Real-time mental workload assessment with low intrusiveness for assembly processes: Limits and preliminary results

Real-time mental workload assessment with low intrusiveness for assembly processes: Limits and preliminary results

Riccardo GERVASI, Matteo DE MARCHI, Luca MASTROGIACOMO, Dominik T. MATT, Fiorenzo FRANCESCHINI

Abstract. The real-time assessment of mental workload emerges as crucial in Industry 5.0 for optimizing human performance and wellbeing when interacting with complex systems. However, balancing diagnosticity and sensitivity with low intrusiveness in such assessments remains challenging. According to ISO 10075, mental workload is a broad concept encompassing several observable phenomena (e.g., monotony and mental fatigue), each requiring special attention. This paper explores current techniques for real-time assessment of mental workload in manufacturing and presents preliminary results from a case study in an assembly line. The case study integrates physiological metrics (i.e., heart rate variability, electrodermal activity, and eye-tracking) collected by non-invasive biosensors with task performance metrics to highlight benefits and limitations of a low intrusive real-time assessment setup. The need to use more metrics to reliably identify the operator’s psychophysical state is also highlighted.

Keywords
Human Aspects, Monitoring, Quality Engineering

Published online 9/10/2025, 9 pages
Copyright © 2025 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Riccardo GERVASI, Matteo DE MARCHI, Luca MASTROGIACOMO, Dominik T. MATT, Fiorenzo FRANCESCHINI, Real-time mental workload assessment with low intrusiveness for assembly processes: Limits and preliminary results, Materials Research Proceedings, Vol. 57, pp 47-55, 2025

DOI: https://doi.org/10.21741/9781644903735-6

The article was published as article 6 of the book Italian Manufacturing Association Conference

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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