1. INTRODUCTION

With the development of microcomputers and single chips, the way people interact with computers has changed. It has come a long way from the early keyboard and mouse to the development of the multi-touch. Developers always want to find better ways to let people interact with apps in a more natural way, such as through gestures (Leap Motion [1]), Wii [2], voice input, etc. However, these are all motor functions, that is, different people using the same operation method will get the same result. Compared with Electroencephalogram (EEG), because people cannot see how the user moves, it just exists in the brain’s operation, so no one can copy the actions of another person and produce a personal style. Therefore, we aim at the state of concentration and meditation in the brain waves as an interactive input method to bring a new perspective.

In addition, installation art is becoming more and more popular as a form of modern art. Compared with other art forms, installation art allows people to be more involved, use touch, and even play in it. Therefore, interactive methods are also added to allow people to enjoy, participate in, communicate, and interact with art, making it truly interactive installation art. However, most of the art content is fixed or arranged according to the creator. So, there is not much change, resulting in people not wanting to repeat, come, and participate.

Generative art is produced by computer programs. It has the characteristics of non-repetition and endless evolution. It has received a lot of attention since the beginning of computer graphics. Many works of art are inspired by nature, among which phyllotaxis is included. It is a combination of mathematics and the beauty of nature. Not only can it be seen everywhere in nature, but also often appear in man-made objects, becoming part of culture or religion. For example, Mandala Kolam is not only an expression of art but also healing people’s bodies and minds. And Chakra’s representative totem is also like phyllotaxis. When people are using it, it is easier to relax the mood and achieve the function of art therapy.

Therefore, we try to use EEG to make interactive installation art and use EEG input to create phyllotaxis patterns to project it on the wall. Because everyone has a different state, the graphics drawn are also different from person to person, creating interesting interactive works. In addition, the sound can also be changed by EEG, becoming a dynamic, real time content.

Finally, when the user looks at the graphics generated by his own brain, the visual and sound effects of these graphics can trigger psychological states to achieve an increasingly relaxed state, and achieve the effect of meditation. This can bring about communication with the heart and then achieve the effect of art therapy [3].

2. BACKGROUND: EEG CONTROL ART

3. DEVELOPMENT AND APPLICATION

3.1. System Structure

The development environment is Intel I7 PC on windows 10 system, with the NVIDIA GeForce RTX 2080TI graphics card. The programming language C# has been used to develop the application on the Unity SDK. The EEG headset is NeuroSky MindWave Mobile 2.

Figures 1 and 2 show the EEG headset is connected to the computer via Bluetooth, and uses the intermediary software ThinkGear Connector [6] to send the received data to Unity [7] via UDP network protocol.

Figure 1

EEG connecting to Unity by Bluetooth and UDP.

Figure 2

System structure.

In NeuroSky EEG, there is a technology called ThinkGear, whose architecture is a sensor that touches the forehead, the contact points and reference points on the earpads, and the onboard chip for processing all data. The ThinkGear chip analyzes, calculates, and outputs the brainwave data, including the Attention and Meditation measures [8].

3.2. Content Generation

The simple model for the florets of a sunflower was Vogel ‘s formula. As the book “The Algorithmic Beauty of Plants” [9] descript below:

φ=n∗137.5°,      r=cn, (1)

• •

  n is the ordering index number of a floret, from the center to outer. Therefore, it is accumulated from the minimum value to the maximum value in the program.

• •

  φ is the angle of the nth floret in a polar coordinate system.

• •

  r is the distance from the center of the capitulum to the nth floret.

• •

  c is a constant scaling.

• •

  The number 137.5 is the angle of this pattern. In the application, the pattern is changed by this parameter. Therefore, it is not constant 137.5.

From this equation, we can get r, φ. From r, φ we can calculate the x, y values of the coordinate system to draw the pattern.

x=r∗cos(φ),       y=r∗sin(φ). (2)

In Figure 3, it can be found that changing different angles will produce different pattern changes, so the angle is used as a variable in the program to generate changeable patterns.

Figure 3

Generating phyllotactic patterns from the Vogel’s formula. (a) α = 137.3°, (b) α = 137.5°, (c) α = 137.6°.

3.3. EEG Data

Different waveform data can be obtained from the signal from the brain waves, such as alpha wave, beta wave, etc., as well as data on concentration and meditation. We used the level of concentration to generate graphics, and use the level of meditation as a reference value for color and sound.

In Table 1, the Attention value is reported on a relative eSense scale of 1–100 [10]. It is direct-mapped into seven ranges to change the angle of the pattern. When the value of attention is low, the angle of the pattern is smaller; when the value is higher, the angle is larger.

Range of attention	Angle φ
0–14	41
15–29	59
30–44	73
45–59	97
60–74	109
75–89	137.5
90–100	157

Table 1

Use value of attention for angle φ

Similarly, the Meditation value is reported on a relative eSense scale of 1–100 [10]. It is direct-mapped into seven ranges to change the color of the pattern as shown in Table 2. They are represented by seven colors of red, orange, yellow, green, blue, indigo, and violet. Obviously, these colors are the same as the chakra colors [11] , and they also form the basic color of white light. This correspondence is natural and conforms to the human body.

Range of meditation	Color
0–14	RED
15–29	ORANGE
30–44	YELLOW
45–59	GREEN
60–74	BLUE
75–89	INDIGO
90–100	VIOLET

Table 2

Use value of meditation for color

Figure 4 shows the patterns change depending on the value of the seven levels. The color of the pattern is changed from warm color to cold color. The user also becomes calmer and gradually enters the deep state of meditation.

Figure 4

The seven patterns generated by different angles and colors. The order is from left to right, up to down.

In the sound part, the sound of ocean waves is used in the background, which makes people feel relaxed. In addition, different frequencies of Tibetan bowl sounds are played by EEG’s meditation state. When the participant enters deep meditation, the system will play a calmer bowling sound.

3.4. Installation

Figure 5 shows the installation for the application which used a projector to project the generated graphics onto the neutral wall, allowing users to sit in front of the projection screen and watch. This allows the user to relax and wear the EEG headset.

Figure 5

Installation for the application.

4. USER FEEDBACK

A user study was conducted over 50 university students, between the ages of 16–25. Include 44% of male and 56% of female. The experiment apparatus and the projector were used to project the patterns to the neutral wall. Each subject used the applications for 2–5 min. After that, subjects were asked to take an online survey. The questions included what subjects thought while using the application and how they felt when they used the applications. Figure 6 shows some patterns made by different subjects.

Figure 6

Pattern generated by different subjects.

Figure 7 shows when people used the application, 44% tried to think about different things to see the changes in graphics, colors, and sounds. 8% tried using different emotions to see different changes. 42% were in the state of emptying meditation. About 6% were thinking about the meaning of these graphics and how such patterns were made.

Figure 7

What are people doing while using the application.

Among them, 84% found it interesting and novel. In addition to the artistry brought about by the graphics and color changes, almost everyone wanted to know the meaning of these graphics and whether they can understand their emotions or psychological state.

5. CONCLUSION

The use of EEG to generate phyllotaxis is a very novel experience for most people. As an installation art, the generated graphics have different results according to the conditions of different people, making the installation art show a variety of effects.

Through some applications, users can also recognize their own mental state. Through different thinking patterns, imagination, and memories, people were able to produce graphics of different colors. Seeing and feeling the visual and sound effects of these graphics can trigger new psychological states, such as excitement or calmness. In this way, we have space and time to face our own state of mind and examine our inner state. It is like a dialogue and communication with the self, allowing the heart to settle, reflect, meditate, and think, and find the inner peace and answer.

In further researches, we need to find out what kind of content can make users more relaxed. By setting up different contents and experiential environments, the impact after the subject’s daily use could be measured. These experiential findings could be guided to find the method to improve the concentration of the users and how to improve users’ creativity and productivity.

CONFLICTS OF INTEREST

The authors declare they have no conflicts of interest.

ACKNOWLEDGMENT

This research was supported in part by the Ministry of Science and Technology of Taiwan under the grant (IV) MOST 109-2218-E-002-038-.

AUTHORS INTRODUCTION

Mr. Chien-Tung Lin

He received his B.S. degree from the Department of Computer Science and Information Management, Providence University, Taiwan in 1999. He is a Graduate student at the Graduate Institute of Animation and Film Art, Tainan National University of the Arts, Taiwan. His research interests include virtual reality, interactive art, EEG, art therapy, computer animation and healing method.

Dr. R.P.C. Janaka Rajapakse

He is an Associate Professor at the Graduate Institute of Animation and Film Art, Tainan National University of the Arts, Taiwan. And he is also a visiting scholar in the Department of Media and Image Technology at the Faculty of Engineering, Tokyo Polytechnic University, Japan. He was a Postdoctoral Researcher at the Center for Hyper Media Research, Graduate School of Engineering, Tokyo Polytechnic University. He received his PhD in Knowledge System Science from Japan Advanced Institute of Science and Technology in 2008. His research interests include computer animation, motion capture, VR/AR/MR, haptic interfaces, AI, computer graphics, and Kansei Engineering. He is a member of the Motion Capture Society, The Society for Art and Science, ASIAGRAPH, and SIG-Design Creativity.

Dr. Yoshimasa Tokuyama

He is a Professor of the Department of Media and Image Technology at the Faculty of Engineering, Tokyo Polytechnic University, Japan. He received his PhD in Computer Graphics from the University of Tokyo in 2000. His areas of research interest include computer graphics, haptics, virtual reality, shape modeling, game, and their applications. He is a member of the IPSJ, ITE, IIEEJ, and The Society for Art and Science.