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How to Assess Mental Workload Quick and Easy at Work: A Method Comparison

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Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) (IEA 2018)

Abstract

In context of Industry 4.0 and the ongoing digitalization, the industrial worker will still maintain a key role. Thereby, the needs and preferences of the workers shall be considered in real-time and the production process should automatically adapt to the worker. A suitable interface for human-automation interaction is needed to allow the worker to easily provide information regarding his/her physiological and psychological state. Using a smartwatch with implemented surveys for data assessment seems a promising solution. However, some studies found a significant difference when presenting the NASA-TLX on a monitor screen. The scores were higher than in the paper version. Thus, the first step should be to examine whether questionnaires presented on a smartwatch have the same outcome as presented on paper.

In a laboratory experiment, 29 participants performed a constant calculating task and, afterwards, filled out the NASA-TLX via paper or via smartwatch by using the bezel or the touchscreen.

The results show that the workload score in the paper version was significantly lower than the workload score in the smartwatch versions (bezel as well as touch). Nevertheless, the relative differences between the altered levels of difficulty of the arithmetic tasks could be equally well identified using the NASA-TLX scores assessed with the smartwatch version compared to the paper version.

In conclusion, the assessment via smartwatch can differentiate between different levels of mental workload and therefore qualifies for the application in the field. Especially for an industrial environment, the implementation of a smartwatch carries great potential.

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Mach, S., Gründling, J.P., Schmalfuß, F., Krems, J.F. (2019). How to Assess Mental Workload Quick and Easy at Work: A Method Comparison. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 825. Springer, Cham. https://doi.org/10.1007/978-3-319-96068-5_106

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