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Development and validation of a behavioural video coding scheme for detecting mental workload in manual assembly
Bram B Van Acker1,2,3, Davy D Parmentier1, Peter D Conradie1,3
1Department of Industrial Systems and Product Design, Faculty of Engineering and Architecture, Ghent University, Zwijnaarde, Belgium.
Ergonomics
|August 20, 2020
Summary
We identified observable assembly behaviors like freezing and part rotations to measure mental workload (MWL) in Industry 4.0 settings. This offers a reliable, naturalistic alternative to current physiological measures for assessing operator cognitive load.
Area of Science:
- Human Factors and Ergonomics
- Industrial Engineering
- Cognitive Psychology
Background:
- Industry 4.0 workplaces demand high operator cognitive processing, increasing the need for reliable mental workload (MWL) measures.
- Current physiological measures like electroencephalography (EEG) lack field reliability.
- Ecologically valid, behavioral measures are needed to assess MWL in real-world industrial settings.
Purpose of the Study:
- To develop and validate a behavioral coding scheme for assessing high mental workload (MWL) in manual assembly tasks.
- To provide an alternative, ecologically valid method for measuring MWL in Industry 4.0 environments.
- To enable practitioners to identify and redesign critical assembly phases and researchers to triangulate MWL data.
Main Methods:
- Developed a behavioral video coding scheme identifying 11 assembly behaviors indicative of high MWL.
- Analyzed videos of 24 participants performing high and low complexity manual assembly tasks.
- Quantified the occurrence and duration of specific behaviors under different workload conditions.
Main Results:
- Five assembly behaviors, including freezing and part rotations, significantly differed between high and low complexity tasks.
- The identified behaviors demonstrated potential as indicators of elevated mental workload.
- The proposed behavioral coding scheme showed substantial ecological validity.
Conclusions:
- Observable assembly behaviors can serve as a reliable and naturalistic measure of mental workload (MWL).
- This method offers a practical approach for mapping and redesigning assembly processes to manage operator cognitive load.
- The findings support the use of behavioral observation for validating and complementing other MWL assessment techniques.
