Analyzing Brainwaves While Listening To Quranic Recitation Compared With Listening To Music Based on EEG Signals

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International Journal on Perceptive and Cognitive Computing (IJPCC) Vol 1, Issue 1 (2015)
Page xx
Analyzing Brainwaves While Listening To Quranic Recitation
Compared With Listening To Music Based on EEG Signals
Sabaa Ahmed Yahya Al-Galal, Imad Fakhri Taha Alshaikhli
Dept of Computer Science, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
aljalalsaba@gmail.com
Dept of Computer Science, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
imadf@iium.edu.my
Abstract—the electroencephalogram (EEG) is an acquiring of the electrical fluctuations that occur in the
brain, generated simply by positioning electrodes over the scalp with amplification of the electrical
potential produced. The actual EEG indicates three primary types of wave, named alpha, beta and delta,
which are distinct based on their rate of production. Data has been collected from twenty five subjects
using BrainMarker EEG hardware and software. Brainwaves were measured, focusing on the Alpha and
Beta bands to measure subjects’ calmness while listening to Quran recitation compared with relaxing
music. The result showed that higher alpha magnitudes were generated during listening to Quran
recitation.
Keywords— EEG , Brainwaves, Alpha, Beta, Quran recitation, Relaxing music.
I. INTRODUCTION
Brainwaves is becoming an important induction of the
peoples’ stress level, Electrophysiology is the area
associated with physiology that is concerned with the
electrical phenomena related to the nervous system as well
as other physiological activities. Recently numerous studies
shed the light on investigating the brainwaves through
recorded EEG. The outcomes of such studies can be very
useful in many aspects, particularly emotional and
physiological health issues [1]-[3]. In this research, we aim
to investigate how Quran recitation as sound therapy can
reduce levels of stress and anxiety for subjects compared
with relaxation music by analysing acquired EEG signals.
II. RELATED STUDIES
Electroencephalograms signals are categorized into five
types of waves (delta, theta, alpha, beta and gamma) [4].
According to the aforementioned reference, alpha wave
frequencies lie between 8-13 Hz and are associated with
relaxed awareness. Most subjects produce alpha waves
while relaxed with their eyes closed. Beta waves (14-26 Hz)
are associated with active thinking and external focus.
Waves greater than 26 Hz are called Gamma waves or
sometimes fast Beta waves; the amplitudes of these
rhythms are very low, and their occurrence is rarely
observed. Detection of these rhythms can be used to
confirm certain brain diseases.
One major theory of emotions proposes that EEG can be
used to categorize a basic set of human emotions [5]. Each
emotion is distinct from other emotions as perceived by its
psychological and physiological manifestations.
Fig. 1 Brainwave frequency bands
According to Russell, emotions are allocated at the two-
dimensional circle space, comprised of arousal and valence
dimensions. Arousal presents the vertical axis, and valence
presents the horizontal axis; as you move to the centre of
the circle, it presents a neutral valence and a medium level
of arousal. On this model, emotional states are represented
with any specific level of valence and arousal. The
Circumplex model has been used most commonly to test
stimuli of emotional facial expressions, audio and affective
states [6].
According to [4], EEG signals show higher Alpha waves
and low Beta waves while listening to Quran recitation. In
contrast, Beta waves are higher when listening to hard
music. Another study compared the Alpha waves for
subjects listening to Quran recitation and classical music;
the result showed that 12.67% of samples demonstrate an
improvement in the Alpha band during Quran recitation,
while 9.97% of samples do for classical music [7].

International Journal on Perceptive and Cognitive Computing (IJPCC) Vol 1, Issue 1 (2015)
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III. METHODOLOGY
The methodology of this study is divided into two mean
directions; first is the experiment and data collection, and
next is the data analysis.
A. Experiment setup
Following are the main steps in our experiment:
1) Material: In the present study, we employed IAPS [8]
combined with suitable music for each distinct emotion
because it has been asserted that combinations of pictures
and sounds give better effect [9]. For the test stimulus,
there are two sets of excerpts: Quran recitation and
relaxing music. We chose three Quranic excerpts Surat
Yasin and Al-Inshirah, and Al-Mu'awwidhatayn with Al-
Ikhlas lasted one minute each. For music track selection to
the best of our knowledge the following are amongst the
best known types of relaxing music: Mozart Music K448,
New age and Jazz [10]-[12]. The music tracks had been
chosen very carefully according to music websites built using
emotion as a cue for music tracks, such as Musicovery, AMG
and Last.fm. The three tracks were chosen from the calm
quadrant.
TABLE I
TIME FRAME PROTOCOL EEG AND ECG ELECTRODES PLACEMENTS
Eyes Close (EC) (1 Minute)
Eyes Open (EO) (1 Minute)
IAPS
Music Listening [1](EC)(1 Min)
Music Listening [2](EC)(1 Min)
Music Listening [3](EC)(1 Min)
Quran Listening [1](EC)(1 Min)
Quran Listening [2](EC)(1 Min)
Quran Listening [3](EC)(1 Min)
Happy (1 Minute)
Fear (1 Minute)
Sad (1 Minute)
Calm (1 Minute)
2 Min
4 Min
6 Min / Total: 12 Minutes
2) Electrode placements: EEG was acquired by placing
nineteen surface electrodes on the scalp according to the
international 10-20 system (Fp1, Fp2, F7, F8, F3, F4, Fz, T7,
T8, C3, C4, Cz, P7, P8, P3, P4, Pz, O1 and O2) We used
BrainMarker software and Hardware [6] as shown in figure
1. The sampling rate was set to 250 Hz. The impedance was
below 5 KΩ.
3) Participants: Twenty five students (fifteen males, ten
females) from university of International Islamic University
Malaysia participated in the experiment. Before the
experiment began they were asked to fill up provided
informed consent form, all subjects had no personal history
of neurological disorders. They had been given a monetary
for their participation.
4) Procedures: Participants were instructed to set in a
comfortable chair 80-100cm away from laptop screen. They
were asked to stay stable and minimize their movement as
much as possible. The experiment began by eyes closed /
eyes opened lasted one minute each. Then the subjects
instructed to watch IAPS stimuli for four emotions (Happy,
Fear, Sad and Calm) combined with the suitable music
through headphone lasted one minute each. After the
subjects watched emotion stimulus. Then they had been
instructed to close their eyes to minimize eyes blinking
artifacts and muscle movement while listening to the three
excerpts of Quran recitation and to the three excerpts of a
relaxing music through headphone lasted one minute each
as shown in Table I.
Fig. 1 BrainMarker software shows a good quality signals (green light) and
the recorded signal is displayed live.
B. Data Analysis
Figure 2 shows the specific band for each wave and the
condition that they appear on. As demonstrated in the
flowchart in Figure 3, the analysis process started by
importing the signal from the 19-channel EEG signal for all
of the data, including emotions, Quran, music, eyes closed
and eyes opened data. Then, we cut the frequency band for
each wave, and after that, we apply the Butter filter in
MATLAB for each band as in Figure 4, which represents
channel F3 from the happy data for subject one. Finally, we
take the average of the wave vector and plot it, focusing
more on Alpha and Beta waves.
Fig. 3 an example of the brain waves analysis from subject 1 (happy ->
channel F7)

International Journal on Perceptive and Cognitive Computing (IJPCC) Vol 1, Issue 1 (2015)
Page xx
Fig. 3 a flowchart for the analysis procedures for brainwaves
IV. RESULT AND DISCUSSION
As mentioned in the literature, increased alpha wave
activity is definitely a desired outcome for researchers
because alpha waves are essentially dominant when the
mind is in a peaceful and relaxed emotional state or
sometimes in a meditative state—bearing in mind that the
subject is not tired or asleep. In contrast, beta waves are
dominant when the mind is in a normal waking state
involving awareness, when attention is directed towards
cognitive tasks and outward activities.
Beta waves are a fast activity and are found when we are
attentive, alert, involved in problem solving, making
judgements or decisions, and engaged in concentrated
mental activity. The performance of the alpha and beta
waves of subjects’ basic emotions is shown in Table II. To
shed light on the calmness emotion, it is clear that 68% of
the subjects produce a higher alpha magnitude than beta
magnitude. The mean values of the four emotions were
calculated, and the highest value is for the calm alpha band,
which is highlighted with a light green colour in Table II.
These data provide further support to the hypothesis that
higher alpha wave magnitude is associated with calm and
relaxed emotions. We further analysed alpha and beta
brainwaves for the Quran verses and music tracks, and the
results show that the alpha magnitude is higher than the
beta magnitude when listening to the Quranic recitation in
most subjects, as shown in Figure 5.
TABLE III
Alpha and Beta Brain Waves magnitude for four basic
emotions
E
Happy
Calm
Fear
Sad
α &
β
Alpha
Beta
Alpha
Beta
Alpha
Beta
Alpha
Beta
S1
0.00033
0.00054
0.00036
0.00085
0.00024
0.00041
0.00028
0.00046
S2
0.00023
0.00043
0.00026
0.00036
0.00041
0.00023
0.00067
0.00137
S3
0.00080
0.00063
0.00098
0.00027
0.00037
0.00019
0.00065
0.00053
S4
0.00094
0.00108
0.00115
0.00037
0.00097
0.00053
0.00052
0.00053
S5
0.00058
0.00047
0.00071
0.00041
0.00052
0.00076
0.00055
0.00137
S6
0.00042
0.00027
0.00053
0.00037
0.00064
0.00064
0.00039
0.00105
S7
0.00032
0.00050
0.00029
0.00025
0.00025
0.00021
0.00055
0.00033
S8
0.00037
0.00032
0.00033
0.00042
0.00085
0.00024
0.00093
0.00021
S9
0.00037
0.00043
0.00054
0.00028
0.00029
0.00035
0.00084
0.00043
S10
0.00088
0.00058
0.00037
0.00021
0.00047
0.00052
0.00033
0.00049
S11
0.00098
0.00078
0.00186
0.00076
0.00092
0.00051
0.00155
0.00038
S12
0.00026
0.00053
0.00051
0.00044
0.00060
0.00167
0.00027
0.00072
S13
0.00017
0.00037
0.00068
0.00062
0.00044
0.00027
0.00150
0.00117
S14
0.00045
0.00039
0.00083
0.00098
0.00044
0.00051
0.00049
0.00037
S15
0.00059
0.00109
0.00081
0.00020
0.00090
0.00065
0.00118
0.00037
S16
0.00029
0.00053
0.00073
0.00098
0.00018
0.00034
0.00024
0.00038
S17
0.00069
0.00038
0.00039
0.00035
0.00025
0.00024
0.00062
0.00052
S18
0.00043
0.00069
0.00066
0.00095
0.00091
0.00052
0.00049
0.00054
S19
0.00025
0.00084
0.00039
0.00055
0.00026
0.00083
0.00078
0.00097
S20
0.00024
0.00053
0.00066
0.00055
0.00050
0.00072
0.00042
0.00041
S21
0.00037
0.00083
0.00136
0.00030
0.00039
0.00040
0.00025
0.00018
S22
0.00037
0.00063
0.00056
0.00043
0.00082
0.00093
0.00022
0.00079
S23
0.00187
0.0002
0.00025
0.00024
0.00023
0.00038
0.00036
0.00032
S24
0.00113
0.00121
0.00111
0.00090
0.00205
0.00075
0.00058
0.00132
S25
0.00020
0.00029
0.00024
0.00027
0.00029
0.00038
0.00013
0.00040
Avg
0.00054
0.00058
0.00067
0.00049
0.00057
0.00053
0.00059
0.00063
The alpha magnitude is almost as high as the beta
magnitude for many of the subjects for tracks 1 and 2. For
many subjects, track 3 elicited a higher alpha magnitude
than beta magnitude. However, there are exceptions, such
as subjects 3, 9, 10 and 12, who generated higher alpha
magnitudes than beta magnitudes for tracks 1 and 2.
Additionally, subjects 2, 5, 11, 18 and 21 generated higher
alpha magnitudes than beta magnitudes for track 2 but not
for track 1, because of the space limitation so we have just
chosen randomly four subjects.

International Journal on Perceptive and Cognitive Computing (IJPCC) Vol 1, Issue 1 (2015)
Page xx
S1
S8
S15
S4
Fig. 5 Alpha (blue bars) and Beta (red bars) brainwave magnitudes (y-axis)
for Quran verses (Q1, Q2 & Q3) and music tracks (M1, M2 & M3) for four
selected subjects.
The mean alpha and beta brainwaves for the Quran
verses and music tracks were calculated. The results
demonstrate that the alpha magnitude is higher than the
beta magnitude when listening to the Quranic recitation, as
shown in Figure 6. In contrast, the alpha and beta
magnitudes are almost equal for music tracks 1 and 2.
However, the third track showed a higher alpha magnitude
than beta magnitude. Thus, Quranic recitation as sound
therapy can improve brainwaves by generating high alpha
activity, which is related to a resting and calm state. In
contrast, the three selected types of best-known relaxing
music can also generate high alpha brainwaves—but not as
high as Quranic recitation.
Fig. 6 Mean Alpha and Beta brainwaves magnitude for Quran verses
and music tracks for all subjects
V. CONCLUSIONS
Brainwave result analysis showed that Quran data
generates higher alpha magnitudes then beta magnitudes,
which reflects the calmness and relaxation of the subjects
while listening to Quran recitation. Alternately, relaxing
music data generated almost equal beta and alpha
magnitudes, meaning that relaxing music can generate
high alpha but not as high as Quran recitation can.
ACKNOWLEDGMENT
This project has been funded by Ministry of Higher
Education Malaysia (MOHE) under Fundamental Research
Grant Scheme (FRGS14-127-0368).
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0
0.0005
0.001
0.0015
0.002
Q1 Q2 Q3 M1 M2 M3
0
0.0005
0.001
0.0015
Q1 Q2 Q3 M1 M2 M3
0
0.0005
0.001
0.0015
0.002
0.0025
0.003
Q1 Q2 Q3 M1 M2 M3
0
0.001
0.002
0.003
0.004
Q1 Q2 Q3 M1 M2 M3
0
0.0002
0.0004
0.0006
0.0008
0.001
0.0012
Q1 Q2 Q3 M1 M2 M3
Magnitude( μV)
Quran - Music
ALPHA
BETA