Ergonomi Kognitif dalam Sistem Kerja dan Interaksi Manusia-Teknologi: Systematic Literature Review tentang Penerapan, Pengukuran, dan Luaran

Silvana Mohamad; Moh. Ainul Fais; Dedy Kunhadi; Bambang Sutejo; Djaffar Sodiq; Novid Hidayat; Mohamad Tsaqif Apta Laksono

Authors

Silvana Mohamad Universitas Negeri Gorontalo
Moh. Ainul Fais Universitas W R Supratman
Dedy Kunhadi Universitas W R Supratman
Bambang Sutejo Universitas W R Supratman
Djaffar Sodiq Universitas W R Supratman
Novid Hidayat Universitas W R Supratman
Mohamad Tsaqif Apta Laksono Universitas W R Supratman

Keywords:

cognitive ergonomics, human-technology interaction, mental workload, multimodal measurement, systematic literature review, work systems

Abstract

Digital work-system transformation intensifies human-technology interaction and creates a need to understand how cognitive ergonomics is applied, measured, and associated with human and system outcomes. This study maps cognitive ergonomics applications, mental-workload measurement approaches, and their relationships with performance, safety, usability, technology acceptance, and worker well-being. A systematic literature review was conducted on 52 full-text journal articles published from 2020 to 2026. Articles were selected through deduplication, multistage screening, DOI verification, quality appraisal, and extraction of 29 variables. The findings identify five application mechanisms: task and interface redesign, human-technology function allocation, cognitive-state monitoring, decision support and training, and integration into work systems. Measurement approaches include subjective ratings, performance measures, behavioral indicators, physiological and neurophysiological signals, task analysis, and multimodal assessment. Associations with outcomes are conditional because they vary according to task complexity, experience, age, duration, technology transparency, and environmental conditions. The review proposes a three-layer application-measurement-outcome framework in which workload functions as a linking mechanism and a source of feedback for redesign. The findings support multi-indicator evaluation, field validation, and designs that preserve cognitive fit, predictability, control, situation awareness, and recovery.

References

Arana-De las Casas, N. I., De la Riva-Rodríguez, J., Maldonado-Macías, A. A., & Sáenz-Zamarrón, D. (2023). Cognitive analyses for interface design using Dual N-Back tasks for mental workload (mwl) evaluation. International Journal of Environmental Research and Public Health, 20(2), 1184. https://doi.org/10.3390/ijerph20021184

Bagheri, M., & Power, S. D. (2022). Simultaneous classification of both mental workload and stress level suitable for an online passive brain-computer interface. Sensors, 22(2), 535. https://doi.org/10.3390/s22020535

Basnet, N., & Zahabi, M. (2025). Real-time cognitive workload assessment using non-intrusive methods: A systematic review. Ergonomics, 1–26. https://doi.org/10.1080/00140139.2025.2606779

Bläsing, D., Bornewasser, M., & Hinrichsen, S. (2022). Cognitive compatibility in modern manual mixed-model assembly systems. Zeitschrift für Arbeitswissenschaft, 76, 289–302. https://doi.org/10.1007/s41449-021-00296-1

Braarud, P. Ø. (2024). Measuring cognitive workload in the nuclear control room: A review. Ergonomics. Advance online publication. https://doi.org/10.1080/00140139.2024.2302381

Caiazzo, C., Djapan, M., Savkovic, M., Milojevic, D., Vukicevic, A., & Gualtieri, L. (2025). Evaluating mental workload and productivity in manufacturing: A neuroergonomic study of human-robot collaboration scenarios. Machines, 13(9), 783. https://doi.org/10.3390/machines13090783

Caiazzo, C., Savkovic, M., Pusica, M., Milojevic, D., Leva, M. C., & Djapan, M. (2023). Development of a neuroergonomic assessment for the evaluation of mental workload in an industrial human-robot interaction assembly task: A comparative case study. Machines, 11(11), 995. https://doi.org/10.3390/machines11110995

Cao, H., Garcia Rivera, F., Söderlund, H., Berlin, C., Stahre, J., & Johansson, B. (2025). Human-centered design of VR interface features to support mental workload and spatial cognition during collaboration tasks in manufacturing. Cognition, Technology & Work, 27, 467–485. https://doi.org/10.1007/s10111-025-00809-6

Cescon, M., & Peruzzini, M. (2026). Evaluating UX and usability in automotive human-machine interfaces: A systematic review. Applied Sciences, 16(7), 3437. https://doi.org/10.3390/app16073437

Darejeh, A., Marcusa, N., Mohammadi, G., & Sweller, J. (2026). Cognitive load measurement methods for usability testing. Human Factors, 68(7). https://doi.org/10.1177/00187208261427867

Dehais, F., Lafont, A., Roy, R., & Fairclough, S. (2020). A neuroergonomics approach to mental workload, engagement and human performance. Frontiers in Neuroscience, 14(2020), 268. https://doi.org/10.3389/fnins.2020.00268

Diarra, M., Theurel, J., & Paty, B. (2025). Systematic review of neurophysiological assessment techniques and metrics for mental workload evaluation in real-world settings. Frontiers in Neuroergonomics, 6(2025), 1584736. https://doi.org/10.3389/fnrgo.2025.1584736

Doost, E. Z., & Zhang, W. (2022). Mental workload variations during different cognitive office tasks with social media interruptions. Ergonomics, 66(5), 592–608. https://doi.org/10.1080/00140139.2022.2104381

Drankoff, L., & Bommer, S. (2020). A systems engineering framework for integration of cognitive ergonomics in smart factory configurations. Journal of Management and Engineering Integration, 13(1), 53–61. https://doi.org/10.62704/10057/24745

Dörner, A., Bures, M., Simon, M., & Pirkl, G. (2024). Making cognitive ergonomics in the human-computer interaction of manufacturing execution systems assessable: Experimental and validation approaches to closing research gaps. Machines, 12, 195. https://doi.org/10.3390/machines12030195

Faidah, U. N., Maulana, I., & Efranto, R. Y. (2026). Driver mental workload measurement trends and cognitive impacts: A literature review. Theoretical Issues in Ergonomics Science. Advance online publication. https://doi.org/10.1080/1463922x.2025.2608063

Fogelberg, E., Cao, H., & Thorvald, P. (2025). Cognitive ergonomics: Triangulation of physiological, subjective, and performance-based mental workload assessments. Frontiers in Industrial Engineering, 3(2025), 1605975. https://doi.org/10.3389/fieng.2025.1605975

Gervasi, R., Capponi, M., Mastrogiacomo, L., & Franceschini, F. (2025). Eye-tracking support for analyzing human factors in human-robot collaboration during repetitive long-duration assembly processes. Production Engineering, 19, 47–64. https://doi.org/10.1007/s11740-024-01294-y

Guerrero-Castañeda, J. E., Balderrama-Armendariz, C. O., & Maldonado-Macías, A. A. (2026). Improvement of additive manufacturing processes through cognitive ergonomics analyses: A case study in fused deposition modeling. Processes, 14(5), 823. https://doi.org/10.3390/pr14050823

Hilmi, A. H., Hamid, A. R. A., & Ibrahim, W. A. R. A. W. (2024). Advancements in cognitive ergonomics: Integration with human-robot collaboration, workload management, and industrial applications. Malaysian Journal of Ergonomics (MJEr), 6(1), 29–41. https://doi.org/10.58915/mjer.v6.2024.1368

Hilmi, A. H., HAMID, A. R. A., & Ibrahim, W. A. R. A. W. (2025). Integrating physical and cognitive ergonomics: Workload, performance, and human-technology interaction across complex systems. Malaysian Journal of Ergonomics (MJEr), 7, 129–146. https://doi.org/10.58915/mjer.v7.2025.2767

Holt, K. L. (2025). Cognitive ergonomics in the aging workforce: A contemporary health and safety perspective. International Journal of Contemporary Sciences (IJCS), 8, 2025. https://doi.org/10.55927/f36qj339

Ioniță, A.-R., Anghel, D.-C., & Boudouh, T. (2025). Mind, machine, and meaning: Cognitive ergonomics and adaptive interfaces in the age of Industry 5.0. Applied Sciences, 15, 7703. https://doi.org/10.3390/app15147703

Jin, H., Zhu, L., Li, M., & Duffy, V. G. (2023). Recognition and evaluation of mental workload in different stages of perceptual and cognitive information processing using a multimodal approach. Ergonomics, 67(3), 377–397. https://doi.org/10.1080/00140139.2023.2223785

Kazemi, R., & Smith, A. (2022). Overcoming COVID-19 pandemic: Emerging challenges of human factors and the role of cognitive ergonomics. Theoretical Issues in Ergonomics Science. Advance online publication. https://doi.org/10.1080/1463922x.2022.2090027

Kia, K., Hwang, J., & Kim, J. H. (2024). The effects of target sizes on biomechanical and cognitive load and task performance of virtual reality interactions. Ergonomics, 68(8), 1207–1221. https://doi.org/10.1080/00140139.2024.2396038

Kodithuwakku Arachchige, S. N. K., Burch V, R. F., Chander, H., Turner, A. J., & Knight, A. C. (2021). The use of wearable devices in cognitive fatigue: Current trends and future intentions. Theoretical Issues in Ergonomics Science. Advance online publication. https://doi.org/10.1080/1463922x.2021.1965670

Koirala, R., & Maharjan, K. (2022). Cognitive ergonomics on employee wellbeing: A literature review. The Journal of Economic Concerns, 13, 93–106. https://doi.org/10.3126/tjec.v13i1.57064

Kordmiri, S. H. M., Aliabadi, M., Golmohammadi, R., Farhadian, M., & Balochkhaneh, F. A. (2024). Effect of concurrent exposure to noise and hand-transmitted vibration on auditory and cognitive attention under simulated work with construction tools. International Journal of Occupational Safety and Ergonomics. Advance online publication. https://doi.org/10.1080/10803548.2024.2337545

Li, H., & Lu, H. (2026). Integrating ergonomics and cognitive systems engineering for occupational safety in healthcare work systems: An exploratory study. Economics Ecology Socium, 2(2026), 94–105. https://doi.org/10.61954/2616-7107/2026.10.2-7

Li-Wang, J., Townsley, A., & Katta, R. (2023). Cognitive ergonomics: A review of interventions for outpatient practice. Cureus, 15(8), e44258. https://doi.org/10.7759/cureus.44258

Liu, C., & Qu, Q.-X. (2026). Research on the influence of interface visual design features of mobile news on cognitive load: A study of elderly users in china. Behavioral Sciences, 16(1), 32. https://doi.org/10.3390/bs16010032

Longo, L., Wickens, C. D., Hancock, G., & Hancock, P. A. (2022). Human mental workload: A survey and a novel inclusive definition. Frontiers in Psychology, 13(2022), 883321. https://doi.org/10.3389/fpsyg.2022.883321

Moreira, S. S. D. C., Santos, I. J. A. L. D., & Morgado, C. D. R. V. (2023). Cognitive ergonomics in the analysis of work on offshore platforms: “Cognitive Bowtie” application. STUDIES IN HEALTH SCIENCES, 4(2), 419–442. https://doi.org/10.54022/shsv4n2-013

MOUDETTIR, Y., OUHRIR, S., & LOTFI, S. (2025). Enhancing cognitive ergonomics and pedagogical quality a comprehensive evaluation framework for technological pedagogical tools in physical education. Cuestiones de Fisioterapia, 54(3), 5007–5029. https://doi.org/10.48047/53m9x307

Musicant, O., Kuperman, A., & Barachman, R. (2026). Safety, efficiency, and mental workload of predictive display in simulated teledriving. Sensors, 26, 221. https://doi.org/10.3390/s26010221

Panchetti, T., Pietrantoni, L., Puzzo, G., Gualtieri, L., & Fraboni, F. (2023). Assessing the relationship between cognitive workload, workstation design, user acceptance and trust in collaborative robots. Applied Sciences, 13(3), 1720. https://doi.org/10.3390/app13031720

Pereira, E., Sigcha, L., Silva, E., Sampaio, A., Costa, N., & Costa, N. (2025). Capturing mental workload through physiological sensors in human-robot collaboration: A systematic literature review. Applied Sciences, 15(6), 3317. https://doi.org/10.3390/app15063317

Rodriguez Aguiñaga, A., Realyvásquez-Vargas, A., López R., M. Á., & Quezada, A. (2020). Cognitive ergonomics evaluation assisted by an intelligent emotion recognition technique. Applied Sciences, 10(5), 1736. https://doi.org/10.3390/app10051736

Saud, S., & Saud, M. (2025). A holistic approach to radiology: The impact of physical, cognitive, and organizational ergonomics. Canadian Journal of Medical Sonography, 16, 51–58. https://doi.org/10.3138/cjms-2025-0002

Segura, P., Lobato-Calleros, O., Soria-Arguello, I., & Hernández-Martínez, E. G. (2025). Work roles in human-robot collaborative systems: Effects on cognitive ergonomics for the manufacturing industry. Applied Sciences, 15(2), 744. https://doi.org/10.3390/app15020744

Silva, N. M. D., Merino, E. A. D., & Paulo, I. I. (2025). Cognitive ergonomics and eye tracking in undersea well drilling: An integrative review. Revista Ação Ergonômica, 19, e202506. https://doi.org/10.4322/rae.v19n2.e202506.en

Staab, V., Ramrath, M., Bačkalov, I., Athanassiou, G., & Liebherr, M. (2026). Mental workload in the maritime industry: A pre-registered systematic review of influencing factors. WMU Journal of Maritime Affairs. Advance online publication. https://doi.org/10.1007/s13437-026-00420-0

Taheri, M. R., Mortazavi, S. B., Asilian, H., Ahmadi, O., & Sogandi, F. (2022). Investigating human error in Iran’s copper mines using CREAM based on human cognitive reliability analysis. International Journal of Occupational Safety and Ergonomics. Advance online publication. https://doi.org/10.1080/10803548.2022.2135259

Tanaka, K., Asaumi, K., Kasai, R., Sato, H., Uchibayashi, R., & Shigenaga, M. (2026). An ergonomic approach to medical safety training using augmented reality glasses: System design, cognitive-neuroscientific theoretical framework, and preliminary outcomes. Theoretical and Applied Ergonomics, 2(2), 10. https://doi.org/10.3390/tae2020010

Trstenjak, M., Benešova, A., Opetuk, T., & Cajner, H. (2025). Human factors and ergonomics in Industry 5.0: A systematic literature review. Applied Sciences, 15(4), 2123. https://doi.org/10.3390/app15042123

Vizcarra, A., Quiroz, G., & Cornejo, J. (2026). The impact of user interface and experience (UI/UX) design on visual ergonomics: A technical approach for reducing human error in industrial settings. Designs, 10(1), 8. https://doi.org/10.3390/designs10010008

Wong, S. W., & Crowe, P. (2024). Cognitive ergonomics and robotic surgery. Journal of Robotic Surgery, 18, 110. https://doi.org/10.1007/s11701-024-01852-7

Yao, Y., Han, T., & Li, D. (2026). Assistance or distraction? A cognitive ergonomics perspective on cognitive load during AI-assisted post-editing. International Journal of Human–Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2026.2628994

Yiu, C. Y., Ng, K. K. H., Li, Q., & Yuan, X. (2025). Gaze behaviours, situation awareness and cognitive workload of air traffic controllers in radar screen monitoring tasks with varying task complexity. International Journal of Occupational Safety and Ergonomics. Advance online publication. https://doi.org/10.1080/10803548.2025.2453312

Zhou, C., Qian, Y., Huang, T., Kaner, J., & Zhang, Y. (2022). The impact of different age-friendly smart home interface styles on the interaction behavior of elderly users. Frontiers in Psychology, 13(2022), 935202. https://doi.org/10.3389/fpsyg.2022.935202

Zhou, C., Yuan, F., Huang, T., Zhang, Y., & Kaner, J. (2022). The impact of interface design element features on task performance in older adults: Evidence from eye-tracking and EEG signals. International Journal of Environmental Research and Public Health, 19(15), 9251. https://doi.org/10.3390/ijerph19159251