Acknowledgement
이 연구는 2022년도 한국연구재단 연구비 지원에 의한 결과의 일부임. 과제번호:2022R1A2C3011796
References
- Al-Nafjan, A., Hosny, M., Al-Ohali, Y., & Al-Wabil, A. (2017). Review and classification of emotion recognition based on EEG brain-computer interface system research: A systematic review. Applied Sciences, 7(12), 1239.
- Ari, B., Siddique, K., Alcin, O. F., Aslan, M., Sengur, A., & Mehmood, R. M. (2022). Wavelet ELM-AE Based Data Augmentation and Deep Learning for Efficient Emotion Re cognition Using EEG Recordings. IEEE Access, 10, 72171-72181. https://doi.org/10.1109/ACCESS.2022.3181887
- Arias Sarah, P., Hall, L., Saitovitch, A., Aucouturier, J. J., Zilbovicius, M., & Johansson, P. (2023). Pupil dilation reflects the dynamic integration of audiovisual emotional speech. Scientific Reports, 13(1), 5507.
- Bogdanova, O. V., Bogdanov, V. B., Miller, L. E., & Hadj-Bouziane, F. (2022). Simulated proximity enhances perceptual and physiological responses to emotional facial expressions. Scientific Reports, 12(1), Article 1.
- Campbell, E., Phinyomark, A., & Scheme, E. (2019). Feature extraction and selection for pain recognition using peripheral physiological signals. Frontiers in Neuroscience, 13, 437.
- Cesar Cavalcanti Roza, V., & Adrian Postolache, O. (2019). Multimodal approach for emotion recognition based on simulated flight experiments. Sensors, 19(24), 5516.
- Chen, W. (2018, February 10-11). Architectural style analysis method based on intelligent computing technology[Paper presentation]. 2018 10th International Conference on Measuring Technology and Mechatronics Automation(ICMTMA), Los Alamitos, CA, United States.
- Cho, M. E., & Kim, M. J. (2017). Measurement of user emotion and experience in interaction with space. Journal of Asian Architecture and Building Engineering, 16(1), 99-106.
- Ciampelli, S., Voppel, A. E., de Boer, J. N., Koops, S., & Sommer, I. E. C. (2023). Combining automatic speech recognition with semantic natural language processing in schizophrenia. Psychiatry Research, 325, 115252. https://doi.org/10.1016/j.psychres.2023.115252
- Czepiel, A., Fink, L. K., Seibert, C., Scharinger, M., & Kotz, S. A. (2023). Aesthetic and physiological effects of naturalistic multimodal music listening. Cognition, 239, 105537.
- Deng, M., Wang, X., & Menassa, C. C. (2021). Measurement and prediction of work engagement under different indoor lighting conditions using physiological sensing. Building and Environment, 203, 108098.
- Fernandez Rojas, R., Hirachan, N., Brown, N., Waddington, G., Murtagh, L., Seymour, B., & Goecke, R. (2023). Multimodal physiological sensing for the assessment of acute pain. Frontiers in Pain Research, 4, 1150264.
- Gurel, N. Z., Huang, M., Wittbrodt, M. T., Jung, H., Ladd, S. L., Shandhi, M. M. H., Ko, Y. A., Shallenberger, L., Nye, J. A., & Pearce, B. (2020). Quantifying acute physiological biomarkers of transcutaneous cervical vagal nerve stimulation in the context of psychological stress. Brain Stimulation, 13(1), 47-59.
- Hanjong, J. (2023, October 26). 2nd Sensing Architecture & Space[Oral presentation]. Autumn Annual Conference of ALK. Jeongseon-gun, Gangwon-do, Republic of Korea. https://conf.aik.or.kr/2023f/pages/committee.vm#a2
- Hsiao, S. J., & Sung, W. T. (2021). Using mobile technology to construct a network medical health care system. Intelligent Automation & Soft Computing, 31(2), 729-748.
- Hu, X., Li, F., & Liu, R. (2022). Detecting music-induced emotion based on acoustic analysis and physiological sensing: a multimodal approach. Applied Sciences, 12(18), Article 18.
- Hofling, L., Oesterle, J., Berens, P., & Zeck, G. (2020). Probing and predicting ganglion cell responses to smooth electrical stimulation in healthy and blind mouse retina. Scientific Reports, 10(1), 5248. https://doi.org/10.1038/s41598-020-61899-y
- Johnson, T., Kanjo, E., & Woodward, K. (2023). DigitalExposome: Quantifying impact of urban environment on wellbeing using sensor fusion and deep learning. Computational Urban Science, 3(1), 14.
- Kanjo, E., Younis, E. M., & Ang, C. S. (2019). Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection. Information Fusion, 49, 46-56.
- Keller, M., Pelz, H., Perlitz, V., Zweerings, J., Erik Rocher, E., Baqapuri, H. I., & Mathiak, K. (2020). Neural correlates of fluctuations in the intermediate band for heart rate and respiration are related to interoceptive perception. Psychophysiology, 57(9), e13594.
- Kim, J., Yadav, M., Chaspari, T., & Ahn, C. R. (2020). Saliency detection analysis of collective physiological responses of pedestrians to evaluate neighborhood built environments. Advanced Engineering Informatics, 43, 101035.
- Kim, M., Cheon, S., & Kang, Y. (2019). Use of electroencephalography (EEG) for the analysis of emotional perception and fear to nightscapes. Sustainability, 11(1), 233.
- Kloda, L. A., Boruff, J. T., & Cavalcante, A. S. (2020). A comparison of patient, intervention, comparison, outcome (PICO) to a new, alternative clinical question framework for search skills, search results, and self-efficacy: a randomized controlled trial. Journal of the Medical Library Association: JMLA, 108(2), 185.
- Kruger, E. (2022). Seasonal Effects of Daylight Conditions on Occupant Perception and Skin Temperature. Frontiers in Sustainable Cities, 4. https://doi.org/10.3389/frsc.2022.782712
- Kurosaka, C., Maruyama, T., Yamada, S., Hachiya, Y., Ueta, Y., & Higashi, T. (2022). Estimating core body temperature using electrocardiogram signals. Plos One, 17(6), e0270626.
- Lea, R., Davis, S. K., Mahoney, B., & Qualter, P. (2023). Do emotionally intelligent adolescents flourish or flounder under pressure? Linking emotional intelligence to stress re gulation mechanisms. Personality and Individual Differences, 201, 111943. https://doi.org/10.1016/j.paid.2022.111943
- Mansi, S. A., Pigliautile, I., Arnesano, M., & Pisello, A. L. (2022). A novel methodology for human thermal comfort decoding via physiological signals measurement and analysis. Building and Environment, 222, 109385.
- Nixon, P., Dobson, S., Terzis, S., & Wang, F. (2002, October 30-31). Architectural implications for context adaptive smart spaces[Paper presentation]. Proceedings 3rd IEEE International Workshop on System-on-Chip for Real-Time Applications, Liverpool, United Kingdom.
- Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ..., Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ, 372, n71.
- Pang, Y., Xu, X., Chen, S., Fang, Y., Shi, X., Deng, Y., Wang, Z. L., & Cao, C. (2022). Skin-inspired textile-based tactile sensors enable multifunctional sensing of wearables and soft robots. Nano Energy, 96, 107137. https://doi.org/10.1016/j.nanoen.2022.107137
- Qu, Z., Chen, J., Li, B., Tan, J., Zhang, D., & Zhang, Y. (2020). Measurement of high-school students' trait math anxiety using neurophysiological recordings during math exam. IEEE Access, 8, 57460-57471.
- Santhosh, J., Dzsotjan, D., & Ishimaru, S. (2023). Multimodal assessment of interest levels in reading: Integrating eye-tracking and physiological sensing. IEEE Access, 11, 93994-94008
- Sato, W., Murata, K., Uraoka, Y., Shibata, K., Yoshikawa, S., & Furuta, M. (2021). Emotional valence sensing using a wearable facial EMG device. Scientific Reports, 11(1), 5757.
- Sel, K., Osman, D., Huerta, N., Edgar, A., Pettigrew, R. I., & Jafari, R. (2023). Continuous cuffless blood pressure monitoring with a wearable ring bioimpedance device. Npj Digital Medicine, 6(1), 1-11.
- Smith, V., Devane, D., Begley, C. M., & Clarke, M. (2011). Methodology in conducting a systematic review of systematic reviews of healthcare interventions. BMC Medical Research Methodology, 11(1), 15.
- Song, C., Droitcour, A. D., Islam, S. M. M., Whitworth, A., Lubecke, V. M., & Boric-Lubecke, O. (2023). Unobtrusive occupancy and vital signs sensing for human building interactive systems. Scientific Reports, 13(1), 954. https://doi.org/10.1038/s41598-023-27425-6
- Sonmez, N. O. (2018). A review of the use of examples for automating architectural design tasks. Computer-Aided Design, 96, 13-30.
- Sripian, P., Anuardi, M. N. A. M., Ito, T., Tobe, Y., & Sugaya, M. (2021). Emotion-sensitive voice-casting care robot in rehabilitation using real-time sensing and analysis of biometric information. Journal of Ambient Intelligence and Smart Environments, 13(6), 413-431.
- Torku, A., Chan, A. P. C., Yung, E. H. K., & Seo, J. (2022). Detecting stressful older adults-environment interactions to improve neighbourhood mobility: A multimodal physiological sensing, machine learning, and risk hotspot analysis-based approach. Building and Environment, 224, 109533.
- Tyagi, S., & Szenasi, S. (2023). Semantic speech analysis using machine learning and deep learning techniques: A comprehensive review. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-17769-6
- Yang, D., Gao, B., Woo, W. L., Wen, H., Zhao, Y., & Gao, Z. (2023). Wearable Structured Mental-Sensing-Graph Measurement. IEEE Transactions on Instrumentation and Measurement, 72, 1-12. https://doi.org/10.1109/TIM.2022.3232163
- Zuccala, V. C., Favilla, R., & Coppini, G. (2021). Recognition of Stress Activation by Unobtrusive Multi Sensing Setup. Applied Sciences, 11(14), 6381.
- Zou, Z., & Ergan, S. (2021). Evaluating the effectiveness of biometric sensors and their signal features for classifying human experience in virtual environments. Advanced Engineering Informatics, 49, 101358. https://doi.org/10.1016/j.aei.2021.101358