NeuroPlace: Categorizing urban places according to mental states

Lulwah Al-barrak, Eiman Kanjo, Eman M. G. Younis, Boris Podobnik
2017 PLoS ONE  
Urban spaces have a great impact on how people's emotion and behaviour. There are number of factors that impact our brain responses to a space. This paper presents a novel urban place recommendation approach, that is based on modelling in-situ EEG data. The research investigations leverages on newly affordable Electroencephalogram (EEG) headsets, which has the capability to sense mental states such as meditation and attention levels. These emerging devices have been utilized in understanding
more » ... human brains are affected by the surrounding built environments and natural spaces. In this paper, mobile EEG headsets have been used to detect mental states at different types of urban places. By analysing and modelling brain activity data, we were able to classify three different places according to the mental state signature of the users, and create an association map to guide and recommend people to therapeutic places that lessen brain fatigue and increase mental rejuvenation. Our mental states classifier has achieved accuracy of (%90.8). NeuroPlace breaks new ground not only as a mobile ubiquitous brain monitoring system for urban computing, but also as a system that can advise urban planners on the impact of specific urban planning policies and structures. We present and discuss the challenges in making our initial prototype more practical, robust, and reliable as part of our on-going research. In addition, we present some enabling applications using the proposed architecture. PLOS ONE | https://doi.org/10.1371/journal.pone. Kaplan [1] . Today, many people restore attention and seek relief through meditation or outdoor recreation. Nature and urban environments offer a restorative experience that may impact individuals' well-being. However, some environments are hectic and might not relieve stress or remedy attention problems and exhaustion. Given today's technological advances, several studies have emerged which can be utilized to assess the effects of built environments on humans using physiological sensors. For instance, heart rate monitors and skin conductivity sensors, have shown enhanced results following the exposure to restorative environments. Recently, affordable wireless Electroencephalogram (EEG) headsets capturing the electric potentials of neuronal populations have become available. Originally designed for Brain-Computer Interfaces (BCI) to assist physically impaired individuals, BCI also carries new research prospects applications in many domains. In this work, we study brain signals in an attempt to understand the effects of outdoor built environments on mental activity, and in particular: the restorative state. In addition, we provide an objective measure of how different place categories impact our mental states. This paper achieves this goal by employing low-cost EEG devices for data collection and analysis. A predictive model is then built in order to provide a better understanding of how the exposure to different outdoor environments may foster or hinder recovery from stress, the investigation also correlates the mental state with environmental acoustic noise levels. The built environments considered in this work consist of both green spaces and urban built areas, and hence allow us to know how the exposure to natural green spaces may promote greater attention restoration and stress recovery than visiting built environments. In the final part of the work, we present two classification techniques for the mental state results and visually represented on geographical maps to recommend relaxing environments for people in order to alleviate stress.
doi:10.1371/journal.pone.0183890 pmid:28898244 pmcid:PMC5595286 fatcat:n7wtfom64fed7ny35a2nlmceiu