Abstract
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 how 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.
Highlights
The increase in stress-related illnesses is escalating dramatically in the world
One-way repeated measures Analysis of Variance (ANOVA) is a statistical method used to decide whether a feature shows a significant difference between two or more classes and to identify important features to classify mental states
Meditation levels and frequency bands of subjects are plotted to illustrate the changes in levels as they move from place to place and the duration of the experiment in each place
Summary
The increase in stress-related illnesses is escalating dramatically in the world. Stress can be a chronic disease that is difficult to detect and is often associated with a stigma of embarrassment and humiliation. Many researchers have begun to explore BCI technology as a new way of communication and control for disabled people. Current BCI systems use EEG activity recorded at the scalp to control devices and assist people with neuromuscular impairments. Many companies are offering portable and low cost EEG devices to enable the new applications of BCI [3][4][5]. We used commercially available mobile EEG devices that can be used in outdoor environments to enable different emerging applications
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