
some background principles of spectral analysis and introduce important issues that
researchers must consider during EEG spectral analysis.
3.1 Introduction
The human electroencephalogram (EEG) is one of the most complex sets of biomedical signals. It is believed to reflect a variety of processes of the brain, especially the
neocortex, in which our cognitive function and sensorimotor information are processed. Since the first report of successful recording of the human EEG by neuropsychiatrist Hans Berger [6, 12], the EEG has been used extensively to help understand
the functions of the brain. Although we still do not have enough understanding to
describe every detail of the brain’s dynamics, extensive neuroscience studies provide
us with pieces of information on how the human brain operates in certain conditions,
e.g., reaction to a given stimulus.
EEGs can be analyzed qualitatively, as Berger did in his report on the human EEG,
or quantitatively, by using various computational EEG analysis methods. Qualitative
D.-W. Kim (B)
Department of Biomedical Engineering, Chonnam National University, Yeosu, South Korea
e-mail: dowon.kim@jnu.ac.kr
C.-H. Im
Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
© 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_3
35
EEG Spectral Analysis
Do-Won Kim and Chang-Hwan Im
Abstract Electroencephalogram (EEG) spectral analysis quantifies the amount of
rhythmic (or oscillatory) activity of different frequency in EEGs. Based on numerous
studies that reported significant relationship between the EEG spectrum and human
behavior, cognitive state, or mental illnesses, EEG spectral analysis is now accepted
as one of the principal analysis methods in the field of neuroscience. Despite the
tremendous amount of research related to its usefulness, EEG spectral analysis still
exhibits inconsistent results among studies. This might be partly because of the
various methodological decisions the researchers have to make during EEG spectral
analysis. Indeed, there is no standardized analysis procedure. In this chapter, we cover
some background principles of spectral analysis and introduce important issues that
researchers must consider during EEG spectral analysis.
3.1 Introduction
The human electroencephalogram (EEG) is one of the most complex sets of biomedical signals. It is believed to reflect a variety of processes of the brain, especially the
neocortex, in which our cognitive function and sensorimotor information are processed. Since the first report of successful recording of the human EEG by neuropsychiatrist Hans Berger [6, 12], the EEG has been used extensively to help understand
the functions of the brain. Although we still do not have enough understanding to
describe every detail of the brain’s dynamics, extensive neuroscience studies provide
us with pieces of information on how the human brain operates in certain conditions,
e.g., reaction to a given stimulus.
EEGs can be analyzed qualitatively, as Berger did in his report on the human EEG,
or quantitatively, by using various computational EEG analysis methods. Qualitative
D.-W. Kim (B)
Department of Biomedical Engineering, Chonnam National University, Yeosu, South Korea
e-mail: dowon.kim@jnu.ac.kr
C.-H. Im
Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
© 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_3
35