comparison of brain activities between hand and …

cooking route and kitchen information these two aspects, it can be clearly found that modern cooking habits have undergone new changes, and the users’ dependence on the kitchen information has greatly increased. However, the layout and the information of the kitchen are directly related to the cooking efficiency and kitchen experience of the users. The kitchen layout and information system are supplemented by each other. Both the information system and the kitchen layout help users achieve better cooking experience. The smart kitchen consists of the integral kitchen (the whole cabinet and intelligent electric appliances) and the integrated control system. The concept of the smart kitchen is designed to make activities in the kitchen more convenient through the technologies which are embedded into the kitchen space and introduced to support the users’ activities at the precise time based on the users’ needs by recognizing the users’ behaviors [14]. The essence of the smart kitchen is to make the hidden information like cooking steps in the traditional kitchen transparent and to integrate external information like kitchen appliances into the kitchen, so that users can grasp and understand the status of the kitchen and even the whole family at any time. All these functions cannot be separated from the kitchen design, and they require a suitable kitchen layout and display mode to make them work. Therefore, we try to give a suggestion for the future kitchen design that the kitchen should require a new work triangle, set aside enough space for preparing food, and provide a more suitable kitchen information display area and working method. The new kitchen layout will be equipped with kitchen information guide devices (smart devices used for guiding cooking behaviors): The new core functional area of the kitchen provides information guidance, which leads to new changes in each area by means of information display; The information display is used to guide the user’s cooking behaviors, while the information is generated from the user’s cooking behaviors and needs. The future research will focus on discussing how the users can accept the presentation of the kitchen information under the system kitchen. Through the user evaluation, the assumption we summarized can be determined, so that the user can get higher cooking efficiency and more joy of cooking by the interactive operation. References [1] Martin Maguire, Sheila Peace, Colette Nicolle, Russell

Marshall, Ruth Sims, John Percival, Clare Lawton, Kitchen living in later life: Exploring ergonomic problems, coping strategies and design solutions, International Journal of Design, 8(1), 73-91, 2014

[2] Ranney, Elizabeth M., Kitchen Planning Standards, Journal of University of Illinois Bulletin, 47(19), 1949

[3] He X., Yu D.R., The Developing Trend of the Kitchen Design in the Information Age, Journal of Art & Design, (05), 110-112, 2010 (in Chinese)

[4] Michael Schneider, The Semantic Cookbook: Sharing Cooking Experience in the Smart Kitchen. Proceedings of the 3rd IET International Conference on Intelligent Environments 2007 (2007), 416-423

[5] Haier http://www.techweb.com.cn/news/2015-07-10/2174043.shtml (Accessed 10 July 2015)

[6] Mitsubishi Electric: http://www.mitsubishielectric.com/news/2015/0213.html (Accessed 13 February 2015)

[7] Chia-Hsun Jackie Lee, Leonardo Bonanni, Jose H. Espinosa, Henry Lieberman, Ted Selker, Augmenting Kitchen Appliances with a Shared Context. Proceedings of the 11th International Conference on Intelligent User Interfaces(IUI) 2006

[8] Itiro Siio, Reiko Hamada, Noyuri Mima, Kitchen of the Future and Applications. Proceedings of Human-Computer Interaction: Interaction Platforms and Techniques 2007, 946-955

[9] Zhang S.Y., Application of Kitchen Entirety Design on Residence Construction, Journal of Science & Technology of Baotou Steel (Group) Corporation, 29(3), 74-76, 2003 (in Chinese))

[10] Atkinson, R.C., Shiffrin, R.M.: Human memory: a proposed system and its control processes, The Psychology of Learning and Motivation: Advances in Research and Theory, 89–195, 1968

[11] Marcus Stander, Aristotelis Hadjakos, Niklas Lochschmidt, Christian Klos, Bastian Renner, Max Muhlhauser, A Smart Kitchen Infrastructure. Proceedings of IEEE International Symposium on Multimedia 2012, 96-99

[12] Bonanni L, Lee C, Selker T, CounterIntelligence: Augmented Reality Kitchen. Proceedings of CHI 2005, 44.

[13] Bonanni L, Lee C, Selker T, Attention-based Design of Augmented Reality Interfaces. Proceedings of CHI Extended Abstracts on human factors in computing systems 2005, 1228-1231

[14] Azir, Ku Nurul Fazira and Baber, Chris and Jusoh, Muzammil, Cooking Guide: Direct and Indirect Form of Interaction in The Digital Kitchen Environment. Proceedings of the 5th International Conference on Computing and Informatics (ICOCI) 2015 (2015), 52-57

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COMPARISON OF BRAIN ACTIVITIES BETWEEN HAND AND COMPUTER DRAWINGS IN FINKE’S PATTERN

GENERATION TASK

Takeo KATO*, Shogo OTAGIRI*, Yusuke NAGAMORI**, Yuuichi IZU***

* Keio University Hiyoshi, 3-14-1, Kohoku-ku, Yokohama City, Kanagawa, 223-8522, Japan ** Tsukuba University of Technology Amakubo 4-3-15, Tsukuba City, Ibaraki, 305-8520, Japan

** Shizuoka University of Art and Culture 2-1-1 Chuo, Naka-ku, Hamamatsu City, Shizuoka, 430-8533 Japan

Abstract: CAD (Computer Aided Design/Drawing) has become popular to be used both in industrial and engineering design areas. The drawing by CAD is superior to the hand drawing in the accuracy and ease of modifying, but is inferior in the generation of a creative idea accidentally given by the hand drawing. There are some studies to compare the two drawings, but is no one to evaluate the difference in the designers’ creativity, quantitatively. This study is a preliminary stage to quantitatively differentiate them and measured of the cerebral blood flow of the sixteen participants taking the creative task (Finke’s pattern generation task) employing the two drawings. The blood flow was measured using a NIRS (Near Infra-Red Spectroscopy) apparatus. The result shows that the significant difference of the qualitative assessment between the hand drawing and computer operation could not be confirmed, and the computer operation activates more channels (brain regions), especially in the right prefrontal cortex, than the hand drawing. Keywords: Design Thinking, Creativity, NIRS, Hand Drawing, CAD

1. Introduction

1.1. Background

This section introduces the following three research trends: sketches and engineering drawings by hand and CAD; creativity; brain activities against creative tasks. (1) Sketches and engineering drawings by hand and CAD: Due to the information technology development, CAD (Computer Aided Design/Drawing) has become popular to be used both in industrial and engineering design areas. The drawings using three dimensional CAD (3D-CAD) can be comprehended by the people without expertise in engineering drawing, such as develop members and customers, and can be easily prototyped using a three dimensional (3D) printer. This improves the efficiency of the product development. However, some studies give warning that the use of CAD decreases the designer’s creativity. Iwata stated that the unintended line drawn by

hand expands the image and withdraws the innovative idea [1]. Iwata also stated that the both drawing and considering can realize the designer’s intention freely. Kudrowitz explored the relationship between the quality of an idea sketches and its creativity evaluation and reported the higher quality (line quality, correct perspective, and realistic proportions) correlates with the higher creativity rank [2]. Additionally, Chikawa criticized that the CAD drawing might disturb the creative tasks because the designers concentrate to the CAD software operation [3]. Many designers, therefore, employ the hand drawing in order to generate a creative idea despite the convenience of CAD drawing [4].

The aforementioned studies, however, suggest their opinion based only on the designer’s experience or the qualitative assessments. Therefore, the quantitative evaluation has been required.

The Bulletin of JSSD Vol.1 No.2 pp.1-2(2000)

Original paper

Journal of the Science of Design Vol. 2 No. 2 2018 43

Original ArticlesReceived Nov 9 2016; Accepted Jun 10 2018

*

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(2) Creativity: Creativity is defined as an ability of an individual to generate original and novel ideas by breaking established mental habits of thinking and has been studied in various approaches (social, psychological, and clinical approaches) [5]. The studies of the creativity are classified on the basis of the following objectives [6].

1) Creative personality: The study for the creative personality aims to clarify the personality of the people who are creative in order to distinguish them.

2) Creative ambient: The creative ambient (i.e. human and environment interaction) affects the creative achievement, and the social and environmental factors of the creativity are investigated in these studies.

3) Creative process: The creative process has been popularly studied since the 1990s in order to clarify the cognitive process regarding the creative thinking.

4) Creation: The creation means all the output derived by the activities (e.g. action, performance, idea, and object). This study has an important role in the creative studies because it has possibilities to develop the evaluation criteria which can be applied to the other three study objectives.

All the four approaches require the evaluation of the creations because they define the creativity as generating the creative things. The evaluation methods include the one defines the creativity criterion and employs the evaluators, and the other counts the number of the information material to searching the idea. However, the former has less objectivity and the latter depends on the object that the participants work on. Therefore, the method to objectively and versatilely evaluate the creativity is required. The following sub-section introduces the brain activity measurement studies having potential to construct the evaluation method. (3) Brain activities against creative tasks: The research measuring the brain activities against the creative tasks has become popular due to the development of the measurement devices. Alexiou compared the brain activities between the ill- and well-structured design problems (furniture layout problems) using a function Magnetic Resonance Imaging (fMRI) apparatus and suggested that the former problem whose evaluation criteria is not well specified activates more brain regions than the latter one [7]. Particularly, the former task activated the two types of the brain regions: one includes the areas involved in visual imagery, semantic processing, and multi-sensory integration,

such as the temporal, occipital, and parietal regions; the other is the prefrontal cortex (PFC) for constructing executive schemes of action. Kowatari measured the brain activities of the undergraduate/graduate students designing the shape of a pen using a Magnetic Resonance Imaging (MRI) device and concluded the design task facilitated and suppressed the right and left PFCs, respectively [5]. Gibson used a NIRS apparatus and compared the brain activities between schizophrenic patients and healthy participants during the task to generate new uses of the objects shown in the computer screen [8]. As a result, compared to the healthy participants, the patients generated more uses, and the more brain regions in both the right and left PFCs were activated. Gibson also compared the brain activities between the creative individuals (musicians) and healthy participants [9]. The result reveals that the musicians also derived more uses and activated more brain regions in the PFCs, same as the patients. Nagamori measured the brain activities of the undergraduate/graduate students when they work on the following two creative tasks using NIRS apparatus [10]. Task 1 is to select and arrange one or three colors which are fit to the given concept (adjective phrase, such as “cool” and “cute”). Task 2 is to make a “cute chair” using single- or multi-color blocks. The results of the two tasks show some task conditions (e.g., selecting one color in Task 1 and using multi-color blocks in Task 2) activate the PFC more than the others. In other words, the more creativity the task requires, the more brain regions in the PFC activate.

These studies confirmed the creative tasks activate the brain regions in the PFC, suggesting the possibilities to evaluate the creativity by measuring them.

1.2. Objective and Method

The present study is a preliminary stage to quantitatively differentiate the creativity in the idea generation employing a hand drawing and CAD software and aims to compare the brain activities between the hand drawing and computer operation in order to discuss the possibilities to construct the way to evaluate the creativity quantitatively. In the experiment, the participants conduct the Finke’s pattern generation task [11] employing the hand drawing and computer operation. Then, the brain activities of them and the creativity assessments of the generated patterns are compared. In the experiment, the participants conduct the Finke’s pattern generation task [11] employing the hand drawing and computer operation. Then, the brain activities

Journal of the Science of Design Vol. 2 No. 2 201844

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(2) Creativity: Creativity is defined as an ability of an individual to generate original and novel ideas by breaking established mental habits of thinking and has been studied in various approaches (social, psychological, and clinical approaches) [5]. The studies of the creativity are classified on the basis of the following objectives [6].

1) Creative personality: The study for the creative personality aims to clarify the personality of the people who are creative in order to distinguish them.

2) Creative ambient: The creative ambient (i.e. human and environment interaction) affects the creative achievement, and the social and environmental factors of the creativity are investigated in these studies.

3) Creative process: The creative process has been popularly studied since the 1990s in order to clarify the cognitive process regarding the creative thinking.

4) Creation: The creation means all the output derived by the activities (e.g. action, performance, idea, and object). This study has an important role in the creative studies because it has possibilities to develop the evaluation criteria which can be applied to the other three study objectives.

All the four approaches require the evaluation of the creations because they define the creativity as generating the creative things. The evaluation methods include the one defines the creativity criterion and employs the evaluators, and the other counts the number of the information material to searching the idea. However, the former has less objectivity and the latter depends on the object that the participants work on. Therefore, the method to objectively and versatilely evaluate the creativity is required. The following sub-section introduces the brain activity measurement studies having potential to construct the evaluation method. (3) Brain activities against creative tasks: The research measuring the brain activities against the creative tasks has become popular due to the development of the measurement devices. Alexiou compared the brain activities between the ill- and well-structured design problems (furniture layout problems) using a function Magnetic Resonance Imaging (fMRI) apparatus and suggested that the former problem whose evaluation criteria is not well specified activates more brain regions than the latter one [7]. Particularly, the former task activated the two types of the brain regions: one includes the areas involved in visual imagery, semantic processing, and multi-sensory integration,

such as the temporal, occipital, and parietal regions; the other is the prefrontal cortex (PFC) for constructing executive schemes of action. Kowatari measured the brain activities of the undergraduate/graduate students designing the shape of a pen using a Magnetic Resonance Imaging (MRI) device and concluded the design task facilitated and suppressed the right and left PFCs, respectively [5]. Gibson used a NIRS apparatus and compared the brain activities between schizophrenic patients and healthy participants during the task to generate new uses of the objects shown in the computer screen [8]. As a result, compared to the healthy participants, the patients generated more uses, and the more brain regions in both the right and left PFCs were activated. Gibson also compared the brain activities between the creative individuals (musicians) and healthy participants [9]. The result reveals that the musicians also derived more uses and activated more brain regions in the PFCs, same as the patients. Nagamori measured the brain activities of the undergraduate/graduate students when they work on the following two creative tasks using NIRS apparatus [10]. Task 1 is to select and arrange one or three colors which are fit to the given concept (adjective phrase, such as “cool” and “cute”). Task 2 is to make a “cute chair” using single- or multi-color blocks. The results of the two tasks show some task conditions (e.g., selecting one color in Task 1 and using multi-color blocks in Task 2) activate the PFC more than the others. In other words, the more creativity the task requires, the more brain regions in the PFC activate.

These studies confirmed the creative tasks activate the brain regions in the PFC, suggesting the possibilities to evaluate the creativity by measuring them.

1.2. Objective and Method

The present study is a preliminary stage to quantitatively differentiate the creativity in the idea generation employing a hand drawing and CAD software and aims to compare the brain activities between the hand drawing and computer operation in order to discuss the possibilities to construct the way to evaluate the creativity quantitatively. In the experiment, the participants conduct the Finke’s pattern generation task [11] employing the hand drawing and computer operation. Then, the brain activities of them and the creativity assessments of the generated patterns are compared. In the experiment, the participants conduct the Finke’s pattern generation task [11] employing the hand drawing and computer operation. Then, the brain activities

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of them and the creativity assessments of the generated patterns are compared. The reason for selecting the Finke’s experiment is descried as follows. This study, which compares the hand drawing and PC operation, focuses on the visual thinking in which an idea is generated using both the synthesis and transformation of the visual pattern parts. The Finke’s experiment regarding the visual thinking, used simple patterns and generated the creative ideas (patterns) using the synthesis and transformation of them. And, the result shows the order and practice effects do not exist [11]. This suggests the task in the Finke’s experiment can realize a versatile experiment whose results do not depend on the participant’s knowledge or experience. Additionally, the Finke’s experiment was done not only about the mental synthesis, in which the participants synthesize in their head, but also about the physical synthesis, in which they synthesize while drawing the pattern parts on the work sheet [12]. This result shows no difference of creativity between the psychological and physical syntheses. This study, therefore, employed the Finke’s experiment.

This paper is organized as follows. Chapter 2 illustrates the method to measure the brain activities. Chapter 3 presents the method, result and discussion of the experiment, while Chapter 4 provides conclusions and future tasks.

2. Methods to Measure and Analyze Brain Activities

2.1. Brain Activities Measuring Method

The brain activities measuring methods include NIRS, PET (Positron Emission Tomography) SPECT (Single Photon Emission Computed Tomography), MRI, EEG (Electroencephalogram), MEG (Magnetoencephalogram), as shown in Table 1. This study used NIRS because it is an invasive measurement and does not constrain the participant’s movements (hand drawing and computer operation) or require the electromagnetic wave shielding ambient.

A NIRS apparatus is composed of some emitter-detector pairs of near infrared light whose wavelength is from 700nm to 1000nm and cannot be easily absorbed in a biological tissue. Each emitter has two continuous laser diodes and irradiates the near infrared light of two different wavelength in order to measure the concentration changes in both oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb). While the amounts are calculated on the basis of the modified Beer-Lambert Law [14], which gives the relation equation between the attenuation of light and the density changes in light absorber. The measurement principle of NIRS apparatus based on the modified Beer-Lambert Law is described in Fig. 1. The equation in this figure shows the concentration changes in oxyHb and deoxyHb ( coxy and cdeoxy) can be estimated using the logarithm of the ratio between the input and output light intensities (Iin and Iout). However, the concentration changes derived from neither different participants nor measurement regions can be compared because the light pass length d

Table 1. Apparatuses to Measure Brain Activities [13]

Time resolution Invasive/Noninvasive

Participant movement

NIRS (Near -infrared spectroscopy ) >0.5sec Noninvasive Allowed

EEG (Electroencephalography) 20-30msec Noninvasive Allowed

MEG (Magnetoencephalography) 2-3msec Noninvasive Not allowed

SPECT (Single photon emission computed tomography) One/half day Invasive Not allowed

PET (Positron emission tomography ) Several minutes Invasive Not allowed

MRI (Magnetic resonance imaging ) >0.5sec Noninvasive Not allowed

Figure 1. Measurement Principle of NIRS Apparatus

εoxy , εdeoxy Molar absorption coefficients of oxy- and deoxy-hemoglobin

coxy , cdeoxy Density changes in oxy- and deoxy-hemoglobin

dcΔdcΔII deoxydeoxyoxyoxyoutinlog

Iin Input light intensityIout Transmitted intensityd (=d1+d2): Light path length

Hemoglobin

Light scatter

Illuminator Detector

outIinI

2d1d

Blood vessel


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varies according to them. The change in the oxyHb correlates the change in the regional cerebral blood flow. The apparatus, therefore, can capture the change generated by the activation of the nervous activities of the brain.

2.2. Brain Activities Analysis Method

This study adopted the change in oxyHb which is the most sensitive indicators of the change in regional cerebral blood flow [15] and analyzed the signal as the following methods:

The moving average processing [16,17]: to remove the components originating from the slow fluctuations of cerebral blood flow, heartbeat, and body motion, the oxyHb signal was bandpass filtered between 0 and 0.2 Hz by employing a movement average value in five seconds. The frequency band ([0, 0.2]Hz) was set on the basis of the preliminary experiment. In the experiment, the oxyHb signals from three subjects conducting the hand drawing and resting tasks were measured, and it was found that the difference of the power spectrum distribution obtained by FFT signal processing between hand drawing and resting tasks is statistically significant in the bands above 0.2Hz (see “Appendix” for more information). Base line correction [18,19]: to remove the component originating from the fatigue of a participant which changes the oxyHb caused linearly with respect to time, the line connecting the average values of the two control tasks conducted before and after the target task was calculated and was subtracted from the oxyHb signals.

3. Cerebral Blood Flow Measurement during Creative Activities 3.1. Experimental Outline

This experiment aims to compare the cerebral blood flow of the participants working on the Finke’s pattern generation task by hand drawing and computer operation. The following description outlines the Finke’s task [11].

Finke suggested the importance of visualization in creative thinking and discovery and conducted some experiments in order to clarify the relationship between the visualization methods and the creativity of the output (patterns). One of the typical experiments was conducted the following procedures.

1) At the beginning of each trial, three of the pattern parts

were randomly selected from the fifteen parts (Fig. 2). In order to reduce the complexity difference between the combinations, the selecting condition was that the parts in the first two rows in Fig. 2 were three times as likely to be selected as the complex parts shown in the bottom row. The participants were instructed to close their eyes and to image assembling them to make a recognizable figure. The assembling restrictions are that all three parts are used, the parts can be deformed only by rotation and expansion/reduction, the assembling time is two minutes.

2) The participants were instructed to open their eyes and to write down the generated pattern with their names.

3) The generated patterns were scored by the three judges according to how closely the patterns corresponded to their names using five point scale, where rating of 4 and 5 mean “good” and “very good” correspondence. Additionally, the recognizable pattern received an average correspondence rating of at least 4 was further evaluated. If it was judged to be creative by at least two of the judges, it was classified as a creative pattern.

In this experiment, 40.5 and 15 percent of the generated patterns were classified as recognizable and creative, respectively. The effect of the practice (repetition) were not confirmed.

Finke also conducted the experiments with slight modification in which the participants assembled using writing instruments or the transparent overlays on which the parts were drawn at one of three sizes. Because the experiment could not show the significant difference of the creativity or correspondence between the mental assembly (imaging) and the physical assembly (writing

Figure 2. Pattern Parts Utilized in Finke’s Experiment


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varies according to them. The change in the oxyHb correlates the change in the regional cerebral blood flow. The apparatus, therefore, can capture the change generated by the activation of the nervous activities of the brain.

2.2. Brain Activities Analysis Method

This study adopted the change in oxyHb which is the most sensitive indicators of the change in regional cerebral blood flow [15] and analyzed the signal as the following methods:

The moving average processing [16,17]: to remove the components originating from the slow fluctuations of cerebral blood flow, heartbeat, and body motion, the oxyHb signal was bandpass filtered between 0 and 0.2 Hz by employing a movement average value in five seconds. The frequency band ([0, 0.2]Hz) was set on the basis of the preliminary experiment. In the experiment, the oxyHb signals from three subjects conducting the hand drawing and resting tasks were measured, and it was found that the difference of the power spectrum distribution obtained by FFT signal processing between hand drawing and resting tasks is statistically significant in the bands above 0.2Hz (see “Appendix” for more information). Base line correction [18,19]: to remove the component originating from the fatigue of a participant which changes the oxyHb caused linearly with respect to time, the line connecting the average values of the two control tasks conducted before and after the target task was calculated and was subtracted from the oxyHb signals.

3. Cerebral Blood Flow Measurement during Creative Activities 3.1. Experimental Outline

This experiment aims to compare the cerebral blood flow of the participants working on the Finke’s pattern generation task by hand drawing and computer operation. The following description outlines the Finke’s task [11].

Finke suggested the importance of visualization in creative thinking and discovery and conducted some experiments in order to clarify the relationship between the visualization methods and the creativity of the output (patterns). One of the typical experiments was conducted the following procedures.

1) At the beginning of each trial, three of the pattern parts

were randomly selected from the fifteen parts (Fig. 2). In order to reduce the complexity difference between the combinations, the selecting condition was that the parts in the first two rows in Fig. 2 were three times as likely to be selected as the complex parts shown in the bottom row. The participants were instructed to close their eyes and to image assembling them to make a recognizable figure. The assembling restrictions are that all three parts are used, the parts can be deformed only by rotation and expansion/reduction, the assembling time is two minutes.

2) The participants were instructed to open their eyes and to write down the generated pattern with their names.

3) The generated patterns were scored by the three judges according to how closely the patterns corresponded to their names using five point scale, where rating of 4 and 5 mean “good” and “very good” correspondence. Additionally, the recognizable pattern received an average correspondence rating of at least 4 was further evaluated. If it was judged to be creative by at least two of the judges, it was classified as a creative pattern.

In this experiment, 40.5 and 15 percent of the generated patterns were classified as recognizable and creative, respectively. The effect of the practice (repetition) were not confirmed.

Finke also conducted the experiments with slight modification in which the participants assembled using writing instruments or the transparent overlays on which the parts were drawn at one of three sizes. Because the experiment could not show the significant difference of the creativity or correspondence between the mental assembly (imaging) and the physical assembly (writing

Figure 2. Pattern Parts Utilized in Finke’s Experiment

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instruments/overlays), Finke concluded that the creative patterns are generated serendipitously.

3.2. Experimental Method

(1) Subjects and devices: The sixteen right-handed healthy graduate/undergraduate students participated in this experiments (13 males, 3 females, ranging in age from 20 to 24 years). Before each experiment, informed consent was obtained from all of them. The ethics committee of Keio University approved this experiment.

A NIRS device (OEG-16, Spectratech Inc., Tokyo, Japan, Fig. 3(a)) was used for the measurements. This device includes six pairs of laser and photo diodes (illuminators and detectors) whose distance is 30mm (Fig. 3(b)). The measurement brain regions, termed as channels (CHs) were the PFC (Fig. 3(c)), and the sampling frequency was 1.6Hz. In order to minimize the motion difference between the hand drawing and computer operation (allocating, rotating, and expanding/reducing the preformed pattern parts depicted in Fig. 4), a pen tablet type display (LP-700, WACOM Co., Saitama, Japan) was used. This means that the participants conducted both the hand drawing and computer operation using the display and electronic pen

(Fig. 5). (2) Procedure: The block design of this experiment is depicted in Fig. 6. Each block consists of the following tasks: “control task 1 (30s)”, “assembling task (120s)”, “writing down task (30s)”, and “control task 2 (30s)”. The detail descriptions of them are described below.

In the assembling task, the participants were instructed to assemble the three parts randomly selected from the parts in Fig. 2 and generated the pattern. The assembling used the electronic pen and pen tablet type display and adopted two methods: free hand drawing using the Microsoft Paint (hereinafter called hand drawing assembly, Fig. 7(a)) and computer operation using the Microsoft Power Point (hereinafter called computer operating assembly, Fig. 7(b)). The former one made the participants repeat the action of drawing the three parts (generating ideas) and delating them. The latter let them to operate (e.g. allocate, rotate, expand/reduce depicted in Fig. 4) the pre-made three parts. The participants were allowed to generate several patterns (ideas) but were prohibited to leave the generated patterns on the display in order to confirm the difference between the hand drawing and computer operating assemblies. This banned the change from the assembling task to the task for

Figure 3. NIRS Device and Measured Regions

(b) Location of laser and photo diodes (c) Measured regions termed as channels (CHs)

(a) NIRS (OEG-16)

2

3

5

6

8

91 4 7 10

11

12

14

1513 16

: Laser diodes : Photo diodes

30 30

Figure 4. Conceptual Drawing of Computer Operation (a) Allocating (b) Rotating (c) Expanding/reducing


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modifying the generated patterns left on the display. The control tasks of the hand drawing and computer operating assemblies should be set to minimize the difference of the participant motion between the control and assembling

tasks in order to reduce the cerebral blood flow fluctuation. Therefore, in the control task, the participants were instructed to conduct the hand drawing and computer operation, respectively. Note that they used one part (not

Figure 7. Assemblies by Hand Drawing and Computer Operation

(b) PC operation assembly (a) Hand drawing assembly

Figure 6. Block Design of Experiment

Control 1 Assembling (hand drawing or computer operation)* Writingdown Control 2

0 30 150 180 210Time [sec]

Block 1 Block 2 Block 10hand

drawing* computer

operation*hand

drawing*

* Hand drawing or computer operation is randomly selected five times each

Pen tablet type display

Response sheet

NIRS(OEG-16)

Pen

Figure 5. Participant and Experimental Devices


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three) in order not to conduct assembling. The writing down task made them to remind and draw all the generated patterns with their names on the response sheet. Each participant conducted the block ten times: five times of each assembly type. The order of the assembly types is randomly decided.

After the measurement, in order to compare the two assemblies, we tabulated the figures for the following items: 1) “the ease to create” evaluated by the participants on a scale of 1 to 5 (“very poor” to “very good”); 2) “the correspondence” and “the creativity” of the generated patterns (used in Finke’s experiment [11]) evaluated by the three evaluators who understand the Finke’s assessment well; 3) on the same scale; 3) the number of the generated patterns.

3.3. Experimental Result and Discussion

The examples of the generated patterns are shown in Fig. 8. The evaluation result of the three items (ease to create, creativity, and correspondence) and the number of the generated ideas are summarized in Table 2. The table lists the average and standard deviation of them. The significant difference between hand drawing and computer operation could not be confirmed among all the items, similar to the Finke’s experimental result.

The activated brain regions (CHs) of each participant and each assembly are tabulated in Table 3. The activation was judged by the difference of the concentration change in oxyHb ( coxy) average for twenty seconds between the control and assembling tasks. The Wilcoxon rank-sum test was performed to confirm the statistical significant difference because a nonparametric test is insusceptible to

the outliers. The asterisks “*” and “**” in Table 3 indicate the statistical difference of the coxy average between the control and assembling tasks at the 5 and 1 percent level, respectively. Note that the significance level evaluates the qualitative difference (rank-sum) of the coxy average, not the quantitative difference. This means the lower significance probability becomes, the higher the number of the coxy average data in assembly tasks exceeding/falling below those in control tasks becomes. Additionally, due to the difference in the cerebral blood flow increase rate caused by both tasks and participants, we calculated the averages for the nine time ranges of the assembling task (0-20s, 10-30s, 20-40s, 30-50s, 40-60s, 50-70s, 60-80s, 70-90s, and 80-100s) and adopted one of them that maximizes the difference from the average of the control task. The reason of eliminating the time ranges of 90-110s and 100-120s is that some participants stopped assembling during the time ranges. Table 3 shows the computer operation activates more channels, especially in the right PFC, than the hand drawing. The Wilcoxon test was performed to compare the activation amount (i.e. average difference between control and assemble tasks) between the two assemblies in each channel. The result reveals that the

Table 2. Result of Assessments

Evaluation items Hand drawing Computer drawing

Ease to create 2.62 (1.45) 2.23 (1.09)

Creativity 2.97 (0.30) 3.03 (0.28)

Correspondence 2.73 (0.31) 2.75 (0.27)

Drawing number 7.38 (2.87) 6.23 (2.17)

Mean value (S.D.)

Figure 8. Examples of Generated Patterns (Ideas)

(Tree) (House)(Snowman with

bamboo hat)(Snowman with

high nose)

Selected parts Selected parts

Generated ideas Generated ideas


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activation amount in the computer operation is larger than that in the hand drawing in all channels. The channels in which the difference is statistically significant at the 5 or 1 percent levels (Fig. 9) also indicate that the computer operation activates the regions in the right PFC.

Alexiou confirmed the right PFC in the open-ended problem solving task (design task) is activated more than that in the problem solving task in the conventional study [7]. Goel also suggested the importance of the right PFC for design thinking from the result of the experiment in which an architect with a lesion to the right PFC could not achieve the preliminary design in many cases [20]. Goel focused the architect could not concluded the Lateral Transformation (LT), which is one of the idea transformations from one idea to a slightly different idea rather than a more detailed

version of the same idea, and hypothesized that the LT is conducted by the right PFC.

On the basis of this hypothesis, the result of the experiment is considered to be caused by the experimental condition about the inchoate patterns on the display. In this condition, a participant can look the previous idea (i.e., pattern pars being operated by himself) in the computer operation but cannot in the hand drawing, in which he repeats the action of drawing the parts and delating them. There is a possibility that the visual information made them to conduct LT in the computer operation and activated the right PFC. However, the difference of neither the creativity evaluation nor the number of generated patterns was not confirmed between the computer operation and hand drawing in this study though LT is said to be effective to generate a design idea [20]. The reason can be considered that the Finke’s pattern generation task (assembling the selected three parts) is very limited design task (i.e. similar to the problem solving task) compared to the Goel’s one. This suggests the need for the further research in which the experiment employs the tasks similar to an actual design activities. This study also suggests the need to consider the assembling methods (e.g., hand drawing and computer operating) in more detail in order to compare the ways of idea transformations in the methods because the

Table 3. Brain Regions (CHs) Where Concentration Change in oxyHb ( coxy) Increases or Decreases According to Assembly Subject

No.Hand drawing Computer operation

Increase in oxyHb Decrease in oxyHb Increase in oxyHb Decrease in oxyHb

1 2** 1*/3*/10*2 2*/11** 1**/3-4*/16** 3*/12**

3 11-14** 4**/7**/8*/11**/13-14**/16**

4 11* 3*/6**/10*56 4*/10* 1*/2*/6**/15 7*/8**/10**7 14*/16* 16*8 8*/10*/13* 5**/7**/11*9 1**/3**/15**

10 1-2*/3-7**/13-16** 1*/3*/4**/6**/7**11 5*12

13 1**/2*/3**/4-6* 1-4*/5-6**/8-9**/11**/13-14**/15*

14 3-4**/5*/6-12**/13-14*/15-16** 3*/5*/15**

15 1* 4** 3**/5**/7-12**

16 4*/5*/10*/11**/13*/14**/16* 6*/7*/11*/13*/14** 8*

Note: the asterisks “*” and “**” indicate the statistical difference of the oxyHb average between the control and assembling task at the 5 and 1 percent level, respectively

Activated More Than Hand Drawing

2

3

5

6

8

91 4 7 10

11

12

14

1513 16 : P<0.01

: P<0.05

Figure 9. Brain Regions (CHs) Where PC Operation


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experimental result indicates the difference of the brain activation between the ways.

This study conducted an additional experiment in order to confirm the effect of the visual information (i.e., previous idea). In the experiment, three male participants conducted the hand drawing assemblies by looking the previous idea or not. The other experimental conditions are same as the previous experiment. The comparison of the two hand drawing assemblies is summarized in Fig.10. This figure shows the channels in which the mean value of the activation amount during the assembly using the previous idea is larger than that during the assembly without it and the difference is statistically significant at the 5 or 1 percent levels by Wilcoxson test. This result indicates the act of looking the previous idea activates the right PFC and suggests the need to consider the ways of idea transformations included in the assembling methods, as referred to above.

4. ConclusionThis study measured the cerebral blood flow and the

qualitative assessment of the creativity when the participant conducted the creative task (Finke’s pattern generation task) employing the hand drawing or computer operation. Although the significant difference of the qualitative assessment between them could not be confirmed, the computer operation activates more channels (brain regions), especially in the right prefrontal cortex, than the hand drawing. Unlike the hand drawing, the computer operation in this study allowed the participants to look the previous idea (pattern). The right prefrontal cortex (PFC) activation, therefore, is considered to be caused by the lateral transformation (LT), which is one of the idea transformations from one idea to a slightly different idea rather than a more detailed version of the same idea. To confirm the effect of the act of looking the previous idea, this study conducted the additional experiment to compare the hand drawing with and without the act. The result indicates the act activates the right PFC and supports the hypothesis of the activation caused by the LT. This suggests the need to consider not only the assembling methods (e.g., hand drawing and computer operation) but also the ways of idea transformations in order to compare the brain activities regarding design activities.

The future research includes the experiment using an eye-tracking system or the protocol analysis in order to confirm the way of idea transformations.

Acknowledgements This study was partly supported by the Japan Society for

the Promotion of Science, Grant-in-Aid for Young Scientists (B) (26750005 and 18K18318), and was conducted with the permission from the ethics committee of Keio University and the informed consents from all participants. We would like to express our gratitude to all of them.

Figure 11. Power Spectrum Distributions Transformed from oxyHb Signals

0.2

2

3

5

6

8

91 4 7 10

11

12

14

1513 16 : P<0.01

: P<0.05

Figure 10. Brain Regions (CHs) Where Hand Drawing Using Previous Idea Activated More Than Hand Drawing without It


Appendix Figure 11 is a result of the preliminary experiment

mentioned in the illustration of the moving average processing (Section 2.2). This figure is the power spectrum distributions transformed from the oxyHb signals of a subject conducting hand drawing and resting, using FFT signal processing. The remarkable difference of them can be shown in the frequencies above 0.2Hz.

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