Effect of Chinese Zither Performance Training on Brain Function of

Autistic Children

Yunan Zhao

, Wei Lv

,Yi Xie

and Mengyi Zhang

School of Electrical Engineering, Shenyang University of Technology, ShenYang, LiaoNing, China

Shenyang Conservatory of music, ShenYang, LiaoNing, China

Keywords: Autism, Power Spectrum, Sample Entropy, Chinese Zither Performance Training.

Abstract: Based on the EEG signal analysis method of power spectrum and sample entropy, this paper analyzes the

EEG signals of children with autism (ASD) after different cycles of training, and studies the effect of Chinese

Zither performance training on the brain function of ASD children. Eight ASD children, with an average age

of 13, were trained in zither performance for 4 months, and EEG signals were collected once a month. The

results showed that the relative power of alpha frequency band increased after the training of Chinese Zither

performance, and the occipital lobe was more obvious, and there was a gradual upward trend with the increase

of training cycle; the relative power of theta band decreases, and the parietal lobe is more obvious, and has a

gradual downward trend; the sample entropy is higher than that before training, showing a gradually

increasing trend, and the complexity of the brain is also gradually increasing. It proves that Chinese Zither

performance training has a positive impact on the brain function of ASD children, and Chinese Zither

performance training may become a new direction of intervention and treatment of autism.

1 INTRODUCTION

Autism, also known as autism, that is, autism

spectrum disorders (ASD), is characterized by social

language disorder, rigid and strange behavior,

accompanied by growth retardation, etc (Kocsis

2013). Generally, the symptoms of autism will show

some characteristics in the early stage of children's

development, about 3 years old(Hu 2021).The

intelligence of autistic children is mostly lower than

the normal level. At the same time, autism is usually

accompanied by a series of health problems.

Therefore, most patients with autism cannot live

alone, which brings great pressure to the family. At

present, there are more than 10 million people with

autism in China, and the number is increasing year by

year. Autism has gradually attracted extensive

attention from the society.

Nowadays, although the research on autism is

more and more in-depth, its etiology has not been

found. Many studies on genetic inheritance show that

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autism may be a genetic comprehensive disease, but

no authoritative person gives a clear conclusion.

There is still no clear plan for the treatment of autism,

so we can only carry out some nondestructive and

harmless intervention treatment. Therefore, the in-

depth study of autism still has a long way to go.

Music therapy combines many disciplines,

integrates the knowledge and skills of psychology and

pedagogy into music, and achieves the purpose of

helping patients improve their cognitive ability,

emotional state and psychological situation by means

of music activities(Sun 2018). The developmental

disorders of autistic children have strong specificity,

and different patients have different manifestations. It

is very difficult to select subjects in various studies,

and music therapy is usually treated alone, so the

number of subjects is small. The adaptive music

training of Chinese Zither for autistic children

conforms to the international advanced education

concept of autism-cultivating one skill, making use of

the low sensitivity of the sound of Chinese Zither

Zhao, Y., Lv, W., Xie, Y. and Zhang, M.

Effect of Chinese Zither Performance Training on Brain Function of Autistic Children.

DOI: 10.5220/0011237100003438

In Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare (ICHIH 2022), pages 157-163

ISBN: 978-989-758-596-8

157

instruments and the adaptive advantages of playing

methods, and taking Chinese Zither music and its

performance as the intervention medium to provide

adaptive education and teaching theories and

implementation strategies for autistic children. To

improve the musical ability of autistic children, such

as zither playing, Chinese Zither performance

training involves multiple human sensory channels,

which are completed by multiple regions of cerebral

cortex(Huang 2019).These areas participate in

performance in different forms. This multi regional

cooperation can promote the network connection and

all-round development of the brain, promote the

changes of brain structure and function, and obtain

the development of brain plasticity(Pu 2015). At the

same time, Chinese Zither performance training will

also promote the changes of other cognitive functions

of individuals.

EEG signal is the best index to reflect the working

state of human brain, because EEG collects the

electrical signal sent by brain neurons. EEG is closely

related to mental disorders. A large number of studies

show that EEG has abnormal characteristics such as

amplitude, power and left-right asymmetry for

autistic patients, which are different from those of

healthy people(Han 2018). With the continuous

development of EEG signals and the achievements of

mental disorders through EEG analysis, researchers

believe that EEG contains useful information for the

treatment of autism patients.

More and more studies have proved that there are

some differences between EEG signals of ASD

patients and normal EEG signals(Li 2021). At the

same time, with the development of EEG analysis

methods, it has a more solid theoretical basis for the

analysis of EEG signals. It is more direct and effective

to evaluate the effect of intervention treatment in

ASD children based on EEG signals and evaluate

their brain function from the perspective of brain

cell electrophysiological activities.

In this study, Chinese Zither performance training

is used to intervene autistic children, not only through

auditory music perception, but also through the

combination of hearing and movement. After long-

term and systematic Chinese Zither performance

training, autistic children can play complete music

and even participate in Chinese Zither performance

activities, so that they can experience the joy and

sense of achievement brought by zither playing, build

self-confidence, and better integrate into the school

and society. At present, the evaluation methods of

various intervention effects are mainly behavior

observation, scale statistics, parent description and so

on. By collecting EEG signals of autistic children and

analyzing the characteristics of EEG signals from the

perspective of frequency domain and nonlinearity

based on power spectrum and sample entropy, this

study can objectively reflect the impact of Chinese

Zither performance training on the intervention effect

of autistic children, and then make an objective

judgment.

2 METHOD

2.1 Chinese Zither Performance

Training

Chinese Zither is one of the unique and important

national musical instruments in China. It has beautiful

timbre, wide range, rich playing skills and strong

expressiveness (Li 2020). Chinese Zither training is a

complex task, including long-term, large and diverse

skill training. In the field of hearing, ASD children

must learn to focus on distinguishing subtle

differences in pitch, rhythm, volume and timbre, and

learn to distinguish and remember complex auditory

patterns. In the field of sports, they must learn how

to control their arms, hands and fingers. They must

also integrate auditory and motor functions to control

different motor responses. When playing Chinese

Zither, players need to develop asymmetric manual

dexterity, pluck the string with the right hand, play the

melody and master the rhythm, and the left hand

conforms to the tension of the string and controls the

changes of the string sound, so as to adjust the pitch

and improve the melody (Wu 2020). Through such a

complex audio motion conversion, EEG signals have

obvious characteristics in the process of performing

this conversion.

2.2 Power Spectrum

In the frequency domain analysis method of EEG

signals, parameters such as power spectral density

and relative power need to be calculated on the basis

of power spectral quantification (Cheng 2021). When

an abnormal change occurs in a certain part of the

brain, the trend of EEG will change, and its power

spectrum will change accordingly. The power

spectrum calculation of EEG signal overcomes the

subjectivity of traditional naked eye observation of

EEG signal waveform, so that the physiological

information contained in the waveform can be

transmitted with quantitative numbers, and the

accuracy of EEG in disease diagnosis has been

improved (Li 2020). The power spectrum can be

ICHIH 2022 - International Conference on Health Big Data and Intelligent Healthcare

158

obtained by integrating the power spectral density in

the frequency domain.The nonparametric estimation

method of Fourier transform is selected to calculate

the power spectral density function and estimate the

spectrum of time series. The specific steps are as

follows:

The random function x(n) is known, the

autocorrelation function r(k) is estimated, and the

power spectral density function is obtained by Fourier

transform of r(k), which is recorded as P(ω), as shown

in formula (1).

() ()

Prke

+∞

−

=−∞



(1)

The classical method is the periodic graph method

for nonparametric spectrum estimation. When the

time series is of finite length, the expectation and

limit values are ignored to obtain the periodic

spectrum estimation, as shown in formula (2).

() ()

Pxne

−



(2)

Welch is improved on the basis of: segment the

data to make them overlap each other; use a variety

of window functions to add windows. Divide the data

into k segments, each segment is marked as x(n), and

the length is L. The signals of two adjacent segments

overlap each other. Calculate the power spectral

density of each segment and average it, as shown in

formula (3).

() ()

()

infn

Pf X dne

KLU

−



(3)

Where U is the normalization factor, ω(n) is

window function. Hamming window function is

selected in this study. The calculated results of each

section of data are superimposed and averaged, and

the power spectral density is the mean.

The absolute power can be calculated by dividing

the EEG activity of a single frequency band by the

average power of each frequency band. The average

power can be calculated from the power spectral

density of each channel. The absolute power is easily

affected by individual differences and has errors, that

is, the absolute value of the power spectrum has

errors, which affects the objectivity of the final data

conclusion. Therefore, in order to avoid random

errors, this paper selects the feature of relative power.

The relative power calculation method is: the energy

ratio of each frequency band to the whole frequency

band.

2.3 Sample Entropy

Entropy originates from the physical concept and is a

measure of the uncertainty of random variables. The

greater the probability of generating a new model, the

more complex the sequence, and the greater the value

of entropy, which can directly reflect the complexity

of the sample system (Zhao 2019). At the same time,

it can also reflect the distribution of energy in space.

The more chaotic and uneven the energy distribution

is, the smaller the entropy is; the more uniform the

energy distribution, the entropy tends to the

maximum. Sample entropy (SampEn) algorithm is

simple, does not compare with itself, has good

relative consistency, and is more conducive to

predicting the probability of new information (Wang

2013). Construct an m-dimensional vector for a given

time series, as shown in formula (4).

[

]

,,, ,

1, 2, 3, , 1

iii im

xxx x

iNm

++−

=−+



(4)

Define the maximum distance between two vector

elements as d, as shown in formula (5).

,max ,

0,1, 2, , 1, 1, 2, , 1

xxxji

ij ik jk

kmjNm



=−≠





=−=−+

，

(5)

Define the threshold r, count the number n less

than the threshold r, calculate the ratio of n to the total

number, and record it as C, as shown in formula (6).

()

{

}

1, 2, 3, , 1

iNm

−+

=−+

(6)

Find the average value, as shown in formula (7).

() ()

Prke

+∞

−

=−∞



(7)

Add 1 to the above dimension to make it a vector

of m+1 dimension, and repeat the above steps(Song

2016). Based on the above, the sample entropy is

defined, as shown in formula (8).

()

,, ln

SampEn m r N

=−

(8)

Where m is the embedding dimension and r is the

threshold.

Effect of Chinese Zither Performance Training on Brain Function of Autistic Children

159

3 EEG SIGNAL ACQUISITION

AND PREPROCESSING

3.1 Research Object

In this study, 8 ASD children were selected as

subjects, with an average age of 13 years, no history

of brain injury, no history of epilepsy and no implants

in the body. All of them were diagnosed as autistic

children by the diagnostic certificate issued by the

municipal third class hospital. All parents who

participated in this study fully understood the

experimental process and signed the consent form.

All 8 ASD children received Chinese Zither learning

for a year or so, which had a certain foundation. Due

to COVID-19, the Chinese Zither performance

training lasted for at least 8 months.

When selecting the tested children, the non

probability sampling method of judgment sampling is

used to select the relatively homogeneous and

representative children from the collected autistic

children as the research object, so as to realize the

research purpose of understanding the whole from

part. After the actual sampling, the sample quality

shall be evaluated, and the sample quality,

representativeness and deviation shall be

preliminarily tested and measured to prevent the

experimental results from being affected by the

excessive deviation of the sample.

3.2 Experimental Design and EEG

Acquisition

The selected 8 ASD children were taught Chinese

Zither adaptive music instruction for four months,

fixed for half an hour a week, and taught one-on-one

by professional Chinese Zither teachers. From the

first acquisition of EEG signals, EEG signals are

collected once a month as a training cycle. In each

acquisition process, EEG signals in resting state

before Chinese Zither performance training and in

resting state after Chinese Zither performance

training are collected for 30s, the flow chart is shown

in Figure 1.

Figure 1: Schematic diagram of EEG signal acquisition

process.

EEG signal acquisition uses g.Nautilus high-

precision wireless bioelectric signal acquisition and

analysis system. The motor is placed in the 10/20

system according to the international standard, and

the FPZ(Gun) electrode is used as the reference

electrode. The specific location distribution is shown

in Figure 2. Set the impedance value of each electrode

less than 50 KΩ, the reference electrode less than 10

KΩ, 24bit (1.024mhz internal sampling per channel),

and the sampling rate is 500Hz.

Figure 2: EEG electrode diagram.

3.3 Research Object

16 channels were selected from all 32 channels,

which were located in 4 brain regions: frontal lobe

(AF3, AF4, F3, F4), parietal lobe (C3, C4, CP1, CP2),

temporal lobe (FC5, FC6, T7, T8) and occipital lobe

(PO3, PO4, PO7, PO8). Remove artifacts such as eye

movement, electromyography, ECG, baseline drift

and outliers, filter 50Hz power frequency

interference, and carry out band-pass filtering of 0.5

~ 45.0 Hz.

4 RESULTS AND AANALYSIS

4.1 Based on Power Spectrum Analysis

The collected EEG signals are decomposed to obtain

four frequency bands. The energy ratio of each

frequency band to the whole frequency band is

calculated to obtain the relative power of each

frequency band. Previous studies have confirmed that

the alpha band power spectrum energy of ASD

children in resting state is lower than that of normal

group, and the theta band power spectrum energy is

significantly higher than that of normal children. This

study focuses on the analysis of the relative power of

alpha and theta frequency bands, occipital alpha

frequency band and parietal theta frequency band in

ASD children.

ICHIH 2022 - International Conference on Health Big Data and Intelligent Healthcare

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In this study, the relative power of 16 channels of

all 8 subjects was averaged to obtain the relative

power of alpha and theta frequency bands of all

subjects, and the relative power of alpha frequency

band of occipital lobe and theta frequency band of

parietal lobe were analyzed. The changes of relative

power of each brain region in alpha band before

training and at rest after each training cycle are shown

in Figure 3 and Figure 4, and the relative power of

theta band is shown in Figure 5 and Figure 6.

Figure 3:Relative power of all subjects before alpha band

training and after each training cycle.

Figure 4: Relative power of single subject before training

and after each training cycle in alpha band of occipital lobe.

As shown in Figure 3 and figure 4, in the alpha

band, the average relative power of all subjects and

the relative power of a single subject are compared

and analyzed. Compared with the EEG signals

collected before and after Chinese Zither

performance training, the relative power of the four

brain regions in the resting state increases to varying

degrees, especially in the occipital lobe, the relative

power of individual channels increases gradually with

the increase of training time.

Figure 5: Relative power of all subjects before theta band

training and after each training cycle.

Figure 6: Relative power of single subject before training

and after each training cycle in theta band of parietal lobe.

As shown in Figure 5 and figure 6, in theta band,

the relative power of most channels of EEG signals in

resting state after Chinese Zither performance

training is lower than that before training, the parietal

effect is significant, and individual channels show a

decreasing trend with the increase of training time.

4.2 Based on Sample Entropy Analysis

Sample entropy mainly reflects the chaotic degree of

the sequence. The greater the chaotic degree, the

greater the entropy and the higher the complexity; on

the contrary, the smaller the entropy, the more regular

the sequence, and the lower the generation rate of new

mode signals (Wu 2020). Previous studies have

confirmed that the sample entropy of EEG signals in

autism is significantly lower than that in healthy

people, and the entropy parameter can be used as a

parameter to analyze the brain function of autism. In

this study, the EEG signals of four brain regions of 8

children were analyzed based on sample entropy. The

sample entropy analysis results are shown in Figure

Effect of Chinese Zither Performance Training on Brain Function of Autistic Children

161

Figure 7: Results of Sample Entropy Analysis.

According to figure 7, the sample entropy of the

four brain regions of ASD children after Chinese

Zither performance training increased in varying

degrees, and some channels showed a gradual upward

trend with the increase of training cycle, while others

fluctuated in varying degrees, but showed an overall

upward trend.

5 CONCLUSIONS

For a long time, because the etiology of autism is not

clear, most of the treatment methods are non-invasive

intervention. In recent years, music therapy has been

accepted by more and more patients and their

families. Based on the power spectrum and sample

entropy, this paper analyzes the resting EEG signals

of ASD children after different cycles of training, and

obtains the following conclusions.

1. The analysis results based on power spectrum

show that although the relative power of alpha band

of ASD children in resting state fluctuates after

receiving zither performance training, it generally

shows an upward trend, and some channels gradually

increase with the increase of training cycle, especially

in occipital lobe. The relative power of theta band

decreases, and some channels have a gradual

downward trend, especially in the top lobe. This

proves that Chinese Zither performance training has

a positive intervention effect on ASD children from

the perspective of EEG frequency domain.

2. The analysis results based on sample entropy

show that after Chinese Zither performance training,

the sample entropy of ASD children in resting state is

higher than that before training. Although there are

fluctuations in individual channels, with the increase

of training time, the sample entropy generally shows

a gradually increasing trend, and its complexity also

gradually increases. This proves that Chinese Zither

performance training plays a positive role in

improving the complexity of ASD children's brain

from the perspective of nonlinearity.

3. Chinese Zither performance training is not only

to let the ASD children who receive training feel

music passively, but to play actively, even play. The

analysis results of EEG signals show that Chinese

Zither performance training can improve the brain

function of the tested children to a certain extent,

which has a positive impact. Therefore, Chinese

Zither performance training can provide a new

direction for the intervention of autism.

ACKNOWLEDGEMENTS

We would like to thank autistic children and their

families for their full support and cooperation in this

study during such a long experimental cycle. Thank

the teachers for providing the experimental site,

experimental equipment and post-processing

technology for this experiment.

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