Effects of Noise Exposure and Mental Workload on Physiological Responses during Task Execution
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Experimental Conditions
2.3. Physiological Measurement
2.4. Experimental Procedure
3. Results
3.1. Effects of Noise Exposure
3.2. Effects of Mental Workload
3.3. Correlation Analyses
4. Discussion
4.1. Comparison with Previous Studies
4.2. Physiological Mechanisms Affecting Task Performance
4.3. Limitation
5. Conclusions
- (1)
- The physiological responses during the task tests were more significant than those at rest, indicating that additional effort was needed to cope with the adverse conditions when executing the tasks.
- (2)
- The subjects showed increased HRV metrics, modestly lower alpha relative power of EEG, and more visual search effort spent when they accomplished the tasks at higher SPL or increased noise sharpness. It can be inferred that the subjects had to put in more effort to cope with the detrimental effects of unfavorable noise exposure.
- (3)
- The elevated MW resulted in higher theta relative power of EEG and decreased average saccade velocity. This indicated that the subjects were more stressed and it took more visual search effort to perform tasks as the MW increased. Either high or low MW was related to reduced saccade amplitude and decreased task performance, which could help explain the inverted U-shaped relationship between MW and task performance.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Basner, M.; Babisch, W.; Davis, A.; Brink, M.; Clark, C.; Janssen, S.; Stansfeld, S. Auditory and Non-Auditory Effects of Noise on Health. Lancet 2014, 383, 1325–1332. [Google Scholar] [CrossRef]
- Basner, M.; McGuire, S. WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Effects on Sleep. Int. J. Environ. Res. Public Health 2018, 15, 519. [Google Scholar] [CrossRef] [PubMed]
- Zhou, J.; Shi, Z.; Zhou, L.; Hu, Y.; Zhang, M. Occupational Noise-Induced Hearing Loss in China: A Systematic Review and Meta-Analysis. BMJ Open 2020, 10, e039576. [Google Scholar] [CrossRef] [PubMed]
- Kerns, E.; Masterson, E.A.; Themann, C.L.; Calvert, G.M. Cardiovascular Conditions, Hearing Difficulty, and Occupational Noise Exposure within US Industries and Occupations. Am. J. Ind. Med. 2018, 61, 477–491. [Google Scholar] [CrossRef]
- Peris, E. Environmental Noise in Europe: 2020; European Environment Agency: Copenhagen, Denmark, 2020; Volume 1, p. 104.
- Babisch, W.; Fromme, H.; Beyer, A.; Ising, H. Increased Catecholamine Levels in Urine in Subjects Exposed to Road Traffic Noise. Environ. Int. 2001, 26, 475–481. [Google Scholar] [CrossRef]
- Babisch, W. Road Traffic Noise and Cardiovascular Risk. Noise Health 2008, 10, 27. [Google Scholar] [CrossRef]
- Babisch, W. The Noise/Stress Concept, Risk Assessment and Research Needs. Noise Health 2002, 4, 1. [Google Scholar]
- Babisch, W. Cardiovascular Effects of Noise. Noise Health 2011, 13, 201. [Google Scholar] [CrossRef]
- Münzel, T.; Sørensen, M.; Gori, T.; Schmidt, F.P.; Rao, X.; Brook, F.R.; Chen, L.C.; Brook, R.D.; Rajagopalan, S. Environmental Stressors and Cardio-Metabolic Disease: Part II–Mechanistic Insights. Eur. Heart J. 2017, 38, ehw294. [Google Scholar] [CrossRef]
- Münzel, T.; Sørensen, M.; Gori, T.; Schmidt, F.P.; Rao, X.; Brook, J.; Chen, L.C.; Brook, R.D.; Rajagopalan, S. Environmental Stressors and Cardio-Metabolic Disease: Part I–Epidemiologic Evidence Supporting a Role for Noise and Air Pollution and Effects of Mitigation Strategies. Eur. Heart J. 2017, 38, ehw269. [Google Scholar] [CrossRef]
- Guan, H.; Hu, S.; Lu, M.; He, M.; Mao, Z.; Liu, G. People’s Subjective and Physiological Responses to the Combined Thermal-Acoustic Environments. Build Environ. 2020, 172, 106709. [Google Scholar] [CrossRef]
- Fyhri, A.; Aasvang, G.M. Noise, Sleep and Poor Health: Modeling the Relationship between Road Traffic Noise and Cardiovascular Problems. Sci. Total Environ. 2010, 408, 4935–4942. [Google Scholar] [CrossRef]
- Golmohammadi, R.; Darvishi, E.; Shafiee Motlagh, M.; Faradmal, J.; Aliabadi, M.; Rodrigues, M.A. Prediction of Occupational Exposure Limits for Noise-Induced Non-Auditory Effects. Appl. Ergon. 2022, 99, 103641. [Google Scholar] [CrossRef]
- Tomei, G.; Fioravanti, M.; Cerratti, D.; Sancini, A.; Tomao, E.; Rosati, M.V.; Vacca, D.; Palitti, T.; Di Famiani, M.; Giubilati, R.; et al. Occupational Exposure to Noise and the Cardiovascular System: A Meta-Analysis. Sci. Total Environ. 2010, 408, 681–689. [Google Scholar] [CrossRef]
- Seidler, A.; Wagner, M.; Schubert, M.; Dröge, P.; Römer, K.; Pons-Kühnemann, J.; Swart, E.; Zeeb, H.; Hegewald, J. Aircraft, Road and Railway Traffic Noise as Risk Factors for Heart Failure and Hypertensive Heart Disease—A Case-Control Study Based on Secondary Data. Int. J. Hyg. Environ. Health 2016, 219, 749–758. [Google Scholar] [CrossRef]
- Bolm-Audorff, U.; Hegewald, J.; Pretzsch, A.; Freiberg, A.; Nienhaus, A.; Seidler, A. Occupational Noise and Hypertension Risk: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2020, 17, 6281. [Google Scholar] [CrossRef]
- Pretzsch, A.; Seidler, A.; Hegewald, J. Health Effects of Occupational Noise. Curr. Pollut. Rep. 2021, 7, 344–358. [Google Scholar] [CrossRef]
- Orlandi, L.; Brooks, B. Measuring Mental Workload and Physiological Reactions in Marine Pilots: Building Bridges towards Redlines of Performance. Appl. Ergon. 2018, 69, 74–92. [Google Scholar] [CrossRef]
- Young, M.S.; Brookhuis, K.A.; Wickens, C.D.; Hancock, P.A. State of Science: Mental Workload in Ergonomics. Ergonomics 2015, 58, 1–17. [Google Scholar] [CrossRef]
- Marinescu, A.C.; Sharples, S.; Ritchie, A.C.; Sánchez López, T.; McDowell, M.; Morvan, H.P. Physiological Parameter Response to Variation of Mental Workload. Hum. Factors 2018, 60, 31–56. [Google Scholar] [CrossRef]
- Tao, D.; Tan, H.; Wang, H.; Zhang, X.; Qu, X.; Zhang, T. A Systematic Review of Physiological Measures of Mental Workload. Int. J. Environ. Res. Public Health 2019, 16, 2716. [Google Scholar] [CrossRef] [Green Version]
- Zhang, J.; Pang, L.; Cao, X.; Wanyan, X.; Wang, X.; Liang, J.; Zhang, L. The Effects of Elevated Carbon Dioxide Concentration and Mental Workload on Task Performance in an Enclosed Environmental Chamber. Build. Environ. 2020, 178, 106938. [Google Scholar] [CrossRef]
- Brookhuis, K.A.; Waard, D. Assessment of Drivers’ Workload: Performance, Subjective and Physiological Indices; Hancock, P., Desmond, P., Eds.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 2001. [Google Scholar]
- Mach, S.; Storozynski, P.; Halama, J.; Krems, J.F. Assessing Mental Workload with Wearable Devices—Reliability and Applicability of Heart Rate and Motion Measurements. Appl. Ergon. 2022, 105, 103855. [Google Scholar] [CrossRef]
- Fairclough, S.H.; Houston, K. A Metabolic Measure of Mental Effort. Biol. Psychol. 2004, 66, 177–190. [Google Scholar] [CrossRef]
- Zhang, J.; Cao, X.; Wang, X.; Pang, L.; Liang, J.; Zhang, L. Physiological Responses to Elevated Carbon Dioxide Concentration and Mental Workload during Performing MATB Tasks. Build. Environ. 2021, 195, 107752. [Google Scholar] [CrossRef]
- Mahmood, R.; Parveen, N.; Jillani, G.; Safi, A.J.; Din, S.U.; Haq, I.U.; Rehman, J.U.; Haq, A.U. Effect of Noise on Heart Rate. J. Postgrad. Med. Inst. 2011, 20, 12–15. [Google Scholar]
- Kraus, U.; Schneider, A.; Breitner, S.; Hampel, R.; Rückerl, R.; Pitz, M.; Geruschkat, U.; Belcredi, P.; Radon, K.; Peters, A. Individual Daytime Noise Exposure during Routine Activities and Heart Rate Variability in Adults: A Repeated Measures Study. Environ. Health Perspect. 2013, 121, 607–612. [Google Scholar] [CrossRef]
- El Aarbaoui, T.; Méline, J.; Brondeel, R.; Chaix, B. Short-Term Association between Personal Exposure to Noise and Heart Rate Variability: The RECORD MultiSensor Study. Environ. Pollut. 2017, 231, 703–711. [Google Scholar] [CrossRef]
- Charles, R.L.; Nixon, J. Measuring Mental Workload Using Physiological Measures: A Systematic Review. Appl. Ergon. 2019, 74, 221–232. [Google Scholar] [CrossRef]
- De Rivecourt, M.; Kuperus, M.N.; Post, W.J.; Mulder, L.J.M. Cardiovascular and Eye Activity Measures as Indices for Momentary Changes in Mental Effort during Simulated Flight. Ergonomics 2008, 51, 1295–1319. [Google Scholar] [CrossRef] [PubMed]
- Brookings, J.B.; Wilson, G.F.; Swain, C.R. Psychophysiological Responses to Changes in Workload during Simulated Air Traffic Control. Biol. Psychol. 1996, 42, 361–377. [Google Scholar] [CrossRef]
- Finsen, L.; Søgaard, K.; Jensen, C.; Borg, V.; Christensen, H. Muscle Activity and Cardiovascular Response during Computer-Mouse Work with and without Memory Demands. Ergonomics 2001, 44, 1312–1329. [Google Scholar] [CrossRef] [PubMed]
- Gao, Q.; Wang, Y.; Song, F.; Li, Z.; Dong, X. Mental Workload Measurement for Emergency Operating Procedures in Digital Nuclear Power Plants. Ergonomics 2013, 56, 1070–1085. [Google Scholar] [CrossRef]
- Fallahi, M.; Motamedzade, M.; Heidarimoghadam, R.; Soltanian, A.R.; Miyake, S. Effects of Mental Workload on Physiological and Subjective Responses during Traffic Density Monitoring: A Field Study. Appl. Ergon. 2016, 52, 95–103. [Google Scholar] [CrossRef]
- Kramer, A.F. Physiological Metrics of Mental Workload: A Review of Recent Progress. In Multiple-Task Performance; CRC Press: Boca Raton, FL, USA, 1991; ISBN 978-1-00-306944-7. [Google Scholar]
- Pagnotta, M.; Jacobs, D.M.; de Frutos, P.L.; Rodríguez, R.; Ibáñez-Gijón, J.; Travieso, D. Task Difficulty and Physiological Measures of Mental Workload in Air Traffic Control: A Scoping Review. Ergonomics 2022, 65, 1095–1118. [Google Scholar] [CrossRef]
- Ke, J.; Du, J.; Luo, X. The Effect of Noise Content and Level on Cognitive Performance Measured by Electroencephalography (EEG). Autom. Constr. 2021, 130, 103836. [Google Scholar] [CrossRef]
- Ke, J.; Zhang, M.; Luo, X.; Chen, J. Monitoring Distraction of Construction Workers Caused by Noise Using a Wearable Electroencephalography (EEG) Device. Autom. Constr. 2021, 125, 103598. [Google Scholar] [CrossRef]
- Fournier, L.R.; Wilson, G.F.; Swain, C.R. Electrophysiological, Behavioral, and Subjective Indexes of Workload When Performing Multiple Tasks: Manipulations of Task Difficulty and Training. Int. J. Psychophysiol. 1999, 31, 129–145. [Google Scholar] [CrossRef]
- Jaquess, K.J.; Lo, L.-C.; Oh, H.; Lu, C.; Ginsberg, A.; Tan, Y.Y.; Lohse, K.R.; Miller, M.W.; Hatfield, B.D.; Gentili, R.J. Changes in Mental Workload and Motor Performance Throughout Multiple Practice Sessions under Various Levels of Task Difficulty. Neuroscience 2018, 393, 305–318. [Google Scholar] [CrossRef]
- Wilson, G.F. An Analysis of Mental Workload in Pilots during Flight Using Multiple Psychophysiological Measures. Int. J. Aviat. Psychol. 2002, 12, 3–18. [Google Scholar] [CrossRef]
- Kosti, M.V.; Georgiadis, K.; Adamos, D.A.; Laskaris, N.; Spinellis, D.; Angelis, L. Towards an Affordable Brain Computer Interface for the Assessment of Programmers’ Mental Workload. Int. J. Hum.-Comput. Stud. 2018, 115, 52–66. [Google Scholar] [CrossRef]
- Matthews, G.; Reinerman-Jones, L.E.; Barber, D.J.; Abich, J. The Psychometrics of Mental Workload: Multiple Measures Are Sensitive but Divergent. Hum. Factors 2015, 57, 125–143. [Google Scholar] [CrossRef]
- Di Nocera, F.; Camilli, M.; Terenzi, M. A Random Glance at the Flight Deck: Pilots’ Scanning Strategies and the Real-Time Assessment of Mental Workload. J. Cogn. Eng. Decis. Mak. 2007, 1, 271–285. [Google Scholar] [CrossRef]
- Di Stasi, L.L.; Marchitto, M.; Antolí, A.; Baccino, T.; Cañas, J.J. Approximation of On-Line Mental Workload Index in ATC Simulated Multitasks. J. Air Transp. Manag. 2010, 16, 330–333. [Google Scholar] [CrossRef]
- Chen, Y.; Yan, S.; Tran, C.C. Comprehensive Evaluation Method for User Interface Design in Nuclear Power Plant Based on Mental Workload. Nucl. Eng. Technol. 2019, 51, 453–462. [Google Scholar] [CrossRef]
- Di Stasi, L.L.; Antolí, A.; Cañas, J.J. Evaluating Mental Workload While Interacting with Computer-Generated Artificial Environments. Entertain. Comput. 2013, 4, 63–69. [Google Scholar] [CrossRef]
- Strukelj, A.; Holmberg, N.; Lindström, P.; Mossberg, F.; Brännström, J.; Holmqvist, K. Text Comprehension during Noise Exposure: Effects on Eye Movements, Galvanic Skin Responses and Subjective Performance. In Proceedings of the SWAET 2012, Las Vegas, NV, USA, 9–11 June 2012. [Google Scholar]
- Liao, H.-I.; Kidani, S.; Yoneya, M.; Kashino, M.; Furukawa, S. Correspondences among Pupillary Dilation Response, Subjective Salience of Sounds, and Loudness. Psychon. Bull. Rev. 2016, 23, 412–425. [Google Scholar] [CrossRef]
- Hogervorst, M.A.; Brouwer, A.-M.; van Erp, J.B.F. Combining and Comparing EEG, Peripheral Physiology and Eye-Related Measures for the Assessment of Mental Workload. Front. Neurosci. 2014, 8, 322. [Google Scholar] [CrossRef]
- Santiago-Espada, Y.; Myer, R.R.; Latorella, K.A.; Comstock, J. The Multi-Attribute Task Battery II (MATB-II) Software for Human Performance and Workload Research: A User’s Guide; NASA: Hanover, MD, USA, 2011.
- Hart, S.G.; Staveland, L.E. Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. Adv. Psychol. 1988, 52, 139–183. [Google Scholar]
- Münzel, T.; Gori, T.; Babisch, W.; Basner, M. Cardiovascular Effects of Environmental Noise Exposure. Eur. Heart J. 2014, 35, 829–836. [Google Scholar] [CrossRef]
- Passchier-Vermeer, W.; Passchier, W.F. Noise Exposure and Public Health. Environ. Health Perspect. 2000, 108, 123–131. [Google Scholar]
- Glorig, A. The Effects of Noise on Man. JAMA 1966, 196, 839. [Google Scholar] [CrossRef]
- Widmann, U. Aurally Adequate Evaluation of Sounds. In Proceedings of the EuroNoise ’98, Munich, Germany, 1 January 1998. [Google Scholar]
- Maschke, C.; Widmann, U. The Effects of Sound on Humans. In Handbook of Engineering Acoustics; Müller, G., Möser, M., Eds.; Springer: Berlin/Heidelberg, Germany, 2013; pp. 69–86. ISBN 978-3-540-69460-1. [Google Scholar]
- EN 61672-1:2013; Electroacoustics—Sound Level Meters—Part1: Specifications. International Electrotechnical Commission: Newark, DE, USA, 2002.
- ISO Standards 7933; Ergonomics of the Thermal Environment—Analytical Determination and Interpretation of Heat Stress Using Calculation of the Predicted Heat Strain. International Standards Organization: Geneva, Switzerland, 2004.
- Standard 55-2010; Thermal Environmental Conditions for Human Occupancy. Atlanta—American Society of Heating, Refrigerating and Air-Conditioning Engineers: Atlanta, GA, USA, 2010.
- Klem, G.H.; Lüders, H.O.; Jasper, H.H.; Elger, C. The Ten-Twenty Electrode System of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalogr. Clin. Neurophysiol. Suppl. 1999, 52, 3–6. [Google Scholar]
- Hutchinson, T.E.; White, K.P.; Martin, W.N.; Reichert, K.C.; Frey, L.A. Human-Computer Interaction Using Eye-Gaze Input. IEEE Trans. Syst. Man Cybern. 1989, 19, 1527–1534. [Google Scholar] [CrossRef]
- Andersson, R.; Nyström, M.; Holmqvist, K. Sampling Frequency and Eye-Tracking Measures: How Speed Affects Durations, Latencies, and More. J. Eye Mov. Res. 2010, 3, 1–12. [Google Scholar] [CrossRef]
- Profillidis, V.A.; Botzoris, G.N. Modeling of Transport Demand: Analyzing, Calculating, and Forecasting Transport Demand; Elsevier: Amsterdam, The Netherlands, 2018; ISBN 0-12-811514-9. [Google Scholar]
- Sim, C.S.; Sung, J.H.; Cheon, S.H.; Lee, J.M.; Lee, J.W.; Lee, J. The Effects of Different Noise Types on Heart Rate Variability in Men. Yonsei Med. J. 2015, 56, 235. [Google Scholar] [CrossRef]
- Lee, G.-S.; Chen, M.-L.; Wang, G.-Y. Evoked Response of Heart Rate Variability Using Short-Duration White Noise. Auton. Neurosci. 2010, 155, 94–97. [Google Scholar] [CrossRef]
- Fairclough, S.H.; Venables, L.; Tattersall, A. The Influence of Task Demand and Learning on the Psychophysiological Response. Int. J. Psychophysiol. 2005, 56, 171–184. [Google Scholar] [CrossRef]
- Ahlstrom, U.; Friedman-Berg, F.J. Using Eye Movement Activity as a Correlate of Cognitive Workload. Int. J. Ind. Ergon. 2006, 36, 623–636. [Google Scholar] [CrossRef]
- May, J.G.; Kennedy, R.S.; Williams, M.C.; Dunlap, W.P.; Brannan, J.R. Eye Movement Indices of Mental Workload. Acta Psychol. 1990, 75, 75–89. [Google Scholar] [CrossRef]
- Park, S.; Kyung, G.; Choi, D.; Yi, J.; Lee, S.; Choi, B.; Lee, S. Effects of Display Curvature and Task Duration on Proofreading Performance, Visual Discomfort, Visual Fatigue, Mental Workload, and User Satisfaction. Appl. Ergon. 2019, 78, 26–36. [Google Scholar] [CrossRef]
- Park, S.H.; Lee, P.J.; Jeong, J.H. Effects of Noise Sensitivity on Psychophysiological Responses to Building Noise. Build. Environ. 2018, 136, 302–311. [Google Scholar] [CrossRef]
- Golmohammadi, R.; Darvishi, E.; Shafiee Motlagh, M.; Faradmal, J. Role of Individual and Personality Traits in Occupational Noise-Induced Psychological Effects. Appl. Acoust. 2021, 173, 107699. [Google Scholar] [CrossRef]
- Abbasi, M.; Tokhi, M.O.; Falahati, M.; Yazdanirad, S.; Ghaljahi, M.; Etemadinezhad, S.; Jaffari Talaar Poshti, R. Effect of Personality Traits on Sensitivity, Annoyance and Loudness Perception of Low- and High-Frequency Noise. J. Low Freq. Noise Vib. Act. Control. 2021, 40, 643–655. [Google Scholar] [CrossRef]
- Boele-Vos, M.J.; Commandeur, J.J.F.; Twisk, D.A.M. Effect of Physical Effort on Mental Workload of Cyclists in Real Traffic in Relation to Age and Use of Pedelecs. Accid. Anal. Prev. 2017, 105, 84–94. [Google Scholar] [CrossRef] [PubMed]
- Causse, M.; Chua, Z.K.; Rémy, F. Influences of Age, Mental Workload, and Flight Experience on Cognitive Performance and Prefrontal Activity in Private Pilots: A FNIRS Study. Sci. Rep. 2019, 9, 7688. [Google Scholar] [CrossRef] [PubMed]
- Cantin, V.; Lavallière, M.; Simoneau, M.; Teasdale, N. Mental Workload When Driving in a Simulator: Effects of Age and Driving Complexity. Accid. Anal. Prev. 2009, 41, 763–771. [Google Scholar] [CrossRef]
- Henry, J.P. Biological Basis of the Stress Response. Integr. Physiol. Behav. Sci. 1992, 27, 66–83. [Google Scholar] [CrossRef]
- De Waard, D.; Brookhuis, K.A. The Measurement of Drivers’ Mental Workload; The Traffic Research Centre VSC, University of Groningen: Haren, The Netherlands, 1996; ISBN 90-6807-308-7. [Google Scholar]
- Cohen, S. Aftereffects of Stress on Human Performance and Social Behavior: A Review of Research and Theory. Psychol. Bull. 1980, 88, 82–108. [Google Scholar] [CrossRef]
- Weinstein, N.D. Effect of Noise on Intellectual Performance. J. Appl. Psychol. 1974, 59, 548–554. [Google Scholar] [CrossRef]
- Weinstein, N.D. Noise and Intellectual Performance: A Confirmation and Extension. J. Appl. Psychol. 1977, 62, 104–107. [Google Scholar] [CrossRef]
Thermal Environment Parameters | Measurement Range | Accuracy | Resolution |
---|---|---|---|
Air temperature | −20 °C–+60 °C | ±0.2 °C | 0.1 °C |
Relative humidity | 0% RH–10% RH | ±3% RH | 0.1% RH |
10% RH–90% RH | ±2% RH | 0.1% RH | |
90% RH–100% RH | ±3% RH | 0.1% RH | |
Air velocity | 0.1 m/s–9.9 m/s | ±(0.05 m/s + 5%) | 0.01 m/s |
10.0 m/s–20.0 m/s | ±(5%) | 0.1 m/s | |
Black bulb temperature | 10.0 °C–49.9 °C | ±0.5 °C | 0.1 °C |
50.0 °C–84.9 °C | ±1.0 °C | 0.1 °C | |
85.0 °C–120.0 °C | ±1.5 °C | 0.1 °C |
Environment Parameters | N85-S1 | N80-S1 | N75-S2 |
---|---|---|---|
A-weighted SPL (dB(A)) | 84.2 ± 0.8 | 78.3 ± 0.7 | 75.0 ± 0.8 |
Sharpness (acum) | 1.28 ± 0.03 | 1.30 ± 0.03 | 2.42 ± 0.04 |
Air temperature (°C) | 20.9 ± 0.6 | 21.0 ± 0.6 | 21.1 ± 0.6 |
Relative humidity (%) | 26.5 ± 8.1 | 29.0 ± 7.5 | 24.7 ± 5.6 |
Air velocity (m/s) | 0.12 ± 0.01 | 0.13 ± 0.01 | 0.12 ± 0.01 |
Black bulb temperature (°C) | 21.1 ± 0.6 | 21.2 ± 0.6 | 21.3 ± 0.5 |
Parameter | Metric | Implication |
---|---|---|
ECG | SDNN (ms) | Standard deviation of NN interval time series |
RMSSD (ms) | Root mean square of successive differences between normal heartbeats | |
pNN50 (%) | Percentage of successive RR intervals that differ by more than 50 ms | |
EEG | Alpha relative power | Inability to focus, relaxation (8–13 Hz) |
Beta relative power | High arousal, stress (14–30 Hz) | |
Theta relative power | Drowsy, depression (4–7 Hz) | |
Delta relative power | Extreme fatigue, deep sleep (1–3 Hz) | |
Eye movements | Fixation duration (ms) | The sum of time the eyes remain fixated on each fixation point in the task scene region |
Saccade amplitude (px) | The distance from the end of the last fixation to the beginning of the next fixation in pixels | |
Saccade velocity (px/ms) | The average distance per second between fixation points, defined as the saccade amplitude divided by the saccade time | |
Mean pupil diameter (px) | The average diameter of left and right pupil |
ECG Metrics | Noise Exposure | MW | Intercept | |||||
---|---|---|---|---|---|---|---|---|
N75-S2 | N80-S1 | N85-S1 | LMW | MMW | HMW | |||
SDNN (ms) | Estimate | −14.380 * | −9.834 | Reference | Reference | 1.806 | 1.847 | 78.858 |
p | 0.016 | 0.100 | 0.755 | 0.761 | - | |||
RMSSD (ms) | Estimate | −6.443 | −9.721 | 7.517 | 7.815 | 52.715 | ||
p | 0.310 | 0.142 | 0.223 | 0.232 | - | |||
pNN50 (%) | Estimate | −0.124 ** | −0.076 * | 0.018 | 0.036 | 0.302 | ||
p | <0.001 | 0.029 | 0.600 | 0.302 | - | |||
SDNN (ms) | Estimate | −4.541 | Reference | 9.834 | −1.806 | Reference | 0.041 | 70.825 |
p | 0.451 | 0.100 | 0.755 | 0.995 | - | |||
RMSSD (ms) | Estimate | 3.278 | 9.721 | −7.517 | 0.298 | 50.512 | ||
p | 0.611 | 0.142 | 0.223 | 0.964 | - | |||
pNN50 (%) | Estimate | −0.048 | 0.076 * | −0.018 | 0.018 | 0.244 | ||
p | 0.172 | 0.029 | 0.600 | 0.595 | - |
EEG Metrics | Noise Exposure | MW | Intercept | |||||
---|---|---|---|---|---|---|---|---|
N75-S2 | N80-S1 | N85-S1 | LMW | MMW | HMW | |||
Alpha relative power | Estimate | 0.002 | −0.006 | Reference | Reference | 0.002 | −0.006 | 0.164 |
p | 0.589 | 0.190 | 0.680 | 0.188 | - | |||
Beta relative power | Estimate | 0.004 | 0.005 | 0.000 | −0.001 | 0.067 | ||
p | 0.322 | 0.193 | 0.963 | 0.713 | - | |||
Theta relative power | Estimate | 0.001 | 0.000 | 0.001 | 0.011 ** | 0.191 | ||
p | 0.742 | 0.772 | 0.721 | 0.002 | - | |||
Delta relative power | Estimate | −0.004 | 0.004 | 0.000 | 0.002 | 0.555 | ||
p | 0.588 | 0.638 | 0.971 | 0.784 | - | |||
Alpha relative power | Estimate | 0.008 | Reference | 0.006 | −0.002 | Reference | −0.008 | 0.160 |
p | 0.066 | 0.190 | 0.680 | 0.085 | - | |||
Beta relative power | Estimate | −0.001 | −0.005 | 0.000 | −0.002 | 0.072 | ||
p | 0.753 | 0.193 | 0.963 | 0.679 | - | |||
Theta relative power | Estimate | 0.002 | 0.000 | −0.001 | 0.009 ** | 0.192 | ||
p | 0.537 | 0.772 | 0.721 | 0.007 | - | |||
Delta relative power | Estimate | −0.008 | −0.004 | 0.000 | 0.002 | 0.558 | ||
p | 0.312 | 0.638 | 0.971 | 0.756 | - |
Eye Movements | Noise Exposure | MW | Intercept | |||||
---|---|---|---|---|---|---|---|---|
N75-S2 | N80-S1 | N85-S1 | LMW | MMW | HMW | |||
Fixation duration | Estimate | 37.886 | 3.089 | Reference | Reference | −28.991 | −39.680 | 455.403 |
p | 0.165 | 0.909 | 0.287 | 0.146 | ||||
Saccade amplitude | Estimate | 18.092 | 7.504 | 38.851 ** | 20.548 * | 329.040 | ||
p | 0.053 | 0.418 | <0.001 | 0.028 | ||||
Saccade velocity | Estimate | −0.015 | −0.009 | −0.025 | −0.049 ** | 1.417 | ||
p | 0.364 | 0.572 | 0.127 | 0.003 | ||||
Mean pupil diameter | Estimate | −0.371 | −0.675 * | 0.034 | 0.285 | 18.549 | ||
p | 0.153 | 0.010 | 0.894 | 0.271 | ||||
Fixation duration | Estimate | 34.796 | Reference | −3.089 | 28.991 | Reference | −10.688 | 455.403 |
p | 0.202 | 0.909 | 0.287 | 0.694 | ||||
Saccade amplitude | Estimate | 10.588 | −7.504 | 38.851 ** | −18.303 * | 375.395 | ||
p | 0.254 | 0.418 | <0.001 | 0.050 | ||||
Saccade velocity | Estimate | −0.006 | 0.009 | 0.025 | −0.024 | 1.383 | ||
p | 0.730 | 0.572 | 0.127 | 0.130 | ||||
Mean pupil diameter | Estimate | 0.304 | 0.675* | −0.034 | 0.251 | 17.908 | ||
p | 0.240 | 0.010 | 0.894 | 0.333 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Fan, Y.; Liang, J.; Cao, X.; Pang, L.; Zhang, J. Effects of Noise Exposure and Mental Workload on Physiological Responses during Task Execution. Int. J. Environ. Res. Public Health 2022, 19, 12434. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191912434
Fan Y, Liang J, Cao X, Pang L, Zhang J. Effects of Noise Exposure and Mental Workload on Physiological Responses during Task Execution. International Journal of Environmental Research and Public Health. 2022; 19(19):12434. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191912434
Chicago/Turabian StyleFan, Yurong, Jin Liang, Xiaodong Cao, Liping Pang, and Jie Zhang. 2022. "Effects of Noise Exposure and Mental Workload on Physiological Responses during Task Execution" International Journal of Environmental Research and Public Health 19, no. 19: 12434. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191912434