Mapping Biometric Signals to Support Spatial Design

Arlene Ducao

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. The Multimer mobile app can record data from several kinds of commonly available, inexpensive, wearable sensors, including EEG (electroencephalogram), ECG (electrocardiogram), 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 socioeconomic, environmental, and municipal data sets to provide actionable insights towards the creation of sites and spaces.

This report presents final technical results for a Multimer study supported by the National Science Foundation SBIR program (NSF#1721679). The study area was in Manhattan south of Central Park, New York City, USA. The study involved training 101 pedestrians, cyclists, and drivers to record biosensor, survey, and comment data over the course of twelve weeks, from 01 August 2017 to 31 October 2017. The study specifically focused on Manhattan south of Central Park, which has a gridded, high-traffic area that simplified high-volume data collection and uniform spatial analysis. 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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