EEG-Based Circumplex Model of Affect for Identifying Interindividual Differences in Thermal Comfort
Publication: Journal of Management in Engineering
Volume 38, Issue 4
Abstract
According to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) guidelines, people spend about 80%–90% of their time indoors. One of the most important factors that directly affect occupant comfort is the thermal environment. In light of this, this study aimed to evaluate the viability of the proposed electroencephalography (EEG)–based circumplex model of affect for identifying interindividual differences in occupants’ emotional states in a variety of thermal environments. A total of 30 participants were involved in the predicted mean vote (PMV)–based experimental scenarios, in which an EEG-based physiological data set was gathered in real time. First, a questionnaire survey on individual perceptions of thermal comfort (i.e., thermal sensation and satisfaction) was evaluated. Second, a -means clustering method was used to build the EEG-based circumplex model of affect for thermal environment, in which representative affective states in each quadrant were interpreted: (1) Quadrant 1, Happy, (2) Quadrant 2, Nervous, (3) Quadrant 3, Bored, and (4) Quadrant 4, Relaxed. Third, the results of a questionnaire survey (a subjective assessment) were interpreted similarly to those of the EEG-based circumplex model of affect for thermal environment (an objective assessment) proposed in this study. This study breaks new ground in the use of a biometric research technique in the domain of thermal environmental management in engineering. In terms of practical contribution, it is expected that applying the proposed model to forecast thermal sensation and satisfaction will aid in providing occupant-tailored automated building services that are responsive to their emotional preferences in a variety of thermal environments.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) Grant No. NRF-2020R1C1C1004147 funded by the Korean government [Ministry of Science, ICT & Future Planning (MSIP)].
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Journal of Management in Engineering
Volume 38 • Issue 4 • July 2022
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© 2022 American Society of Civil Engineers.
History
Received: Dec 8, 2021
Accepted: Mar 8, 2022
Published online: May 3, 2022
Published in print: Jul 1, 2022
Discussion open until: Oct 3, 2022
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