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10.1371/journal.pone.0183890 http://scihub22266oqcxt.onion/10.1371/journal.pone.0183890 C5595286!5595286!28898244     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+One 2017 ; 12 (9): ä Nephropedia Template TP {{tp|p=28898244|t=2017. NeuroPlace: Categorizing urban places according to mental states |pdf=|usr=}}{{28898244}} gab.com Text NeuroPlace: Categorizing urban places according to mental states JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=28898244 #FOAvip 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. Twit Text FOAVip NeuroPlace: Categorizing urban places according to mental states ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=28898244 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28898244 #FOAvip English Wikipedia <ref>{{Cite pmid|28898244}}</ref> NeuroPlace: Categorizing urban places according to mental states #MMPMID28898244 Al-barrak L; Kanjo E; Younis EMG PLoS One 2017[]; 12 (9): ä PMID28898244show ga 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. äNeuroPlace: Categorizing urban places according to mental states (epmc).pdf DeepDyve Pubget Overpricing