Development and validation of a behavioural video coding scheme for detecting mental workload in manual assembly |
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| Authors: | Bram B Van Acker Davy D Parmentier Peter D Conradie Stephanie Van Hove Alessandro Biondi Klaas Bombeke |
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| Affiliation: | 1. Department of Industrial Systems and Product Design, Faculty of Engineering and Architecture, Ghent University, Zwijnaarde, Belgium;2. Department of Work, Organisation and Society, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium;3. Research group IMEC-MICT-Ghent University, De Krook, Miriam Makebaplein, Ghent, Belgium bramb.vanacker@ugent.be https://orcid.org/0000-0002-6565-3569;5. Department of Industrial Systems and Product Design, Faculty of Engineering and Architecture, Ghent University, Zwijnaarde, Belgium;6. Research group IMEC-MICT-Ghent University, De Krook, Miriam Makebaplein, Ghent, Belgium https://orcid.org/0000-0003-4495-9136;7. Research group IMEC-MICT-Ghent University, De Krook, Miriam Makebaplein, Ghent, Belgium;8. Department of Communication Sciences, Faculty of Political and Social Sciences, Universiteitstraat, Ghent, Belgium |
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| Abstract: | Abstract Manual assembly in the future Industry 4.0 workplace will put high demands on operators’ cognitive processing. The development of mental workload (MWL) measures therefore looms large. Physiological gauges such as electroencephalography (EEG) show promising possibilities, but still lack sufficient reliability when applied in the field. This study presents an alternative measure with a substantial ecological validity. First, we developed a behavioural video coding scheme identifying 11 assembly behaviours potentially revealing MWL being too high. Subsequently, we explored its validity by analysing videos of 24 participants performing a high and a low complexity assembly. Results showed that five of the behaviours identified, such as freezing and the amount of part rotations, significantly differed in occurrence and/or duration between the two conditions. The study hereby proposes a novel and naturalistic method that could help practitioners to map and redesign critical assembly phases, and researchers to enrich validation of MWL-measures through measurement triangulation. Practitioner summary: Current physiological mental workload (MWL) measures still lack sufficient reliability when applied in the field. Therefore, we identified several observable assembly behaviours that could reveal MWL being too high. The results propose a method to map MWL by observing specific assembly behaviours such as freezing and rotating parts. Abbreviations: MWL: mental workload; EEG: electroencephalography; fNIRS: functional near infrared spectroscopy; AOI: area of interest; SMI: SensoMotoric Instruments, ETG: Eye-Tracking Glasses; FPS: frames per second; BORIS: Behavioral Observation Research Interactive Software; IRR: inter-rater reliability; SWAT: Subjective Workload Assessment Technique; NASA-TLX: National Aeronautics and Space Administration Task Load Index; EL: emotional load; DSSQ: Dundee Stress State Questionnaire; PHL: physical load; SBO: Strategisch Basis Onderzoek |
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| Keywords: | Mental workload measurement behavioural video coding validation assembly |
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https://orcid.org/0000-0002-6565-3569;5. Department of Industrial Systems and Product Design, Faculty of Engineering and Architecture, Ghent University, Zwijnaarde, Belgium;6. Research group IMEC-MICT-Ghent University, De Krook, Miriam Makebaplein, Ghent, Belgium