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an alternative in the EEG data processing is to
perform an analysis of the Power Spectral Density
(PSD). PSD is a very useful tool to know
frequencies and amplitudes of oscillatory signals in
the time series data. In line with it, Kusmaryanto
(2013) stated that the PSD to show the amount of
energy per unit based on the frequency and output-
frequency components of different outcomes.
Power spectral density function (PSD) shows the
strength of the variations (energy) as a function of
frequency. In other words, it shows at which
frequencies variations are strong and at which
frequencies variations are weak. The unit of PSD is
energy (variance) per frequency (width) and you can
obtain energy within a specific frequency range by
integrating PSD within that frequency range Cygnus
Research International (2017).
Based on that, this paper will explain how the
use of PSD to measure the concentration of reading
through the data recorded using EEG. Through this
analysis also expected to be found data related to the
measurement result of reading concentration.
Studies on EEG have been widely practiced.
However, a particular study of reading power
concentration has not been done. EEG research
focuses mainly on two things: time scale and Fourier
transform.
The analysis performed to measure EEG data
primarily to measure the strength of electrical
signals at a particular frequency is to use power
spectral density (PSD) analysis. The PSD analysis
uses Fourier transforms rather than time series.
Valipour, Shaligram, and Kulkarni (2014) state that
“the power spectral density (PSD), explain how the
power or energy of a signal is distributed across
frequency”. This term related to Fourier transform.
Hence PSD is frequency domain analysis.
Any physical signal in Fourier transform can be
decomposed into a number of discrete frequencies,
or a spectrum of frequencies over a continuous
range. Xizheng, Ling, and Weixiong (2011) state
that “Fourier transformation have been used to
analyze the pattern of EEG characteristics and non-
transient EEG activity”.
To describe and interpret the results of recording
and measurement of reading concentration power in
this study used two main theories, namely:
neurolinguistics theory and brain wave interpretation
theory. Neurolinguistics theory adapted from Caplan
(1987) and Ingram (2007). Meanwhile, the brain
wave theory was adapted from Stern and Engel,
(2005), and Tatum (2014).
2 METHODOLOGIES
This research uses descriptive method. The elements
described are interpretations of EEG recording
results, including brain wave and brain mapping
through neurolinguistics analysis. Data collection
using Open Brain Computer Interface by utilizing 16
respondents consisting of 8 men and 8 women from
Department of Indonesian Language and Literature
Education.
The recordings use 4 EEG channels with a
maximum impedance of 15Ω. Data processing using
MATLAB based application, EEGLab. We record
electrical signals in the brain through electrodes
mounted under 10-20 International System, i.e.
Frontal polar 1 (Fp1), Frontal polar 2 (Fp2),
Occipital 1 (O1), Occipital 2 (O2), Ear 1 (A1) and
Ear 2 (A2) (see figure 1).
Figure 1: 10-20 international system.
The EEG data collection procedure for
describing students' concentration on reading
activity is done through the following steps.
• EEG data recording at the time of reading
activity;
• Numbering on the respondents' EEG
recordings by sex, data collection sequence,
respondent code number, and
• Re-examination of EEG data recording
results.
After the recording process is done, the EEG
data is then interpreted. Raw EEG data is processed
through EEGLab. EEGLab is a toolbox and graphic
user interface running under the cross-platform
MATLAB environment for processing of EEG data
of any number of channels. Raw data is filtered at
15-18Hz, and analyzed through Power Spectral
Density (PSD).
Can Power Spectral Density (PSD) be used to Measure Reading Concentration?
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