Reference Signal-Based Method to Remove Respiration Noise in Electrodermal Activity (EDA) Collected from the Field

Gaang Lee, Byungjoo Choi, Houtan Jebelli, Changbum Ryan Ahn, Sang Hyun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2019
Subtitle of host publicationData, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019
EditorsYong K. Cho, Fernanda Leite, Amir Behzadan, Chao Wang
PublisherAmerican Society of Civil Engineers (ASCE)
Pages17-25
Number of pages9
ISBN (Electronic)9780784482438
StatePublished - 2019
EventASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019 - Atlanta, United States
Duration: Jun 17 2019Jun 19 2019

Publication series

NameComputing in Civil Engineering 2019: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019

Conference

ConferenceASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019
CountryUnited States
CityAtlanta
Period6/17/196/19/19

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Civil and Structural Engineering

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