Measuring A Brain Comfort in Neuroarchitectural Research: A Structured Theoretical Study

Rizka Arinta; Vania Angeline Bachtiar; Linda Anastasia

doi:10.24002/jarina.v5i1.11375

Authors

Rizka Arinta Universitas 17 Agustus 1945 Semarang https://orcid.org/0000-0001-9933-3558
Vania Angeline Bachtiar Faculty of Medicine, Soegijapranata Catholic University, Semarang, Indonesia
Linda Anastasia Faculty of Medicine, Soegijapranata Catholic University, Semarang, Indonesia

DOI:

https://doi.org/10.24002/jarina.v5i1.11375

Keywords:

Brain Comfort, Neuroarchitecture Research, Theoretical Study Neurologist Parameter Spatial Design, Theoretical Study, Neurologist Parameter, Spatial Design

Abstract

Comfort is a central objective in architectural design, yet it varies across individuals. This study proposes an evidence-based framework for assessing comfort through a neuroarchitectural approach by analysing neurological parameters. A meta-analysis of Scopus-indexed literature identified 111 relevant keywords from an initial set of 1,298, derived from 2,561 unique keywords in peer-reviewed studies published over the past decade that employed neurological indicators in neuroarchitecture. The findings indicate that comfort is not solely subjective but can be examined through measurable biological and neurological markers. The literature is organised into three main parameters: environmental simulation and spatial comfort, neurological instrumentation and brain signal processing, and emotional perception and sensory experience. Thematic content analysis and bibliometric mapping were conducted using OpenRefine, VOSviewer, and Biblioshiny. The synthesis reveals clear correlations between neurological responses and architectural elements such as natural lighting, spatial configuration, material texture, and environmental control. These parameters reliably capture the neurophysiological mechanisms underlying comfort in built environments, with perceptual and emotional responses identified as particularly critical. Overall, meta-analysis establishes comfort as an objectively quantifiable phenomenon and provides a foundation for adaptive and inclusive architectural design that supports mental health, cognitive performance, and well-being. Future research directions include experimental studies integrating virtual reality and real-time biometric monitoring to further explore brain–environment interactions.

References

[1] A. Krugliak and A. Clarke, “Towards real-world neuroscience using mobile EEG and augmented reality,” Sci. Rep., vol. 12, no. 1, 2022, doi: 10.1038/s41598-022-06296-3.

[2] B. F. Reitsamer, T. D. Heinz, A. Kaschig, and N. E. Stokburger-Sauer, “The effects of website quality perception on users’ responses - A multidisciplinary approach,” in Amer. Conf. Info. Syst., Association for Information Systems, 2014. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905988815&partnerID=40&md5=ee53808a6026d5675e8e10011acc71f7

[3] R. Palaniappan, S. Mouli, H. Bowman, and I. McLoughlin, “Investigating the Cognitive Response of Brake Lights in Initiating Braking Action Using EEG,” IEEE Trans. Intell. Transp. Syst., vol. 23, no. 8, pp. 13878–13883, 2022, doi: 10.1109/TITS.2021.3091291.

[4] D. Fehlings et al., “Pharmacological and neurosurgical management of cerebral palsy and dystonia: Clinical practice guideline update,” Dev. Med. Child Neurol., vol. 66, no. 9, pp. 1133–1147, 2024, doi: 10.1111/dmcn.15921.

[5] T. H. Choi, S. Y. Ji, Y. Y. Hong, and H. J. Jun, “WEB-BASED 3D HEATMAP VISUALIZATION OF SPATIAL COGNITION USING EEG AND EYE TRACKING DATA,” in Proc. Int. Conf. Comput.-Aided Architect. Des. Res. Asia, Gardner N., Herr C.M., Wang L., Toshiki H., and Khan S.A., Eds., The Association for Computer-Aided Architectural Design Research in Asia, 2024, pp. 539–548. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196758059&partnerID=40&md5=3dcd74c8c495c6d1acbd5590a358ba13

[6] İ. Erkan, “Cognitive response and how it is affected by changes in temperature,” Build Res Inf, vol. 49, no. 4, pp. 399–416, 2021, doi: 10.1080/09613218.2020.1800439.

[7] H. W. Brink, W. P. Krijnen, M. G. L. C. Loomans, M. P. Mobach, and H. S. M. Kort, “Positive effects of indoor environmental conditions on students and their performance in higher education classrooms: A between-groups experiment,” Sci. Total Environ., vol. 869, 2023, doi: 10.1016/j.scitotenv.2023.161813.

[8] H. W. Brink, M. G. L. C. Loomans, M. P. Mobach, and H. S. M. Kort, “A systematic approach to quantify the influence of indoor environmental parameters on students’ perceptions, responses, and short-term academic performance,” Indoor Air, vol. 32, no. 10, 2022, doi: 10.1111/ina.13116.

[9] L. Mengqi, Y. Jie, and X. Leiqing, “Protective and Restorative Effects of Biophilic Design in High School Indoor Environments on Stress and Cognitive Function,” Indoor Air, vol. 2025, no. 1, 2025, doi: 10.1155/ina/8696488.

[10] R. T. Arinta, P. Satwiko, R. R. Widjaja, and S. Kusrohmaniah, “Brain spatial reconciliation through multisensory integration in the impact of pandemic fatigue on workplace,” Front. Hum. Neurosci., vol. 18, p. 1419889, Dec. 2024, doi: 10.3389/fnhum.2024.1419889.

[11] C. Carmichael, R. Callingham, and H. M. G. Watt, “Classroom motivational environment influences on emotional and cognitive dimensions of student interest in mathematics,” ZDM Math. Edu., vol. 49, no. 3, pp. 449–460, 2017, doi: 10.1007/s11858-016-0831-7.

[12] K. Hou, X. Guan, H. Wang, S. Hu, M. Lu, and N. Liu, “Influence of functional boundary for corridor spaces in elderly facilities in China,” Build Res Inf, vol. 52, no. 6, pp. 658–679, 2024, doi: 10.1080/09613218.2023.2248297.

[13] B. Du, H. Schwartz-Narbonne, M. Tandoc, E. M. Heffernan, M. L. Mack, and J. A. Siegel, “The impact of emissions from an essential oil diffuser on cognitive performance,” Indoor Air, vol. 32, no. 1, 2022, doi: 10.1111/ina.12919.

[14] M. Boz, H. Demirkan, and B. Ürgen, “Visual Perception of the Built Environment in Virtual Reality: Insights from Generation Z,” Frontiers in Virtual Reality, vol. 5, p. Article 234, 2024, doi: 10.3389/frvir.2024.00234.

[15] Y. Noh, S. Kim, and Y. Yoon, “Evaluation on Diversity of Drivers’ Cognitive Stress Response using EEG and ECG Signals during Real-Traffic Experiment with an Electric Vehicle ∗,” in IEEE Intell. Transp. Syst. Conf., ITSC, Institute of Electrical and Electronics Engineers Inc., 2019, pp. 3987–3992. doi: 10.1109/ITSC.2019.8916844.

[16] L. Bergefurt, R. Appel-Meulenbroek, and T. Arentze, “How salutogenic workplace characteristics influence psychological and cognitive responses in a virtual environment,” Ergonomics, vol. 67, no. 3, pp. 339–355, 2024, doi: 10.1080/00140139.2023.2223372.

[17] M. R. Abdul Rashid et al., “COVID-19 Pandemic Fatigue and Its Sociodemographic, Mental Health Status, and Perceived Causes: A Cross-Sectional Study Nearing the Transition to an Endemic Phase in Malaysia,” International Journal of Environmental Research and Public Health, 2023, doi: 10.3390/ijerph20054476.

[18] S. Alam, M. Sharma, and U. R. Salve, “Assessment of Thermal Comfort in a Hot and Humid Indoor Built Environment of a Kitchen at a University Canteen,” Work, 2022, doi: 10.3233/wor-205174.

[19] H. Sakhaei, N. Gu, and M. A. Looha, “Assessing the association between subjective evaluation of space qualities and physiological responses through cinematic environments’ emotion-eliciting stimuli,” Front. Psychol., vol. 13, 2023, doi: 10.3389/fpsyg.2022.1012758.

[20] R. Mager et al., “Neurophysiological age differences during task-performance in a stereoscopic virtual environment,” Appl. Psychophysiol. Biofeedback, vol. 30, no. 3, pp. 233–238, 2005, doi: 10.1007/s10484-005-6380-4.

[21] A. Brunzini, F. Grandi, M. Peruzzini, and M. Pellicciari, “An integrated methodology for the assessment of stress and mental workload applied on virtual training,” Int J Computer Integr Manuf, vol. 37, no. 9, pp. 1088–1106, 2024, doi: 10.1080/0951192X.2023.2189311.

[22] S. Abbas, “Neuroarchitecture: How the Perception of Our Surroundings Impacts the Brain,” Biology, 2024, doi: 10.3390/biology13040220.

[23] A. E. Guyer et al., “Temperament and Parenting Styles in Early Childhood Differentially Influence Neural Response to Peer Evaluation in Adolescence,” J. Abnorm. Child Psychol., vol. 43, no. 5, pp. 863–874, 2015, doi: 10.1007/s10802-015-9973-2.

[24] F. Bitsch, P. Berger, A. Nagels, I. Falkenberg, and B. Straube, “Characterizing the theory of mind network in schizophrenia reveals a sparser network structure,” Schizophr. Res., vol. 228, pp. 581–589, 2021, doi: 10.1016/j.schres.2020.11.026.

[25] J. H. Abraini, E. Martinez, C. Lemaire, T. Bisson, J.-L. J. De Mendoza, and P. Therme, “Anxiety, sensorimotor and cognitive performance during a hydrogen-oxygen dive and long-term confinement in a pressure chamber,” J. Environ. Psychol., vol. 17, no. 2, pp. 157–164, 1997, doi: 10.1006/jevp.1997.0050.

[26] H. J. Baek, H. J. Lee, Y. G. Lim, and K. S. Park, “Comparison of pre-amplifier topologies for use in brain-computer interface with capacitively-coupled EEG electrodes,” Biomed. Eng. Lett., vol. 3, no. 3, pp. 158–169, 2013, doi: 10.1007/s13534-013-0099-6.

[27] S. Abbas, “Neuroarchitecture: How the Perception of Our Surroundings Impacts the Brain,” Biology, 2024, doi: 10.3390/biology13040220.

[28] S. Sepehri, M. Aliabadi, R. Golmohammadi, and M. Babamiri, “Human cognitive functions and psycho-physiological responses under low thermal conditions in a simulated office environment,” Work, vol. 69, no. 1, pp. 197–207, 2021, doi: 10.3233/WOR-213469.

[29] Y. De, “Reprogramming Urban Block by Machine Creativity: How to use neural networks as generative tools to design space,” in Proc. Int. Conf. Educ. Res. Comput. Aided. Archit. Des. Eur., Werner L.C. and Koering D., Eds., Education and research in Computer Aided Architectural Design in Europe, 2020, pp. 249–258. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122967939&partnerID=40&md5=e41f789e7bb50ce256d6c46427e5022e

[30] M. Baez, S. Camacho, B. Reyes, A. Morante, and M. Fuentes, “Relationship Between Neuroarchitecture and Stress Reduction Compared to Conventional Architecture in Healthcare Personnel,” in IFMBE Proc., Flores Cuautle J.d., Benítez-Mata B., Salido-Ruiz R.A., Vélez-Pérez H.A., Alonso-Silverio G.A., Dorantes-Méndez G., Mejía-Rodríguez A.R., Zúñiga-Aguilar E., and Hierro-Gutiérrez E.D., Eds., Springer Science and Business Media Deutschland GmbH, 2024, pp. 232–240. doi: 10.1007/978-3-031-46936-7_25.

[31] A. K. Singh et al., “Visual Appearance Modulates Prediction Error in Virtual Reality,” IEEE Access, vol. 6, pp. 24617–24624, 2018, doi: 10.1109/ACCESS.2018.2832089.

[32] J. Alba-Martínez, M. Alcañiz, J. Martínez-Monzó, L. M. Cunha, and P. García-Segovia, “Beyond Reality: Exploring the effect of different virtual reality environments on visual assessment of cakes,” Food Res. Int., vol. 179, 2024, doi: 10.1016/j.foodres.2024.114019.

[33] M. Mestiri, M. Khadhar, A. Huftier, and A. Fergombe, “Fostering Social Interaction Variability in the Metaverse: A Case Study of the Museum of L’Avesnois in Fourmies,” Heritage., vol. 8, no. 5, 2025, doi: 10.3390/heritage8050171.

[34] J. Y. Jeon and H. I. Jo, “Effects of audio-visual interactions on soundscape and landscape perception and their influence on satisfaction with the urban environment,” Build. Environ., vol. 169, 2020, doi: 10.1016/j.buildenv.2019.106544.

[35] K. R. Trivedi and R. A. Thakker, “Brainwave enabled multifunctional, communication, controlling and speech signal generating system,” in Int. Conf. Electr., Electron., Optim. Techniques, ICEEOT, Institute of Electrical and Electronics Engineers Inc., 2016, pp. 4889–4893. doi: 10.1109/ICEEOT.2016.7755650.

[36] Y. Zhang, L. Guo, X. You, B. Miao, and Y. Li, “Cognitive Response of Underground Car Driver Observed by Brain EEG Signals,” Sensors, vol. 24, no. 23, 2024, doi: 10.3390/s24237763.

[37] P.-C. Liao, X. Sun, and D. Zhang, “A multimodal study to measure the cognitive demands of hazard recognition in construction workplaces,” Saf. Sci., vol. 133, 2021, doi: 10.1016/j.ssci.2020.105010.

[38] A. Ricci et al., “Understanding the Unexplored: A Review on the Gap in Human Factors Characterization for Industry 5.0,” Appl. Sci., vol. 15, no. 4, 2025, doi: 10.3390/app15041822.

[39] N. C. Lewis, Design and order: Perceptual experience of built form - Principles in the planning and making of place. in Design and Order: Perceptual Experience of Built Form - Principles in the Planning and Making of Place. Wiley Blackwell, 2020, p. 656. doi: 10.1002/9781119539568.

[40] N. Vila-López, I. Kuster-Boluda, and A. Alacreu-Crespo, “Designing a low-fat food packaging: Comparing consumers’ responses in virtual and physical shopping environments,” Foods, vol. 10, no. 2, 2021, doi: 10.3390/foods10020211.

[41] V. Ramanathan and T. Kumar, “Cognitive and Affective Responses to Varied Coloured Light Environments,” in Lect. Notes Networks Syst., Alareeni B. and Hamdan A., Eds., Springer Science and Business Media Deutschland GmbH, 2024, pp. 169–178. doi: 10.1007/978-3-031-67437-2_16.

[42] L. Franzen, A. Cabugao, B. Grohmann, K. Elalouf, and A. P. Johnson, “Individual pupil size changes as a robust indicator of cognitive familiarity differences,” PLoS ONE, vol. 17, no. 1 January, 2022, doi: 10.1371/journal.pone.0262753.

[43] A. Olszewska-Guizzo, A. Sia, A. Fogel, and R. Ho, “Features of urban green spaces associated with positive emotions, mindfulness and relaxation,” Sci. Rep., vol. 12, no. 1, 2022, doi: 10.1038/s41598-022-24637-0.

[44] S. Anwer, H. Li, M. F. Antwi‐Afari, W. Umer, and A. Y. L. Wong, “Cardiorespiratory and Thermoregulatory Parameters Are Good Surrogates for Measuring Physical Fatigue During a Simulated Construction Task,” International Journal of Environmental Research and Public Health, 2020, doi: 10.3390/ijerph17155418.

[45] J. P. Ferreira, “Development of a Low-Cost Apparatus to Assess Auditory Cognitive Responses in Microgravity Flights,” in Proc. Int. Astronaut. Congr., IAC, International Astronautical Federation, IAF, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167615344&partnerID=40&md5=282d4d1810c7629541a99eb87d6f5608

[46] E. Redlinger and C. Shao, “Comparing brain activity in virtual and non-virtual environments: A VR & EEG study,” in Measurement. Sens., Elsevier Ltd, 2021. doi: 10.1016/j.measen.2021.100062.

[47] M. K. Rowell, R. M. Santymire, and T. L. Rymer, “Corticosterone metabolite concentration is not related to problem solving in the fawn‐footed mosaic‐tailed rat melomys cervinipes,” Animals, vol. 12, no. 1, 2022, doi: 10.3390/ani12010082.

[48] A. Coburn, O. Vartanian, and A. Chatterjee, “Buildings, beauty, and the brain: A neuroscience of architectural experience,” J. Cogn. Neurosci., vol. 29, no. 9, pp. 1521–1531, 2017, doi: 10.1162/jocn_a_01146.

[49] K. Bail and L. Grealish, “‘Failure to Maintain’: A theoretical proposition for a new quality indicator of nurse care rationing for complex older people in hospital,” Int. J. Nurs. Stud., vol. 63, pp. 146–161, 2016, doi: 10.1016/j.ijnurstu.2016.08.001.

[50] O. Vartanian, “Impact of Ceiling Height on Brain Activation,” Journal of Environmental Psychology, 2013.