Mediated Atmospheres
Name
17161.JosephA.Paradiso.Preprint1.pdf
Description
Accepted version
Size
3.97 MB
Format
Adobe PDF
Checksum (MD5)
d3af7f1cb937502fe5198aa03f121485
Author(s)
Zhao, Nan
Azaria, Asaph Mordehai Assaf
Paradiso, Joseph A
Alternative Title
A Multimodal Mediated Work Environment
Date Issued
June 2017
Journal
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Publisher
Association for Computing Machinery (ACM)
Citation
Zhao, Nan et al. "A Multimodal Mediated Work Environment." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 2 (June 2017): 31 © 2017 ACM
Version
Author's final manuscript
Abstract
Atmosphere - the sensorial qualities of a space, shaped by the composition of light, sound, objects, people, etc. - has remarkable influence on our experiences and behavior. Manipulating it has been shown to be powerful, affecting cognitive performance, mood and even physiology, our work envisions and implements a smart office prototype, capable of digitally transforming its atmosphere - creating what we call Mediated Atmospheres (MA) - using computationally controlled lighting, video projection and sound. Additionally, we equipped this space with a modular real-time data collection infrastructure, integrating a set of biosignal sensors. Through a user study (N=29) we demonstrate MA's effects on occupants’ ability to focus and to recover from a stressful situation. Our evaluation is based on subjective measurements of perception, as well as objective measurements, extracted from recordings of heart rate variability and facial features. We compare multiple signal processing approaches for quantifying changes in occupant physiological state. Our findings show that MA significantly (p<0.05) affect occupants’ perception as well as physiological response, which encouragingly correlate with occupants’ perception. Our findings is a first step towards personalized control of the ambient atmosphere to support wellbeing and productivity.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3090096
