多重:验证城市中的多模式认知数据:建立城市环境如何影响街景用户的模型

Arlene Ducao, Ilias Koen, Zhiqi Guo
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引用次数: 6

摘要

multitimer是一项新技术,旨在提供数据驱动的理解人类如何认知和物理体验空间环境。通过多模态测量生物传感器数据来模拟建筑环境及其用途如何影响认知过程,Multimer旨在帮助建筑师、工作场所战略家和城市规划者等空间专业人士进行更好的设计干预。Multimer可能是第一个收集生物传感器数据的空间技术,如脑电波和心率数据,并使用时空和神经生理学工具进行分析。multitimer移动应用程序可以记录来自几种常用的、廉价的可穿戴传感器的数据,包括脑电图、心电图、计步器、加速度计和陀螺仪模块。Multimer应用程序还通过其用户界面和微调查记录用户输入的信息,然后使用GPS、信标和其他定位工具将所有这些数据与用户的地理位置相结合。Multimer的研究平台可以在个人和总体层面实时显示所有这些数据。Multimer还通过比较收集到的传感器数据和时空背景下的情感数据来验证数据,然后将收集到的数据与其他数据集(如公民报告、交通数据和城市设施)整合起来,为站点和空间的评估和重新设计提供可操作的见解。本报告介绍了2017年8月至10月在纽约市对101名受试者进行的多重研究的数据验证过程的初步结果。最终,本研究的目的是建立一个可复制的、可扩展的模型原型,以研究建筑环境和交通运动如何影响行人、骑自行车的人和司机的神经生理状态。
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Multimer: validating multimodal, cognitive data in the city: towards a model of how the urban environment influences streetscape users
Multimer is a new technology that aims to provide a data-driven understanding of how humans cognitively and physically experience spatial environments. By multimodally measuring biosensor data to model how the built environment and its uses influence cognitive processes, Multimer aims to help space professionals like architects, workplace strategists, and urban planners make better design interventions. Multimer is perhaps the first spatial technology that collects biosensor data, like brainwave and heart rate data, and analyzes it with both spatiotemporal and neurophysiological tools. The Multimer mobile app can record data from several kinds of commonly available, inexpensive, wearable sensors, including EEG, ECG, pedometer, accelerometer, and gyroscope modules. The Multimer app also records user-entered information via its user interface and micro-surveys, then also combines all this data with a user's geo-location using GPS, beacons, and other location tools. Multimer's study platform displays all of this data in real-time at the individual and aggregate level. Multimer also validates the data by comparing the collected sensor and sentiment data in spatiotemporal contexts, and then it integrates the collected data with other data sets such as citizen reports, traffic data, and city amenities to provide actionable insights towards the evaluation and redesign of sites and spaces. This report presents preliminary results from the data validation process for a Multimer study of 101 subjects in New York City from August to October 2017. Ultimately, the aim of this study is to prototype a replicable, scalable model of how the built environment and the movement of traffic influence the neurophysiological state of pedestrians, cyclists, and drivers.
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