ISSN: 2717-4417

Document Type : Research Paper


Department of Urban Planning, Faculty of Art & Architecture, Tarbiat Modares University, Tehran, Iran.



- The curvature in the street makes it more exciting, and greater variety in curvature causes more arousal and pleasure.
- Streets with medium enclosure (1:2 and 1:1) exhibit the most desirable values of size and enclosure.
- The presence of a square or a prominent building, the permeability of the street, and the variation in its landscape increase the pleasantness and arousal.
- The three-dimensional rhythms of the street walls exhibit greater pleasure and arousal than the two-dimensional rhythms.
- The portable EEG devices (MindWave MW001 headset) are suitable for evaluation of environmental design interventions in the field of architecture and urban development.
The environment can cause positive and negative emotions in citizens. Emotions are important due to their impacts on people’s behaviors, because emotions make up a main component of social behavior, and extraction of emotional responses is one of the best ways to understand different fields of experience and perception. Nowadays, mental health problems and the emphasis on increasing social interactions have led to more and more concern for the subject of emotions, but the impact of physical-spatial factors has received less attention from the conducted studies. The aim of this study is to investigate the effect of the physical-spatial measures of urban streets on pedestrians’ emotional responses by placing the individual in a pseudo-real environment. Moreover, this study makes possible the use of a new neural measurement tool in urban studies and evaluates its accuracy.
Theoretical Framework
The review of previous studies demonstrated that the environmental parameters that can affect emotion include non-physical human factors on the one hand and physical ones on the other. The physical factors that make up the subject of this research can be divided into two categories: 1- non-artificial factors, i.e. green space, and 2- artificial factors, which include the size and enclosure of the space, the shape and form of the space, the characteristics of the surfaces including architectural style, the color and texture of materials, and the variation in spatial sequences. Given the number of studies conducted on the effect of natural factors and certain characteristics of surfaces in the field of architecture, the present research examined four physical parameters.
Ten of the most important physical-spatial variables that make up different states and types of the spatial structure of an urban street, which can affect the individual emotions of pedestrians, were selected for investigation and used to design 18 tests. The research was conducted with a combined method consisting of: 1- a self-report method of Self-Assessment Manikin (SAM) images and 2- a neurological method using electroencephalography. In the EEG method, the single-channel MindWave MW001 headset, produced by Neurosky, was used as the instrument. The research population included 50 students of Tarbiat Modares University. The research was conducted with the help of controlled experiments using the mobile digital 3D modeling technique, which makes it possible for people to navigate the virtual street in the city. After the data extracted by the health and Stroop tests were confirmed, the data analysis was made using a quantitative-statistical method.
Results and Discussion
The findings regarding the shape and form of the space demonstrated that people feel more pleased in curved streets than in straight streets, and there is greater arousal in streets of the former than the latter shape. However, the level of control in a straight street is higher than that in a curved or spiral street. As for the size and enclosure of the urban space, the results indicated that there is greater pleasure in a street with medium enclosure (1:2 and 1:1) than in one with low or high enclosure (1:4 and 1:1.2), but streets with medium enclosure exhibit less arousal. Spaces with less enclosure cause people to have more control over the space. The results also demonstrated that the pleasure and arousal experienced by people is increased by the existence of the square as a spatial element and a landmark building as a physical element, permeability in the spatial structure of the street and brokenness in the path, and variation in the landscape of the street. It was only in the street with physical retraction and protrusion that no effect on arousal was observed, although the level of pleasure should increase. Moreover, the results indicated that the pleasure in the street with the curved corner was greater than that with the other forms. However, the shape of the street corner exhibits no effect on the arousal. Furthermore, the walls that are completely three-dimensional exhibit greater pleasure and arousal than those featuring walls with two-dimensional and three-dimensional rhythms. Finally, the walls that are completely two-dimensional have the least pleasantness and arousal. There is a higher level of control in the street with 2D rhythms than in that with 3D rhythms. The results also showed that visual permeability in the physical structure of the street increases the arousal and control of the space, but it has no effect on the pleasure. Another result of this research is that there is 75% conformity in the results obtained from the two methods of SAM and EEG, which demonstrates that the data (EEG) extracted from the device can extract people’s emotions well.
In general, the current research confirms the results of previous studies, but it precisely demonstrated by measuring the extracted neural data that the levels of emotional pleasure, arousal, and control are affected by the shape and form of the street, the size and enclosure of the street space, the presence of a spatial and physical element that creates attention and emphasis in the street, permeability in the spatial structure of the street, rotation along the street and perspective change along the path, two and three-dimensional wall street rhythms, and the shape and form of the corners of the street intersection. However, physical indentations and protrusions exhibit no effect on arousal, and visual permeability has no effect on pleasure. In addition, the results showed that the EEG data extracted from the headset (MindWave MW001) used in this study could well capture the emotions of individuals, thus making up a proper potential tool for evaluation of environmental design interventions in the field of architecture and urban planning. The results of the present study, which indicate the psychological effects of urban design of a street, help to select and design the appropriate elements and physical characteristics of the space, increase positive emotions and reduce negative emotions, and ultimately improve the mental health of citizens.
This article is taken from the doctoral thesis of urban planning with the title "Explaining the effects of the physical-spatial components of an urban street on the emotional stimulation of pedestrians with an emphasis on the use of neuroscience" which was defended by the first author with the guidance of the second author and the advice of the third author in the Tarbiat Modares University.


Main Subjects

Alavi Belmaani, M. (2008). Application of Video Ecology Topics (The Effect of Human Visual Structure) In the Formation of Design Indicators of Urban Walls. Thesis, master of urban planning, Tarbiat Madras University, Tehran.[in Persian]
Alexander, (1977). A Pattern Language. NewYork: Oxford University Press.
Alnemari, M. H. (2017). Integration of a Low Cost EEG Headset with The Internet of Thing Framework, Thesis, master of science in Computer Engineering, University of California, Irvine.
Alter, A. (2012). Drunk Tank Pink: and Other Unexpected Forces That Shape How We Think, Feel, and Behave. New York: The Penguin Press.
Appleton J. (1975) The Experience of Landscape, Chichester: John Wiley and Sons.
Arifin, S. & Cheung, P.Y.K. (2007). A Computation Method for Video Segmentation Utilizing the Pleasure- Arousal-Dominance Emotional Information. Proceedings of the 15th international conference on Multimedia: 68–77.
Baker, J., Levy, M., Grewal, D. (1992). An Experimental Approach to Making Retail Store Environmen- Griffitt. William (1970), Environmental effects on interpertal decisions. Journal of Retailing, 68 (4), 445-60.
Bar, M. & Neta, M. (2008). The Proactive Brain: Using Rudimentary Information to Make Predictive Judgments. Journal of Consumer Behaviour, 7(4-5319-330.
Barrett, F. L. (2006). Solving the Emotion Paradox: Categorization and the Experience of Emotion. Personality and Social Psychology Review, 10(1), 20-46.
Berto, R. (2014). The Role of Nature in Coping with Psycho-Physiological Stress: a Literature Review on Restorativeness. Behavioral sciences (Basel, Switzerland), 4(4), 394–409.
Beer, (1992). What Color Tells Us. Stuttgart: KreuzVerlag.
Bradley, M. M. & Lang, P. J. (1994). Measuring Emotion: the Self-Assessment Manikin and the Semantic Differential. Journal of behavior therapy and experimental psychiatry, 25 (1), 49–59.
Brooker, G. & Stone, S. (2007) Basics Interior Architecture: Form+Structure. Switzerland: AVA publishing SA.
Caicedo, D.G. & Van Beuzekom, M. (2006). How Do You Feel? An Assessment of Existing Tools for the Measurement Of Emotions and Their Application in Consumer Product Research. Delft University of Technology, Department of Industrial Design.
Carbon, C.C. & Leder, H. (2005). The wall Inside the Brain: Overestimation of Distances Crossing the Former Iron Curtain. Psychonomic Bulletin & Review, 12(4), 746-750.
Chebat, J.C. & Michon, R. (2003). Impact of Ambient Odors on Mall Shoppers’ Emotions, Cognition, and Spending: a TESt of Competitive Causal Theories. Journal of Business Research, 56(7), 529–539.
Cortes, A. B. C. & Morales, E. F. (2016). Emotions and the Urban Lighting Environment: A Cross-Cultural Comparison. SAGE Open, 6(1), 1-8.
Demirbilek, O. (2017). Evolution of Emotion Driven Design. In: Emotions and Affect in Human Factors and Human-Computer Interaction, Academic Press, Elsevier Inc.; San Diego, 341-357.
Dormann, C. (2006). Cultural Representations in Web Design: Differences in Emotions and Values. In: McEwan, T., Gulliksen, J., Benyon, D. (eds) People and Computers XIX — The Bigger Picture. Springer, London, 285-299.
Gartner, G. (2010). Emotional Response to Space as an Additional Concept of Supporting Way-Finding in Ubiquitous Cartography. In: Mapping Different Geographies, Springer Berlin Heidelberg, Germany, 67-73.
Gehl, J. (2003). Life between Buildings: Using Public Space. Copenhagen: Danish Architectural Press.
Franz, , von der Heyde, M. & Bülthoff, H. H. (2004). Predicting Experiential Qualities of Architecture by its Spatial Properties. Proceedings 18th IAPS-Conference,Vienna:1-10.
Franz, G. (2006). Space, Color and Perceived Qualities of Indoor Environments. In Environment, Health and Sustainable Development (IAPS 19),1-8.
Frölich, J., Schneider, S., Kuliga, S., Bielik, M. & Donath, D. (2015) Raumsynth – An Experimental Setup for Investigating the Relationships between Urban Form and Spatial Experience Based on Fechner’s Method of Production. 10th International Space Syntax Symposium,London: UCL.
Gayathri, P. (2016). A New Step in Brain Computer Interaction Towards Emotion Recognition and Prediction. International Journal of Science, Engineering and Technology Research (IJSETR), 5(6), 1882-1890.
Geroimenko ,V. (2014). Augmented Reality Art: from an Emerging Technology to a Novel Creative Medium. Cham: Springer.
Girardi, D., Lanubile, F. & Novielli, N. (2017). Emotion Detection Using Noninvasive Low Cost Sensors. Proceedings of the 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), IEEE, San Antonio October 23-26, Texas: 125-130.
Gomez, R., Gomez, A. & Cooper, A. (2002). Neuroticism and Extraversion as Predictors of Negative and Positive Emotional Information Processing: Comparing Eysenck's, Gray's, and Newman's theories. European Journal of Personality, 16(5), 333-350.
Hamzi Hijazi, I., Koenig, R., Schneider, S., Li, X., Bielik, M., Schmit, G. & Donath, D. (2016). Geostatistical Analysis for the Study of Relationships between the Emotional Responses of Urban Walkers to Urban Spaces. International Journal of E-Planning Research, 5(1), 1-19
Henshaw, V., Mould, O., Kentish, C., Kilvert, E., Michaeladis, A. & Jamil, H. (2012). Emotion in Motion: A Methodology for investigating Emotional Response to the Streets and Urban Spaces in Hanley, Stoke-on-Trent. IAPS 2012 Conference, Human Experience in the Natural and Built Environment, 25 -29 Jun 2012, Strathclyde University, Glasgow.
Hoffken, S., Wilhelm, J., Grob, D., Bergner, B. S. & Zeile, P. (2014). EmoCycling– Analysen von Radwegen Mittels Humansensorik und Wearable Computing. Proceedings REAL CORP 2014 Tagungsband 21-23 May 2014, Vienna: 851-860.
Hogertz, C. (2010). Emotions of the Urban Pedestrian Sensory Mapping. PQN Final Report-Part B4, Documentation-Measuring Walking, Daniel Sauter & et al. COST ( The acronym for European Cooperation in Science and Technology).
Höök, K., Isbister, K. & Laaksolahti, J. (2006). Sensual Evaluation Instrument: Developing an Affective Evaluation Tool. In CHI '06 (pp 1163-1172), New York: ACM.
Hoppen, K., Batten, B., Chislett, H., & Ettedgui, J. (2000). In Touch: Texture in Design. Laurel: Glen publishers.
Hyun, S. S., Wansoo, K., & Myong, J. J. (2011). The Impact of Advertising on Patrons’ Emotional Responses, Perceived Value, and Behavioral Intentions in the Chain Restaurant Industry: the Moderating Role of Advertising-Induced Arousal. International Journal of Hospitality Management, 30(3), 689–700.
Huynh, Q., Craig, W., Janssen, I. & Pickett, W., (2013). Exposure to Public Natural Space as a Protectivefactor for Emotional Well-Being among Young People in Canada. BMC Public Health, 13(407), 1-14.
Iaconesi, S. & Persico, O. (2013). Harvesting Geo-located Emotional States from User Generated Content on Social Networks and Using Them to Create a Novel Experience of Cities. ESSEM 2013,Turin, Italy.
Izard,C. E. (2010). The Many Meanings/Aspects of Emotion: Definitions, Functions, Activation, and Regulation. Emotion Review, 2(4), 363-370.
Kasakin, H. & Mastandrea, S. (2009). Aesthetic Emotions and the Evolution of Architectural Design Styles. International Conference on Engineering and Product Design Education, 10 &11 September 2009, UK, University of Brighton: 501-506.
Kevin, M. L., Goldberg, A., & Michelbach, P. (2011). Understanding the Pursuit of Happiness in Ten Major Cities. Urban Affairs Review, 47(6), 861 –888.
Klettner, S. & Gartner, G. (2012).Modelling Affective Responses to Space, Proceedings REAL CORP 2012 Tagungsband, 14-16 May 2012, Schwechat: 485-491
Konig, R., Schneider, S., Hamzi, I., Li, X., Bielik, M., Schmitt, G. & Donath, D.(2014). Using Geo Statistical Analysis to Detect Similarities in Emotional Responses of Urban Space, Sixth International Conference on Design Computing and Cognition (DCC14), June, London, published by ETH, Zurich.
Krekel, C., Kolbe, J., & Wüstemann, H. (2015). The Greener, the Happier? The Effects of Urban Green and Abandoned Areas on Residential Well-Being. Ecological Economics,121(C), 117-127.
Kuppens, P. (2008). Individual Differences in the Relationship between Pleasure and Arousal. Journal of Research in Personality, 42(4), 1053–1059.
Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2005). International Affective Picture System (IAPS): Digitised Photographs, Instruction Manual and Affective Ratings. Technical Report A-6. FL: University of Florida, Gainesville.
Laroche, M., Teng, L., Michon, R., & Chebat, J. C. (2005). Incorporating Service Quality into Consumer Mallshopping Decision Making: A Comparison between English and French Canadian Consumers. Journal of Services Marketing, 19(3), 157–163.
Larsen R. J. & Ketelaar T. (1989). Extraversion, Neuroticism and Susceptibility to Positive and Negative Mood Induction Procedures. Personality and Individual Differences,10(12), 1221-1228.
Li, X., Hijazi, I., Koenig, R., Lv, Z., Zhong, C., & Schmitt, G. (2016). Assessing Essential Qualities of Urban Space with Emotional and Visual Data based on GIS Technique. ISPRS International Journal of Geo-Information, 5(11), 218-227.
Lynch, K. (1971). Site Planning, Cambridge: MIT Press.
MacKerron, G., Mourato, S. (2013). Happiness Is Greater in Natural Environments. Global Environmental Change, 23(5), 992–1000.
Madani nejad, K. (2007). Curvilinearity in architecture: emotonal effect of curvilinear forms in interior design. PhD Thesis, A&M University, Texas.
Matei, S., Ball-Roceach, S.J., QIU, J.L. (2001). Fear and Misperception of Los Angeles Urban Space: A Spatial-Statistical Study of Communication-Shaped Mental Maps. Communication Research, 28(4), 429-463.
Mehrabian, A. (1978). Measures of Individual Differences in Temperament. Educational and Psychological Measurement, 38(4), 1105-1117.
Mitchell, L.A. (2006). The Relationship between Emotional Recognition and Personality Traits.Thesis, master of Psychology, Rochester Institute of Technology, Rochester.
Montgomery, C. (2013). Happy City: Transforming Our Lives through Urban Design. Farrar: Straus and Giroux.
Morrison, M., Gan, S., Dubelaar, C., & Oppewal, H. (2011). In-Store Music and Aroma Influences on Shopper Behavior and Satisfaction. Journal of Business Research, 64(6), 558–564.
Nass, C., Jonsson, I.M., Harris, H., Reaves, B., Endo, J., Brave, S. & Takayama, L. (2005). Improving Automotive Safety by Pairing Driver Emotion And Car Voice Emotion. In CHI'05 Extended Abstracts on Human Factors in Computing Systems (1973-1976). ACM.
Naz, A., Kopper, R., McMahan, R. P. & Nadin, M. (2017). Emotional Qualities of VR Space. IEEE virtual reality (VR) conference, 18-22 March, Los Angeles, CA: 1-9.
Neuhaus, F.( 2011). New City Landscape - Mapping Urban Twitter Usage. Technoetic Arts: A Journal of Speculative Research, 9(1), 31-48
Nold, C., Jensen, O.B. & Harder, H. (2008). Mapping the City- Reflections on Urban Mapping Methodologies from GPS to Community Dialogue. Paper no.25, Department of Architecture and Design, Aalborg University, Denmark.
Perrins-Margalis, N.M., Rugletic, J., Schepis, N.M., Stepanski, H.R., & Walsh, M.A. (2000). The Immediate Effects of a Group-Based Horticulture Experience on the Quality of Life of Persons with Chronic Mental Illness. Occupational Therapy in Mental Health,16(1), 15-31.
Raslan, R., Al-Hagla, K. & Bakr, A. (2014). Integration of Emotional Behavioural Layer “EmoBeL” in City Planning. REAL CORP 2014 Tagungsband, 21-23 May,Vienna:309-317.
Rasmussen, E. (2000). Experiencing Architecture. Massachusetts: MIT Press.
Reddy, S.M., Chakrabarti, D. & Karmakar, S. (2012). Emotion and Interior Space Design: An Ergonomic Perspective. Work: A Journal of Prevention, Assessment and Rehabilitation, 41(1), 1072-1078.
Resch, B., Summa, A., Sagl, G., Zeile, P., & Exner, J-P. (2014). Urban Emotions — Geo-Semantic Emotion Extraction from Technical Sensors, Human Sensors and Crowdsourced Data. In: Progress in Location-Based Services 2014, 199-212.
Robinson, M.D., Ode, S., Moeller,K & Goetz, P.W. (2007). Neuroticism and Affective Priming: Evidence for a Neuroticism-Linked Negative Schema. Personality and Individual Differences, 42(7), 1221-1231.
Roe, J. J., Thompson, C. W., Aspinall, P. A., Brewer, M. J., Duff, E. I., Miller, D.,Clow, A. (2013). Green Space and Stress: Evidence from Cortisol Measures in Deprived Urban Communities. International journal of environmental research and public health, 10(9), 4086–4103
Rofe, , Weinreb, A. R. (2013). Mapping Feeling: An Approach to the Study of Emotional Response to Built Environment and Landscape. Journal of architectural and planning research, 30(2), 127-145.
Russell, J. (2003). Core Affect and the Psychological Construction of Emotion. Psychological Review, 110 (1), 172-145.
Russell, J. A., & Mehrabian, A. (1977). Evidence for a Three‐ Factor Theory of Emotions. Journal of Research in Personality, 11(3), 273-294
Ryu, K., & Jang, S.S. (2007). The Effect of Environmental Perceptions on Behavioral Intentions through Emotions: The Case of Upscale Restaurants. Journal of Hospitality & Tourism Research, 31(1), 56-72.
Salesses, P., Schechtner K., Hidalgo C. A. (2013). The Collaborative Image of the City: Mapping the Inequality of Urban Perception. PloS one, 8(7), e68400.
Shaftoe, (2008). Convivial Urban Spaces: Creating Effective Public Places. London: Earthscan.
Shemesh, A., Bar, M. & Grobman, J.Y. (2015). Space and Human Perception– Exploring Our Reaction to Different Geometries of Spaces. 20th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, Hong Kong: 541-550.
Silvia, P. & Barona, C. (2009). Do People Prefer Curved Objects? Angularity, Expertise, And Aesthetic Preference. Empir Stud Arts 27(1), 25-42.
Stamps, A. E. (2003). Advances in Visual Diversity and Entropy. Environment and Planning B: Planning and Design, 30(3), 449 - 463.
Tavassoli, M. (2019). Urban Design: The Art of Renewing Urban Structure with Four Case Studies. Tehran: Mahmoud Tavassoli. [in Persian]
Tsai, J. L., Chentsova-Dutton, Y., Freire-Bebeau, L., & Przymus, D. E. (2002). Emotional Expression and Physiology in European Americans and Hmong Americans. Emotion, 2(4), 380–397.
Tyson, G.A., Lambert, G., & Beattie, L. (2002). The Impact of Ward Design on the Behaviour, Occupational Satisfaction and Well-Being of Psychiatric Nurses. International Journal of Mental Health Nursing, 11(2), 94-102.
Van Hagen, M., Galetzka, M., Pruyn, A., & Peters J. (2009). Effects of Colour and Light on Customer Experience and Time Perception at a Virtual Railway Station. Experiencing Light 2009: International Conference on the Effects of Light on Wellbeing, 26-27 Oct 2009, Eindhoven University of Technology, Eindhoven: 137–145.
Wang,Y. & (2018) Validation of Low-Cost Wireless EEG System for Measuring Event-Related Potentials. 29th Irish Signals and Systems Conference (ISSC), June 2018.
Wang, Y., Wang, Z., Clifford, W., Markham, C., Ward, T. E., & Deegan, C. (2018). Validation of Low-Cost Wireless EEG System for Measuring Event-Related Potentials. 29th Irish Signals and Systems Conference (ISSC), 21-22 June, Belfast: 1-6.
Watson, D. & Tellegen, A. (1985). Toward a Consensual Structure of Mood. Psychological Bulletin, 98(2), 219-235.
Zeile, P., Hoffken, S. & Papastefanou, G. (2009). Mapping People? The Measurement of Physiological Data in City Areas and the Potential Benefit for Urban Planning. Real CORP 2009, 22-25 April 2009, Sitges: 341-352.
Zeile, P., Resch, B., Exner, JP., Sagl, G. (2015). Urban Emotions: Benefits and Risks in Using Human Sensory Assessment for the Extraction of Contextual Emotion Information in Urban Planning. In: Geertman, S., Ferreira, Jr., J., Goodspeed, R., Stillwell, J. (eds) Planning Support Systems and Smart Cities. Lecture Notes in Geoinformation and Cartography. Springer, 209-225.