Abstract
In this paper, we present how mobile electroencephalography, or mobile EEG, is becoming a relevant tool of urban studies, including among others, spatial cognition, architecture, urban design and planning. Mobile EEG is a research methodology that requires tightly controlled experiments and complicated analytical tools, but it is increasingly used beyond the clinical and research context to monitor brain function and cognition in real world. It is used to unravel our understanding of the neural processes that enable spatial perception and cognition, while is also applied to the study of psychological transactions between people and the environment, for example to gauge the effects of urban or natural environments on the emotional state of pedestrians. In the near future, mobile EEG could be integrated in the research on cities as a tool to understand the cognitive foundations of urban movement, assess the psychological impact of environments on individuals, or target interventions to improve the quality of the urban environment. In this paper we review relevant research with mobile EEG, as well as the background and methodological issues arising in such projects.
Highlights
Recent technological advances, especially relatively low-cost electroencephalography (EEG) data acquisition equipment and open-source analytical tools, make possible the adoption of EEG outside its traditional clinical or neuroscience context into new domains of research
Spatial cognition abilities vary between individuals (Hegarty et al 2002), and between different scales of space (Montello 1993) and here we focus on what Montello (1993) calls the ‘environmental scale’: large-scale environments, such as buildings and cities, that cannot be observed from a single location
This paper has provided a review of what mobile EEG is, how it is used to understand spatial cognition and the psychological effects of space and even dynamically transform it, as well as the basic research principles employed in such studies
Summary
Especially relatively low-cost electroencephalography (EEG) data acquisition equipment and open-source analytical tools, make possible the adoption of EEG outside its traditional clinical or neuroscience context into new domains of research. Analysing the movement of people in the city, can offer various insights, for example about how the city is used or the spatiotemporal movement of different groups These are relevant to traditional questions of transport, planning and design, and as part of various smart-city efforts, which posit urban sensing as a shift to more efficient management of existing resources and infrastructure (cf Kitchin 2014; Townsent 2013). These news kinds of data and data analysis methods, have wider applications to the understanding the cognitive mechanisms underlying urban movement itself (Manley et al 2015), what kinds of environments encourage walking (Middleton 2011), or the health benefits of cycling (Woodcock et al 2014), with the implications for behaviour change, advocacy, design and policy to create better urban environments
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