The Secret of Tu Embroidery’s Heritage
Wanjun Zhang, Xi Huang, Anqi Song, Qiansheng Li *Shanghai UniversityABSTRACT
Tuzu pan embroidery has experienced the rise and fall of a thousand
years, containing rich national culture and wisdom. With thechange of society, fewer and fewer people possesses panembroidery skills, and plus the complexity of the embroidery
technology, young people are more reluctant to learn panembroidery . Pan embroidery inheritance began to face serious
problems.
In this project we let two students to learn pan embroidery from thecraft and use the data acquisition device to collect data in theprocess of embroidery of students and teachers. We have done aInteractive web page to tell a person how to study Pan embroidery
and to explore Pan embroidery how to get better inheritance byusing data visualization ways.
Keywords: Data collection, Visualization, Tu embroidery, The
inheritance of intangible cultural heritage.
1INTRODUCTION

The protection of intangible cultural heritage refers to various
measures to ensure the vitality of intangible cultural heritage,
including the recognition, filing, research, preservation, publicity,promotion, inheritance (especially through formal and informaleducation) and revitalization. As an important content of protecting
intangible cultural heritage, inheritance is the core of protection.
For more than one thousand years, the traditional pan embroidery
inheritance with mother and daughter oral and personal education,
also in the sister, sister-in-law, mother-in-law and daughter-in-law
inheritance. Nowadays, the limitation of learning pan embroidery
is reduced, but most young people are no longer willing to learn
pan embroidery. In the face of this problem, especially in the faceof non - genetic heirs to teach the novice of no embroidery
experience ,the relationship between teach and learn under theembroidery process is worth our exploration.
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Figure 1: 20 patterns collected by teachers and students

RELATED WORK

In order to find an effective way to learn pan embroidery and how
to better inherit pan embroidery. We designed two experiments:
one is to let a student learn from a teacher, and then let themembroider the same pattern.
Through collecting data of 20 patterns to observe the similarities
and differences between the novice and the craftsman, so as to findthe law of learning pan embroidery; The second is to have a trainee
embroider the same pattern every day for 30 days. In the wholeproject, we analyzed the learning time of the embroidery vertically,
and collected the video of the teacher and two students in theembroidery process, the length of the thread used, brain waves,electromyography signals of the right arm, and the number of knotsof the finished embroidery.

* nick_lee@shu.edu.cn

2.1 Brain wave data collection
Modernscientificresearchshowsthat spontaneouselectrophysiological activity occurs when human brain works,
which can be expressed in the form of brain waves by special
electroencephalograph. We use Mindwave Mobile device to collectbrain waves of teachers and students.
During the acquisition process, the device was worn on the subject's
head. Mindwave Mobile used a sensor placed on the forehead anda reference electrode contact placed on the ear to measure brain
wave signals. Through this device, we collected data of 8
dimensions and eSense index values.
The eSense index value is calculated by applying eSenseblem
algorithm to the processed signal after the ThinkGear amplifies theoriginal brainwave signal and filters the interference caused byenvironmental noise and muscle tissue movement. It is used torepresent concentration and relaxation.
We collected the brainwaves of 20 patterns embroidered by theteacher and a student and the brainwaves of embroidery by anotherstudent for 30 days. We can found the rule of embroidery learning
by analyzing the changes of concentration and relaxation ofstudents and teachers in embroidery.
2.2 Brain wave data collection
In this project, we used myo bracelets to collect surface myoelectric
signals from the right arm of the teacher and two students. Myo ismainly composed of eight different thickness of the block size ofbioelectricity sensor units, each sensor is divided into threeelectrodes, the wearer can be detected gestures change when themuscle of bioelectricity, in addition to the eight sensors, myo builtin three-axis accelerator, three-axis gyroscope, so can collect emg,
acceleration and direction of the gyroscope and four dimensions of
the data. I want to analyze the embroidery differences between thenovice and the craftsman through the collected data.

Because both myo bracelet and Mindwave Mobile are connected
via Bluetooth. We collect them by two computers to avoid
interference with each other. If the device is interrupted, we will
ask the collector to stop the embroidery, and then do the embroidery
after the device is connected, so as to ensure the accuracy of thedata.
2.3 Other data collection
Besides brain waves and electromyography collection,
We also collected the length of thread used by teachers and students
during the embroidery process. The specific method is that we must
do a series of preparatory work before the embroidery. Because of
the unique skill of pan embroidery, we should measure the lengthof the line before they ready for embroidering. The record of theline length is divided into single-strand and 3-strand. And when
they need to change the line, we should subtract the length of theremaining line. With the embroidery beginning, we start to time andrecord the video. We recorded the process of embroidery as video
data and recorded the length of each person's embroidery. The
number of knots will also be counted manually when theembroidery is finished.
33.2 Visual analysis of emg data
When processing the huge emg data, we first used the varianceformula to calculate the variance value of 8 sets of data, which wasused to represent the intensity of muscle activity at this time point.
In order to facilitate the observation of changes in emg data, weprocessed the original density data into 50 seconds by sampling theaverage method, and finally obtained a smoother emg curve in theprocess of embroidery between the student and the teacher. We
could clearly see the difficulty of each pattern and the difference
between the student and the teacher.

DATA VISUALIZATION DESIGN

After the data collection, we got the embroidery data of twostudents and the teacher for 30 days.
We processed and visualized the data, and then made a datavisualization page about the transmission of embroidery.
3.1 Visual analysis of brain wave data
The two data, focus and relaxation, were analyzed in the form of abroken line graph and visualized in polar coordinates. In order tofurther compare their overall relaxation and concentration, wecompared the data with five interval values of brain waves. ESense
index values of 1-20 are "low value zone"; 20-40 is the "lower valuearea"; 40-60 in the general range; 60-80 is the "higher value area";
80-100 is the "high value zone".
Through electroencephalogram and zonal graph we can see theteacher ’ s embroider experience is rich and more relaxed inembroider process，and if the student wants to embroider better,
she must improve concentration higher
and after having certain experience embroider process she just canbe more relaxed.
In the same situation of having problem , the teacher and the student
are more focused, but the student will be more focused.

Figure 2: Visualization of brain wave data

* nick_lee@shu.edu.cn

Figure 3: Electromyogram of teacher and student

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CONCLUSION

Our practice has proved that it is feasible and effective to collectdata in the process of embroidery by equipment. Comparing thedata of the non-genetic inheritor with the data of the novice, we canget the learning method of the embroidery and the problems to bepaid attention to in the process of embroidery. In the current
experiment, we only obtained the data of a professional panembroidery craftsman and two novices, which may have somedeviation in the data comparison. In the future, we need to collect
more data for analysis and comparison, hoping to help panembroidery find a new inheritance method through the similarities
and differences of these data.
REFERENCES[1] Han zehua. Protection and inheritance of plate embroidery of tu
nationality [D]. Chinese academy of arts,2016.
[2] Gibbs, Mark. NeuroSky MindWave Fun with brainwaves[J].
Network World,2012,29(3).
Qiu qingju. Study on feature extraction and pattern classification ofsurface emg signals [D]. Shanghai jiao tong university,2009.