Al-Barrak Lulwah, Kanjo Eiman, Younis Eman M G
Bristol University, Computing Department, Bristol, United Kingdom.
Department of Computing and Technology, Nottingham Trent University, Nottingham, United Kingdom.
PLoS One. 2017 Sep 12;12(9):e0183890. doi: 10.1371/journal.pone.0183890. eCollection 2017.
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.
城市空间对人们的情绪和行为有着巨大影响。有许多因素会影响我们大脑对空间的反应。本文提出了一种新颖的城市场所推荐方法，该方法基于对现场脑电图（EEG）数据进行建模。该研究利用了新出现的价格亲民的脑电图耳机，其能够感知诸如冥想和注意力水平等心理状态。这些新兴设备已被用于了解人类大脑如何受到周围建筑环境和自然空间的影响。在本文中，移动脑电图耳机被用于检测不同类型城市场所中的心理状态。通过分析和建模大脑活动数据，我们能够根据用户的心理状态特征对三个不同场所进行分类，并创建一张关联地图，以引导和推荐人们前往能减轻大脑疲劳并增强精神恢复能力的治疗性场所。我们的心理状态分类器准确率达到了90.8%。NeuroPlace不仅作为一种用于城市计算的移动无处不在的大脑监测系统开辟了新天地，还作为一种能够就特定城市规划政策和结构的影响向城市规划者提供建议的系统。作为我们正在进行的研究的一部分，我们展示并讨论了使我们的初始原型更实用、更强大和更可靠所面临的挑战。此外，我们还展示了一些使用所提出架构的赋能应用。
