Technical Papers
Apr 27, 2024

Measuring Habituation to Auditory Warnings Using Behavioral and Physiological Data

Publication: Journal of Construction Engineering and Management
Volume 150, Issue 7

Abstract

Habituation to auditory warnings is a phenomenon where an individual exposed to frequent auditory warnings responds slowly to them. Repetitive auditory warnings are triggered to prevent struck-by accidents in blind spots on construction equipment; however, these can cause habituation that may increase the likelihood of accidents. The current body of knowledge lacks any evidence quantitatively showing such phenomenon. This study aims at quantifying habituation to auditory warnings using behavioral and physiological data. In the construction equipment operation simulation developed for this study, participants pressed the brake pedal when they heard auditory warnings. Behavioral data included the reaction times (auditory warning trigger to the pedal pressing instant). In addition to the behavioral data, physiological features related to alertness from electroencephalography and electrodermal activity sensors were used to measure habituation to auditory warnings experienced by the participants. It was found that reaction time slowed down as the warnings repeated. Among the physiological features, the skin conductance level best measured habituation to auditory warnings. This study sheds light on the issue of habituation to auditory warnings in construction equipment and contributes to the reduction of the number of struck-by accidents in the construction industry.

Get full access to this article

View all available purchase options and get full access to this article.

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 a National Research Korea grant funded by the Korean Government (Ministry of Education) (NRF-2021R1F1A1050519).

References

Alzahrani, S., and C. W. Anderson. 2017. “EEG P300 wave detection using Emotiv EPOC+: Effects of matrix size, flash duration, and colors.” PeerJ. Preprints 5 (Dec): e3474v1. https://doi.org/10.7287/peerj.preprints.3474v1.
Baddeley, A. 1992. “Working memory.” Science 255 (5044): 556–559. https://doi.org/10.1126/science.1736359.
Belz, S. M., G. S. Robinson, and J. G. Casali. 1999. “A new class of auditory warning signals for complex systems: Auditory icons.” Hum. Factors 41 (4): 608–618. https://doi.org/10.1518/001872099779656734.
Blackmon, R., and A. Gramopadhye. 1995. “Improving construction safety by providing positive feedback on backup alarms.” J. Constr. Eng. Manage. 121 (2): 166–171. https://doi.org/10.1061/(ASCE)0733-9364(1995)121:2(166).
BLS. 2020. “Injuries, illnesses, and fatalities.” Accessed October 1, 2022. http://www.bls.gov/iif/oshcfoi1.htm.
Boucsein, W. 2012. Electrodermal activity. New York: Springer Science & Business Media.
Canisius, S., and T. Penzel. 2007. “Vigilance monitoring–review and practical aspects.” Biomed. Eng. 52 (1): 77–82. https://doi.org/10.1515/BMT.2007.015.
Cash, J. J. 2009. “Alert fatigue.” Am. J. Health-Syst. Pharm. 66 (23): 2098–2101. https://doi.org/10.2146/ajhp090181.
Chae, J., S. Hwang, W. Seo, and Y. Kang. 2021. “Relationship between rework of engineering drawing tasks and stress level measured from physiological signals.” Autom. Constr. 124 (Apr): 103560. https://doi.org/10.1016/j.autcon.2021.103560.
Chang, Y., and A. Mosleh. 2007. “Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents: Part 1: Overview of the IDAC Model.” Reliab. Eng. Syst. Saf. 92 (8): 997–1013. https://doi.org/10.1016/j.ress.2006.05.014.
Chen, J., R. Q. Wang, Z. Lin, and X. Guo. 2018. “Measuring the cognitive loads of construction safety sign designs during selective and sustained attention.” Saf. Sci. 105 (Jun): 9–21. https://doi.org/10.1016/j.ssci.2018.01.020.
Choi, B., H. Jebelli, and S. Lee. 2019. “Feasibility analysis of electrodermal activity (EDA) acquired from wearable sensors to assess construction workers’ perceived risk.” Saf. Sci. 115 (Jun): 110–120. https://doi.org/10.1016/j.ssci.2019.01.022.
Cohen, J. 2013. Statistical power analysis for the behavioral sciences. New York: Academic Press.
Conde, T., Ó. F. Gonçalves, and A. P. Pinheiro. 2015. “Paying attention to my voice or yours: An ERP study with words.” Biol. Psychol. 111 (Oct): 40–52. https://doi.org/10.1016/j.biopsycho.2015.07.014.
Delorme, A., and S. Makeig. 2004. “EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.” J. Neurosci. Methods 134 (1): 9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009.
Dinges, D. F., and J. W. Powell. 1985. “Microcomputer analyses of performance on a portable, simple visual RT task during sustained operations.” Behav. Res. Methods Instrum. Comput. 17 (6): 652–655. https://doi.org/10.3758/BF03200977.
Edworthy, J. 2013. “Medical audible alarms: A review.” J. Am. Med. Inf. Assoc. 20 (3): 584–589. https://doi.org/10.1136/amiajnl-2012-001061.
Fang, D., C. Zhao, and M. Zhang. 2016. “A cognitive model of construction workers’ unsafe behaviors.” J. Constr. Eng. Manage. 142 (9): 04016039. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001118.
Faul, F., E. Erdfelder, A.-G. Lang, and A. Buchner. 2007. “G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences.” Behav. Res. Methods 39 (2): 175–191. https://doi.org/10.3758/BF03193146.
Fernandes, A., R. Helawar, R. Lokesh, T. Tari, and A. V. Shahapurkar. 2014. “Determination of stress using blood pressure and galvanic skin response.” In Proc., 2014 Int. Conf. on Communication and Network Technologies, 165–168. New York: IEEE. https://doi.org/10.1109/CNT.2014.7062747.
Ferreira, C., S. S. Kumar, and D. M. Abraham. 2017. “Using backing cameras to prevent work zone accidents involving mobile equipment.” Pract. Period. Struct. Des. Constr. 22 (4): 04017021. https://doi.org/10.1061/(ASCE)SC.1943-5576.0000343.
Folmer, R. L., and C. D. Yingling. 1997. “Auditory P3 responses to name stimuli.” Brain Lang. 56 (2): 306–311. https://doi.org/10.1006/brln.1997.1828.
Ge, H., Y. Bo, H. Sun, M. Zheng, and Y. Lu. 2022. “A review of research on driving distraction based on bibliometrics and co-occurrence: Focus on driving distraction recognition methods.” J. Saf. Res. 82 (Sep): 261–274. https://doi.org/10.1016/j.jsr.2022.06.002.
Gibbings, A., L. Ray, S. Gagnon, C. Collin, R. Robillard, and S. Fogel. 2022. “The EEG correlates and dangerous behavioral consequences of drowsy driving after a single night of mild sleep deprivation.” Physiol. Behav. 252 (Aug): 113822. https://doi.org/10.1016/j.physbeh.2022.113822.
Golovina, O., J. Teizer, and N. Pradhananga. 2016. “Heat map generation for predictive safety planning: Preventing struck-by and near miss interactions between workers-on-foot and construction equipment.” Autom. Constr. 71 (Nov): 99–115. https://doi.org/10.1016/j.autcon.2016.03.008.
Greco, A., G. Valenza, A. Lanata, E. P. Scilingo, and L. Citi. 2015. “cvxEDA: A convex optimization approach to electrodermal activity processing.” IEEE Trans. Biomed. Eng. 63 (4): 797–804. https://doi.org/10.1109/TBME.2015.2474131.
Hasan, M. M., C. N. Watling, and G. S. Larue. 2022. “Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches.” J. Saf. Res. 80 (Feb): 215–225. https://doi.org/10.1016/j.jsr.2021.12.001.
Haufe, S., J.-W. Kim, I.-H. Kim, A. Sonnleitner, M. Schrauf, G. Curio, and B. Blankertz. 2014. “Electrophysiology-based detection of emergency braking intention in real-world driving.” J. Neural Eng. 11 (5): 056011. https://doi.org/10.1088/1741-2560/11/5/056011.
Hinze, J. W., and J. Teizer. 2011. “Visibility-related fatalities related to construction equipment.” Saf. Sci. 49 (5): 709–718. https://doi.org/10.1016/j.ssci.2011.01.007.
Hou, X., Y. Liu, O. Sourina, Y. R. E. Tan, L. Wang, and W. Mueller-Wittig. 2015. “EEG based stress monitoring.” In Proc., 2015 IEEE Int. Conf. on Systems, Man, and Cybernetics, 3110–3115. New York: IEEE. https://doi.org/10.1109/SMC.2015.540.
Hwang, S., H. Jebelli, B. Choi, M. Choi, and S. Lee. 2018. “Measuring workers’ emotional state during construction tasks using wearable EEG.” J. Constr. Eng. Manage. 144 (7): 04018050. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001506.
Iadarola, G., A. Poli, and S. Spinsante. 2022. “Compressed sensing of skin conductance level for IoT-based wearable sensors.” In Proc., 2022 IEEE Int. Instrumentation and Measurement Technology Conf. (I2MTC), 1–6. New York: IEEE. https://doi.org/10.1109/I2MTC48687.2022.9806516.
Işoğlu-Alkaç, Ü., K. Kedzior, S. Karamürsel, and N. Ermutlu. 2007. “Event-related potentials during auditory oddball, and combined auditory oddball–visual paradigms.” Int. J. Neurosci. 117 (4): 487–506. https://doi.org/10.1080/00207450600773509.
Jebelli, H., S. Hwang, and S. Lee. 2018a. “EEG-based workers’ stress recognition at construction sites.” Autom. Constr. 93 (Sep): 315–324. https://doi.org/10.1016/j.autcon.2018.05.027.
Jebelli, H., S. Hwang, and S. Lee. 2018b. “EEG signal-processing framework to obtain high-quality brain waves from an off-the-shelf wearable EEG device.” J. Comput. Civ. Eng. 32 (1): 04017070. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000719.
Jedon, R., A. Haans, and Y. de Kort. 2022. “Proposing a research framework for urban lighting: The alertness, arousal and anxiety triad.” Light. Res. Technol. 55 (7–8): 658–668. https://doi.org/10.1177/14771535221122139.
Jose, S., and K. Gideon Praveen. 2010. “Comparison between auditory and visual simple reaction times.” Neurosci. Med. 1 (1): 30–32. https://doi.org/10.4236/nm.2010.11004.
Jung, H., B. Choi, S. Kang, and Y. Kang. 2022. “Temporal analysis of the frequency of accidents associated with construction equipment.” Saf. Sci. 153 (Sep): 105817. https://doi.org/10.1016/j.ssci.2022.105817.
Jung, T.-P., S. Makeig, M. Stensmo, and T. J. Sejnowski. 1997. “Estimating alertness from the EEG power spectrum.” IEEE Trans. Biomed. Eng. 44 (1): 60–69. https://doi.org/10.1109/10.553713.
Kamiński, J., A. Brzezicka, M. Gola, and A. Wróbel. 2012. “Beta band oscillations engagement in human alertness process.” Int. J. Psychophysiol. 85 (1): 125–128. https://doi.org/10.1016/j.ijpsycho.2011.11.006.
Kang, Y., S. Siddiqui, S. J. Suk, S. Chi, and C. Kim. 2017. “Trends of fall accidents in the US construction industry.” J. Constr. Eng. Manage. 143 (8): 04017043. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001332.
Kim, N., B. A. Anderson, and C. R. Ahn. 2021a. “Reducing risk habituation to struck-by hazards in a road construction environment using virtual reality behavioral intervention.” J. Constr. Eng. Manage. 147 (11): 04021157. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002187.
Kim, N., J. Kim, and C. R. Ahn. 2021b. “Predicting workers’ inattentiveness to struck-by hazards by monitoring biosignals during a construction task: A virtual reality experiment.” Adv. Eng. Inf. 49 (Aug): 101359. https://doi.org/10.1016/j.aei.2021.101359.
Kim, N., N. Yan, L. Grégoire, B. A. Anderson, and C. R. Ahn. 2023. “Road construction workers’ boredom susceptibility, habituation to warning alarms, and accident proneness: Virtual reality experiment.” J. Constr. Eng. Manage. 149 (2): 04022175. https://doi.org/10.1061/JCEMD4.COENG-12818.
Kirstein, C. 2007. Sleeping and dreaming. Amsterdam, Netherland: Elsevier.
Kompier, M. E., K. C. Smolders, W. van Marken Lichtenbelt, and Y. A. de Kort. 2020. “Effects of light transitions on measures of alertness, arousal and comfort.” Physiol. Behav. 223 (Sep): 112999. https://doi.org/10.1016/j.physbeh.2020.112999.
KOSHA (Korea Occupational Safety and Health Agency). 2022. “NEWS RELEASE_Industrial accidents in 2021: Statistics.” Accessed January 5, 2024. https://oshri.kosha.or.kr/kosha/data/industrialDisasterStatistics.do?mode=view&articleNo=433710&article.offset=0&articleLimit=10.
Kryter, K. D. 2013. The effects of noise on man. Amsterdam, Netherland: Elsevier.
Lader, M., and A. Mathews. 1968. “A physiological model of phobic anxiety and desensitization.” Behav. Res. Ther. 6 (4): 411–421. https://doi.org/10.1016/0005-7967(68)90021-1.
Larue, G., A. Rakotonirainy, and T. Pettitt. 2011. “Real-time evaluation of driver’s alertness on highways.” In Urban transport XVII: Urban transport and the environment in the 21st century, 553–563. Southampton, UK: WIT Press. https://doi.org/10.2495/UT110471.
Lee, B., and H. Kim. 2022. “Measuring effects of safety-reminding interventions against risk habituation.” Saf. Sci. 154 (Oct): 105857. https://doi.org/10.1016/j.ssci.2022.105857.
Lee, G., B. Choi, H. Jebelli, C. Ryan Ahn, and S. Lee. 2020. “Noise reference signal–based denoising method for EDA collected by multimodal biosensor wearable in the field.” J. Comput. Civ. Eng. 34 (6): 04020044. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000927.
Li, X., Y. Guo, F.-L. Ge, and F.-Q. Yang. 2023. “Human reliability assessment on building construction work at height: The case of scaffolding work.” Saf. Sci. 159 (Mar): 106021. https://doi.org/10.1016/j.ssci.2022.106021.
Li, X., L. Yang, and X. Yan. 2022. “An exploratory study of drivers’ EEG response during emergent collision avoidance.” J. Saf. Res. 82 (Sep): 241–250. https://doi.org/10.1016/j.jsr.2022.05.015.
Lopez-Calderon, J., and S. J. Luck. 2014. “ERPLAB: An open-source toolbox for the analysis of event-related potentials.” Front. Hum. Neurosci. 8 (Apr): 213. https://doi.org/10.3389/fnhum.2014.00213.
Luck, S. J. 2014. An introduction to the event-related potential technique. Cambridge, MA: MIT Press.
Makeig, S., A. Bell, T.-P. Jung, and T. J. Sejnowski. 1995. “Independent component analysis of electroencephalographic data.” In Proc., Conf. on Neural Information Processing Systems (NeurlIPS). Red Hook, NY: Curran Associates.
Mampusti, E. T., J. S. Ng, J. J. I. Quinto, G. L. Teng, M. T. C. Suarez, and R. S. Trogo. 2011. “Measuring academic affective states of students via brainwave signals.” In Proc., 2011 3rd Int. Conf. on Knowledge and Systems Engineering, 226–231. New York: IEEE. https://doi.org/10.1109/KSE.2011.43.
Man, S. S., S. Alabdulkarim, A. H. S. Chan, and T. Zhang. 2021. “The acceptance of personal protective equipment among Hong Kong construction workers: An integration of technology acceptance model and theory of planned behavior with risk perception and safety climate.” J. Saf. Res. 79 (Dec): 329–340. https://doi.org/10.1016/j.jsr.2021.09.014.
Marks, E. D., and J. Teizer. 2013. “Method for testing proximity detection and alert technology for safe construction equipment operation.” Construct. Manage. Econ. 31 (6): 636–646. https://doi.org/10.1080/01446193.2013.783705.
Mir, M., F. Nasirzadeh, H. Bereznicki, P. Enticott, S. Lee, and A. Mills. 2023. “Construction noise effects on human health: Evidence from physiological measures.” Sustainable Cities Soc. 91 (Apr): 104470. https://doi.org/10.1016/j.scs.2023.104470.
Nagai, Y., H. D. Critchley, E. Featherstone, M. R. Trimble, and R. J. Dolan. 2004. “Activity in ventromedial prefrontal cortex covaries with sympathetic skin conductance level: A physiological account of a ‘default mode’ of brain function.” Neuroimage 22 (1): 243–251. https://doi.org/10.1016/j.neuroimage.2004.01.019.
Niedermeyer, E., and F. L. da Silva. 2005. Electroencephalography: Basic principles, clinical applications, and related fields. Philadelphia: Lippincott Williams & Wilkins.
NYS-LTAP. n.d. “Safety alarm fatigue.” Accessed December 9, 2022. https://cornell.app.box.com/v/EDSTailgateSafetyAlarm.
Oken, B. S., S. S. Kishiyama, and M. C. Salinsky. 1995. “Pharmacologically induced changes in arousal: Effects on behavioral and electrophysiologic measures of alertness and attention.” Electroencephalogr. Clin. Neurophysiol. 95 (5): 359–371. https://doi.org/10.1016/0013-4694(95)00124-H.
OSHA (Occupational Safety and Health Administration). 2018. Preventing runovers and backovers. Washington, DC: OSHA.
Parasuraman, R. 2000. The attentive brain. Cambridge, MA: MIT Press.
Park, S., C. Y. Park, C. Lee, S. H. Han, S. Yun, and D.-E. Lee. 2022. “Exploring inattentional blindness in failure of safety risk perception: Focusing on safety knowledge in construction industry.” Saf. Sci. 145 (Jan): 105518. https://doi.org/10.1016/j.ssci.2021.105518.
Plant, R. R., and G. Turner. 2009. “Millisecond precision psychological research in a world of commodity computers: New hardware, new problems?” Behav. Res. Methods 41 (3): 598–614. https://doi.org/10.3758/BRM.41.3.598.
Posada-Quintero, H. F., J. B. Bolkhovsky, M. Qin, and K. H. Chon. 2018. “Human performance deterioration due to prolonged wakefulness can be accurately detected using time-varying spectral analysis of electrodermal activity.” Hum. Factors 60 (7): 1035–1047. https://doi.org/10.1177/0018720818781196.
Posada-Quintero, H. F., and K. H. Chon. 2020. “Innovations in electrodermal activity data collection and signal processing: A systematic review.” Sensors 20 (2): 479. https://doi.org/10.3390/s20020479.
Pratt, S. G., D. E. Fosbroke, and S. M. Marsh. 2001. Building safer highway work zones: Measures to prevent worker injuries from vehicles and equipment. Cincinnati: National Institute for Occupational Safety and Health.
Qin, Y., and T. Bulbul. 2023. “An EEG-based mental workload evaluation for AR head-mounted display use in construction assembly tasks.” J. Constr. Eng. Manage. 149 (9): 04023088. https://doi.org/10.1061/JCEMD4.COENG-13438.
Ramachandran, V. S. 2002. Encyclopedia of the human brain: Col-mem. San Diego: Academic Press.
Rankin, C. H., T. Abrams, R. J. Barry, S. Bhatnagar, D. F. Clayton, J. Colombo, G. Coppola, M. A. Geyer, D. L. Glanzman, and S. Marsland. 2009. “Habituation revisited: An updated and revised description of the behavioral characteristics of habituation.” Neurobiol. Learn. Mem. 92 (2): 135–138. https://doi.org/10.1016/j.nlm.2008.09.012.
Rosa, C., M. Lassonde, C. Pinard, J. P. Keenan, and P. Belin. 2008. “Investigations of hemispheric specialization of self-voice recognition.” Brain Cogn. 68 (2): 204–214. https://doi.org/10.1016/j.bandc.2008.04.007.
Rossion, B., C. A. Joyce, G. W. Cottrell, and M. J. Tarr. 2003. “Early lateralization and orientation tuning for face, word, and object processing in the visual cortex.” Neuroimage 20 (3): 1609–1624. https://doi.org/10.1016/j.neuroimage.2003.07.010.
Sawilowsky, S. S. 2009. “New effect size rules of thumb.” J. Mod. Appl. Stat. Methods 8 (2): 597. https://doi.org/10.22237/jmasm/1257035100.
Sengupta, A., A. Dasgupta, A. Chaudhuri, A. George, A. Routray, and R. Guha. 2017. “A multimodal system for assessing alertness levels due to cognitive loading.” IEEE Trans. Neural Syst. Rehabil. Eng. 25 (7): 1037–1046. https://doi.org/10.1109/TNSRE.2017.2672080.
Shayesteh, S., A. Ojha, Y. Liu, and H. Jebelli. 2023. “Human-robot teaming in construction: Evaluative safety training through the integration of immersive technologies and wearable physiological sensing.” Saf. Sci. 159 (Mar): 106019. https://doi.org/10.1016/j.ssci.2022.106019.
Son, H., H. Seong, H. Choi, and C. Kim. 2019. “Real-time vision-based warning system for prevention of collisions between workers and heavy equipment.” J. Comput. Civ. Eng. 33 (5): 04019029. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000845.
Stevens, C., and D. Bavelier. 2012. “The role of selective attention on academic foundations: A cognitive neuroscience perspective.” Dev. Cognit. Neurosci. 2 (Feb): S30–S48. https://doi.org/10.1016/j.dcn.2011.11.001.
Sullivan, G. M., and R. Feinn. 2012. “Using effect size—Or why the P value is not enough.” J. Grad. Med. Educ. 4 (3): 279–282. https://doi.org/10.4300/JGME-D-12-00156.1.
Sur, S., and V. K. Sinha. 2009. “Event-related potential: An overview.” Ind. Psychiatry J. 18 (1): 70. https://doi.org/10.4103/0972-6748.57865.
Tateuchi, T., K. Itoh, and T. Nakada. 2012. “Neural mechanisms underlying the orienting response to subject’s own name: An event-related potential study.” Psychophysiology 49 (6): 786–791. https://doi.org/10.1111/j.1469-8986.2012.01363.x.
Teichner, W. H. 1954. “Recent studies of simple reaction time.” Psychol. Bull. 51 (2): 128. https://doi.org/10.1037/h0060900.
Teizer, J., B. S. Allread, C. E. Fullerton, and J. Hinze. 2010. “Autonomous pro-active real-time construction worker and equipment operator proximity safety alert system.” Autom. Constr. 19 (5): 630–640. https://doi.org/10.1016/j.autcon.2010.02.009.
Vahdatikhaki, F., K. El Ammari, A. K. Langroodi, S. Miller, A. Hammad, and A. Doree. 2019. “Beyond data visualization: A context-realistic construction equipment training simulators.” Autom. Constr. 106 (Oct): 102853. https://doi.org/10.1016/j.autcon.2019.102853.
Wang, J., and S. Razavi. 2016a. “Two 4D models effective in reducing false alarms for struck-by-equipment hazard prevention.” J. Comput. Civ. Eng. 30 (6): 04016031. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000589.
Wang, J., and S. N. Razavi. 2016b. “Low false alarm rate model for unsafe-proximity detection in construction.” J. Comput. Civ. Eng. 30 (2): 04015005. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000470.
Watts, F. 1971. “Desensitization as an habituation phenomenon: I. Stimulus intensity as determinant of the effects of stimulus lengths.” Behav. Res. Ther. 9 (3): 209–217. https://doi.org/10.1016/0005-7967(71)90006-4.
Woods, D. L., J. M. Wyma, E. W. Yund, T. J. Herron, and B. Reed. 2015. “Factors influencing the latency of simple reaction time.” Front. Hum. Neurosci. 9 (Mar): 131. https://doi.org/10.3389/fnhum.2015.00131.
Zhang, B., Y. Morère, L. Sieler, C. Langlet, B. Bolmont, and G. Bourhis. 2017. “Reaction time and physiological signals for stress recognition.” Biomed. Signal Process. Control 38 (Sep): 100–107. https://doi.org/10.1016/j.bspc.2017.05.003.

Information & Authors

Information

Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 150Issue 7July 2024

History

Received: Aug 28, 2023
Accepted: Jan 30, 2024
Published online: Apr 27, 2024
Published in print: Jul 1, 2024
Discussion open until: Sep 27, 2024

Permissions

Request permissions for this article.

Authors

Affiliations

Jeonghyeun Chae [email protected]
Graduate Research Assistant, Dept. of Architecture and Architectural Engineering, Yonsei Univ., Seoul 03722, South Korea. Email: [email protected]
Associate Professor, Dept. of Architectural and Urban Systems Engineering, Ewha Womans Univ., Seoul 03760, South Korea. ORCID: https://orcid.org/0000-0001-5387-6274. Email: [email protected]
Associate Professor, Dept. of Architecture and Architectural Engineering, Yonsei Univ., Seoul 03722, South Korea (corresponding author). ORCID: https://orcid.org/0000-0002-2534-2264. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share