@inproceedings{52c9f98686664c179303c65b24575163,
title = "Reference Signal-Based Method to Remove Respiration Noise in Electrodermal Activity (EDA) Collected from the Field",
abstract = "Measuring built environment users' response using wearable biosensors could provide a new opportunity for understanding their experience in built environment. Electrodermal activity (EDA) sensors are especially useful in detecting people's stressful interaction with the built environment. Despite this potential advancement, the detection accuracy is still limited because of noises in EDA collected from uncontrolled settings. Alleviating respiration noise is most challenging due to the similarity in signal characteristics between the respiration noise and EDA response to distress. The authors propose an adaptive denoising method that references photoplethysmogram (PPG) to detect and remove respiration noise in EDA. Quality of denoising and quality improvement in stress measurement were measured for validation. The results showed that the proposed method brought better quality of respiration noise removal than previous methods, and therefore improved stress measurement quality. The finding can contribute to improve quality of EDA from the field, which is essential to accurately understand people's stressful interaction with built environment.",
author = "Gaang Lee and Byungjoo Choi and Houtan Jebelli and Ahn, {Changbum Ryan} and Lee, {Sang Hyun}",
note = "Funding Information: This study was supported by the Exercise and Sport Science Initiative (ESSI-2018-4), the Urban Collaboratory in the University of Michigan, and the National Science Foundation – United States (# 1800310). Publisher Copyright: {\textcopyright} 2019 American Society of Civil Engineers.; ASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019 ; Conference date: 17-06-2019 Through 19-06-2019",
year = "2019",
language = "English (US)",
series = "Computing in Civil Engineering 2019: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "17--25",
editor = "Cho, {Yong K.} and Fernanda Leite and Amir Behzadan and Chao Wang",
booktitle = "Computing in Civil Engineering 2019",
address = "United States",
}