AN EVALUATION OF THE RELAXATION EFFECT

OF MUSIC BASED ON THE RELATIONSHIPS BETWEEN THE

CONDITION OF PULSE AND MUSIC TEMPO USING THE EEG

AND HRV BASED INDICATORS

Genki Murayama*, Shohei Kato*, Hidenori Itoh* and Tsutomu Kunitachi**

*Dept. of Computer Science and Engineering, Graduate school of Nagoya Institute of Technology

Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan

**Dept. of Computer Science and Art, Daido Institute of Technology, 10-3 Takiharu-cho, Minami-ku, Nagoya, 457-8530, Japan

Keywords:

Music tempo, relaxation, EEG, HRV.

Abstract:

This paper attempt to investigate the relationships between relaxation effect of music and rhythm of human

body (in this paper ﬁngerplethysmogram (so called ”pulse”) is adopted) using EEG and HRV based two relax-

ation indicators. We focus on following viewpoints: synchronization between pulse and music, the tendency of

pulse beat and pulse-music tempo ratio (µ). This paper reports the experimental results that the pulse decreas-

ing state is effective for EEG based indicator while HRV based indicator is high value at the pulse increasing

state. Furthermore, we classify subjects into 3 groups by the analysis of synchronization between pulse and

music tempo. This papar also reports the analysis of relationships between pulse-music tempo ratio (µ) and

relaxation effect under the classiﬁcation.

1 INTRODUCTION

Nowadays, ”Kansei” (emotion, feelings) evaluation

has become more important keyword because many

products are used by human and its feeling effects

good or bad impression for the user. Many re-

searchers are now researching the design and another

factors bringing us better feelings. However, it is dif-

ﬁcult to evaluate emotions because there are too many

variations in ”emotion” and there is no general way to

describe it. On the other hand, the objective way of

evaluating emotion is studied in many institutes using

bio signals. To evaluate the feelings, many indica-

tors are adopted. For example, brain wave is popular

one. Alpha wave of brain waves is usually adopted

as a indicator of relaxation. In the ”Kansei” eval-

uation, a study about relaxation effect is performed

ﬂourishingly because many people needs relaxation

in this demanding society. We focused on the re-

laxation effect of music because we can get the mu-

sic relaxation easily sitting at the sofa in the house

and no any special equipment is needed. (T. Naka-

mura, 2002) described the relationships between the

tone of the sound and power spectrum of the alpha

wave using electroencephalography (EEG). On the

other hand, investigation on musical tempo and im-

pression change using subjective valuation has been

reported (K. Kurashima, 2004). In the other case, the

substance in saliva is used as a indicator of stresses.

Music research is also performed in many viewpoints

because music has so many elements: rhythm, tempo,

harmony, instrumental and more. Various researches

focused on the music tempo has been reported. For

example, synchronization between pulse and music

tempo is described in (M. Fukumoto, 2004). The pa-

per stated that synchronization effect is related to re-

laxation effect calculated from heart rate variability.

In this paper, we try to investigate the relaxation ef-

fect of music based on the relationships between the

rhythm of human body and music tempo in addition

to synchronization effect, and report many empirical

results about relaxation effect.

2 SUBJECT OF ANALYSIS

Relaxation indicators:

In this paper, we adopted electroencephalography

(EEG) and heart rate variability (HRV) to calcualte

relaxation indicators. EEG analysis was performed

using the HSK central rhythm monitor system devel-

314

Murayama G., Kato S., Itoh H. and Kunitachi T. (2008).

AN EVALUATION OF THE RELAXATION EFFECT OF MUSIC BASED ON THE RELATIONSHIPS BETWEEN THE CONDITION OF PULSE AND

MUSIC TEMPO USING THE EEG AND HRV BASED INDICATORS.

In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing, pages 314-319

DOI: 10.5220/0001063603140319

 SciTePress

Figure 1: Brain wave and pulse sensor.

oped by Human Sensing Inc in Japan.

This equipment measures the Fp1 and Fp2 chan-

nels of the EEG and estimates the Comfortable-

Degree (CD) (Yoshida, 2000). Ordinarily, EEG is

measured with the International 10:20 method, but we

adopted the method described in (Yoshida, 2000) be-

cause it lightens a burden of the subject. We used the

content ratio of high frequency (HF) as the HRV indi-

cator calculated from the ﬁnger plethysmogram (sim-

ply called, pulse).

• Comfortable-Degree

We used Comfortable-Degree as an indicator of

relaxation at brain. This indicator is calcu-

lated from the frequency ﬂuctuation of the brain

waves. Tomoyuki Yoshida tried to make a in-

dicator of comfortable-feelings (Yoshida, 2000).

He insisted that human psychological condition

changes every time if the physical situation was

same. So we have to evaluate the ﬂuctuation of

the human emotion in an objective way. The re-

search groups performed the experiment that ex-

hibit many good or bad smells, sounds and musics

for the subject and investigated the ﬂuctuation of

the alpha wave frequency. According to the result,

the gradient of the spectrum of brain waves in the

left frontal area is get closed to 1.0 in the situation

of comfortable. Conversely, that is get closed to

0 in the situation of uncomfortable. On the other

hand, the gradient of the spectrum of brain wave

in the right frontal area is get closed to 0 in the

condition of subject felt awakening. As a result,

the expression of comfortable degree is consisted

below.

CD(%) =

Fp1

slope

+ Fp2

slope

/2∗ 100, (1)

where F p1

slope

and Fp2

slope

mean the gradient of

the spectrum of alpha wave in Fp1 and Fp2 chan-

nel, respectively.

• Content Ratio of HF

Our heart beat is varying every time and R-R In-

terval (peak to peak) also changes every time.

Many researches focused on this phenomenon

clariﬁed that the changes of R-R interval is re-

lated to autonomic nerve system (Task Force of

the European Society of Cardiology, 1996). This

evaluation method is called Heart Rate Variability

(HRV). The method is performed following steps.

– calculate R-R interval from pulse data (shown

in Figure 2).

Figure 2: A sample of pulse data.

– generate an interpolated R-R interval line

(shown in Figure 3).

Figure 3: Interpolated R-R line.

– Apply the Coarse Graining Spectral Analysis

(CGSA) (Y. Yamamoto, 1991)(Y. Yamamoto,

1993) to make the indicator of autonomic nerve

system clear.

– In CGSA method, FFT is performed to obtain

the frequency power spectrum.

– separate the spectrum into Low frequency

(From 0.024 Hz to 0.15 Hz) and High fre-

quency (From 0.15 Hz to 0.6 Hz).

We used Content Ratio of HF as an indicator of

relaxation at body. LF/HF is used as an indicator

of the sympathetic nervous system (SNS). Con-

tent ratio of HF, i.e., HF/(HF+LF), is used as an

indicator of the parasympathetic nervous system

(PNS) that is also used as a relaxation indicator

because parasympathetic nervous system is dom-

inant during relaxation. We calculated the content

ratio of HF by the HRV method from the pulse.

Relationships between pulse and music:

• Synchronization between pulse and music tempo

(Y. Kusunoki, 2003) stated the synchronization

phenomenon between pulse and music tempo

AN EVALUATION OF THE RELAXATION EFFECT OF MUSIC BASED ON THE RELATIONSHIPS BETWEEN

THE CONDITION OF PULSE AND MUSIC TEMPO USING THE EEG AND HRV BASED INDICATORS

315

Figure 4: Spectrum of HF/LF valance (in rest).

Figure 5: Spectrum of HF/LF valance (in tilt).

(Later, it is simply called as ”synchronization”)

as a relationship between pulse and music tempo.

(M. Fukumoto, 2004) explained that synchroniza-

tion period is the period where the ratio between

heart rate and the number of music beats is kept

constant, and indicated that a total of the short

synchronization periods in the music experiment

were signiﬁcantly larger than in the control exper-

iment. For example, a state that the subject’s pulse

beats 3 times while a certain music played in one

musical unit continues for a certain period of time

(see Figure 6).

Figure 6: Example of synchronization.

To analyze the synchronizationbetween pulse and

music tempo, we adopted the method described

in (Y. Kusunoki, 2003). The data (relaxation in-

dicator) obtained are classiﬁed into three groups:

no sound, no synchronization, pulse and music

synchronization. In addition to this classiﬁcation,

no synchronization state is further more classiﬁed

into two groups; pulse beat increased and pulse

beat decreased.

• Pulse-Music Tempo Ratio

In this paper, we introduce a scale that is called the

pulse-music tempo ratio. By classifying the con-

dition of the subject from the pulse-music tempo

ratio, we can evaluate the relationships between

relaxation indicator and the state of the subject’ s

pulse and the tempo of music. Musical tempo T

in every minute is expressed by the sequence T

(j = t

m+1

,...,M), where j is the minute with

music presence, t

is the starting minute of music

presence, and M is the total minutes of measure-

ment. Subject i’ s average value of each indicator

in the j-th minute is described as CD

i, j

and HF

i, j

The average value of each indicator in all listen-

ing terms is described as

CD and HF. Subject i’ s

average pulse beats in the j-th minute is described

as P

i, j

. Then, we denote the pulse-music tempo

ratio as µ

. The µ

value for subject i is calculated

every minute using the following equation:

= {µ

i,t

,µ

i,t

m+1

,...,µ

i,M

}, (2)

where

i, j

= P

i, j

, (3)

For example, (Reinhaldt, 1999) reported that synchro-

nization is well observed in the 2:3 state of pulse and

music tempo ratio. In this case, 2:3 state of the pulse-

music tempo ratio corresponds to µ = 1.5.

Finally, we deﬁne the efﬁciency values τ

and

for each indicator calculated from the following

equations:

(µ) =

i=1

j=t

{s(µ

i, j

,µ)comp(HF

i, j

HF)}

i=1

j=t

{s(µ

i, j

,µ)}

, (4)

(µ) =

i=1

j=t

{s(µ

i, j

,µ)comp(HF

i, j

HF)}

i=1

j=t

{s(µ

i, j

,µ)}

(5)

where N is the number of subjects, and

s(µ

,µ

) = {

1 (0 ≤ µ

− µ

< K)

0 otherwise

, (6)

comp(a,b) = {

1 (a > b)

0 otherwise

(7)

In this deﬁnition, τ is the ratio of the frequency

where each indicator (HF

i, j

, CD

i, j

) is higher than its

average value (

CD, HF ) to the frequency where µ

i, j

is classiﬁed into µ. Function s classiﬁes the condition

of µ

i, j

into each value of the pulse-music tempo ratio

by the appropriate value K.

BIOSIGNALS 2008 - International Conference on Bio-inspired Systems and Signal Processing

316

Figure 7: Experiment environment.

3 EXPERIMENT PROCEDURE

The subjects were 12 males in their 20s (N = 12).

During the experiment, the subjects sat on a sofa and

closed their eyes. The experiment consisted of two

parts. In the ﬁrst 4 min, no sound was presented, and

then music was played for the next 10 min (t

= 5

and M = 14). The experimental environmentis shown

in Figure 7. We presented an MIDI (Musical In-

struments Data Interface) digital ﬁle ’Gymnopedie,

No.1 (E. Satie)’ as the musical stimulus, as used in

(M. Fukumoto, 2004), and the tempo of the music

was gradually decreased from 66 to 48 BPM every

minute. The ﬁlter of the EEG analysis system was ad-

justed to the following settings; low pass ﬁlter: 13 Hz,

high pass ﬁlter: 8 Hz. During the period of the experi-

ment, a ﬁnger plethysmogram (simply called ’Pulse’)

that sampled at 500 Hz was measured from a sub-

ject’s foreﬁnger. The analog data obtained were trans-

lated to digital data and transferred to a PC through an

USB port. To detect the synchronization of musical

tempo and pulse, we adopted the method described

in (Y. Kusunoki, 2003). The output signal from the

MIDI device was transferred to the ampliﬁer through

a ﬁbre optical cable. The volume of sound was ﬁxed

at a level that was not annoying for the subject.

4 RESULTS AND DISCUSSION

4.1 Analysis by Time

Measured average pulse tempo and presented music

tempo is shown in Figure 8. Figure 8 indicate that

the average value of pulse beat decreased 2.9 BPM in

all the listening term, while the change of pulse beat

includes the individual differences.

Figure 8: Music tempo and pulse tempo.

In next section we tried to analyze the relaxation

indicator for each state of the subject using the pulse-

music tempo ratio. According to the variance of the

obtained pulse-music tempo ratio (µ

i, j

), we consid-

ered K = 0.1 to be appropriate to classify µ

i, j

values

in this experiment.

4.2 Analysis by Synchronization

The experimental results have some different tenden-

cies of synchronization. So we classiﬁed observation

type of synchronization into 3 groups (shown in Fig.

9): observed at low ratio, observed at high ratio and

observed in wide range of ratio. In this paper ”ratio”

means the pulse-music tempo ratio.

Figure 9: Classiﬁcation of synchronization.

Experimental result of synchronization were clas-

siﬁed into 3 groups shown in from Fig. 10 to Fig. 12.

The number of person in each groups is following:

• group A(observed at low ratio): 4 subjects

• group B(observed at high ratio): 3 subjects

• group C(observed in wide range of ratio): 5 subjects

AN EVALUATION OF THE RELAXATION EFFECT OF MUSIC BASED ON THE RELATIONSHIPS BETWEEN

THE CONDITION OF PULSE AND MUSIC TEMPO USING THE EEG AND HRV BASED INDICATORS

317

Figure 10: Synchronization observed at low ratio (type A).

Figure 11: Synchronization observed at high ratio (type B).

Figure 12: Synchronization observed at wide ratio (type C).

Figure 13: Synchronization and pulse tendencies and

changes of

CD (each groups).

Figure 14: Synchronization and pulse tendencies and

changes of

HF (each groups).

Synchronizationis observed in spread µ area as shown

in ﬁgures. There is no correlation between synchro-

nization occurrence and pulse-music tempo ratio. But

the pulse-music tempo ratio that synchronization is

well observed exists for each subject and the range

has large individual differences (see Fig. 10, 11 and

12).

Next we considered the tendency of the pulse beat.

In this paper, we adopted the gradient of the instan-

taneous pulse beats in every minute as an indicator

of the pulse beat tendency as well as synchroniza-

tion. Experimental result of Comfortable-degree and

content ratio of HF were classiﬁed into four groups:

no sound, tempo and pulse synchronization, pulse de-

crease at no synchronization, pulse increase at no syn-

chronization, shown in Fig. 13 and 14.

In Figure 13, the changes of Comfortable-degree in

type C (”observed in wide ratio” group) is smaller

than the other groups. The results in Figure 13 says

that Comfortable-degree is higher in both of syn-

chronization state and pulse decreasing state. Fur-

thermore, Comfortable-degreewith listening to music

(involves synchronization and no synchronization) is

higher than no sound state. As well as Comfortable-

degrees, Figure 14 indicates that the changes of con-

tent ratio of HF in type C group is smaller than any

other groups. On the other hand, content ratio of

HF is higher at the synchronization state same as re-

ported in (M. Fukumoto, 2004). Comparing two indi-

cators (Comfortable-degree and content ratio of HF),

the tendency of content ratio of HF is uneven with

Comfortable-degree. The relationships among relax-

ation effect and synchronization and pulse tendency

in all group is shown in Figure 15 and 16.

Figure 15: Sync. pulse tendency and

CD.

Figure 16: Sync. pulse tendency and

HF.

We ﬁrst considered the variance of each relaxation

indicators. The result indicates that HF increases in

the synchronization state, that is same as the result of

each groups. However, the HF value in the no sound

state is higher than that in the pulse decreasing state of

no synchronization. On the other hand, Comfortable-

degree in both the synchronization and no synchro-

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318

nization was higher than that in the no sound state.

This result implies that decreasing of the pulse tempo

is as important as synchronization.

4.3 Analyze by Pulse-music Tempo

Ratio

In this section, we calculated µ

from the pulse tempo

i, j

for all subjects and the musical tempo T

, and the

frequencyratios τ

and τ

from the relaxation indi-

cators (HF

i, j

,CD

i, j

) for all subjects with the following

µ values (µ = 0.8,0.9,1.0,...,1.4).

Figure 17: τ

in each group.

Figure 18: τ

in each group.

At ﬁrst, the relationships between µ and τ

,τ

every groups (see Fig. 9) are shown in Figure 17

and Figure 18. The result in Figure 17 indicate that

the effect for Comfortable-degree in type A group

(”observed at low ratio”) changed constantly in ob-

served pulse-music tempo ratio. In the other groups,

Comfortable-degree was higher in the ratio around

µ = 1.3. In comparison with Comfortable-degree,

content ratio of HF was more effective in lower pulse-

music tempo ratio (around µ = 1.0).

5 CONCLUSIONS

In this paper we reported the relationships among re-

laxation effect, pulse tempo and musical tempo based

on two relaxation indicators. Experimental result in-

dicate that the pulse decreasing state is effective for

comfortable-degree calculated from brain waves as

well as synchronization state. On The other hand,

content ratio of HF calculated from pulse is high value

in pulse increasing state. In analysis of synchroniza-

tion, the tendency of synchronization occurrence is

classiﬁed into 3 types. The analysis of pulse-music

tempo ratio showed that each relaxation indicator has

optimum µ value. According to these result, we sug-

gest a new way of using music for relaxation. That is,

selectively presenting music with slower tempo than

the user’s pulse when the user wants the brain relax-

ation, or music with a tempo near to the user’s pulse

when the user wants body relaxation. If there is a

music music that has both two characteristics, that

kind of music is better for us. In the future work,

we will attempt to generate innovative music that de-

pending on the tempo of the user’ s pulse at the be-

ginning of music, the tempo of music is gradually de-

creased to µ = 1.3. We will study whether that kind

of music is effective for both content ratio of HF and

Comfortable-degree.

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AN EVALUATION OF THE RELAXATION EFFECT OF MUSIC BASED ON THE RELATIONSHIPS BETWEEN

THE CONDITION OF PULSE AND MUSIC TEMPO USING THE EEG AND HRV BASED INDICATORS

319