Multi-dimensional Dataset of Stress Measurements based on Performance, Behavioural, and Perceptual Indicators

The role of humans in industry is changing due to the technological transformation of production processes, which represents a potential source of stress for workers. In this context, the NO-STRESS project aims to combine objective and subjective data collected during task execution to explore causes of work-related stress and propose solutions to mitigate them. This paper describes the within-subjects study design used in the project, where each participant was exposed to all experimental conditions, and outlines the workflow developed during the study. Moreover, it describes the behavioural, performance and perceptual indicators of participants' stress collected during the execution of full-kitting, component quality control, assembly and product quality monitoring tasks. The data collection sessions were conducted in different manufacturing contexts. The collected data may be reused to compare stress intensity among different subjects considering individual factors and experimental conditions. In addition, the results of stress in manufacturing may be compared to the intensity of this phenomenon in other sectors. The consequent outcomes may have practical implications for work contexts and benefits for society as a whole.

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Publication Details

Journal
Scientific Data
Published
2024-12-18
DOI
https://doi.org/10.1038/s41597-024-04165-4
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

Multi-dimensional Dataset of Stress Measurements based on Performance, Behavioural, and Perceptual Indicators

Ganix Lasa, Abdullah Al Noman, Francesca Montagna, Graziana Blandino et al.
Scientific Data
Digital Transformation in Industry
article

Multi-dimensional Dataset of Stress Measurements based on Performance, Behavioural, and Perceptual Indicators

Ganix Lasa, Abdullah Al Noman, Francesca Montagna, Graziana Blandino, Ainhoa Apraiz, Hien Ngoc Nguyen, Ali Tarhini, Pedro Pratas
article en

Abstract

The role of humans in industry is changing due to the technological transformation of production processes, which represents a potential source of stress for workers. In this context, the NO-STRESS project aims to combine objective and subjective data collected during task execution to explore causes of work-related stress and propose solutions to mitigate them. This paper describes the within-subjects study design used in the project, where each participant was exposed to all experimental conditions, and outlines the workflow developed during the study. Moreover, it describes the behavioural, performance and perceptual indicators of participants' stress collected during the execution of full-kitting, component quality control, assembly and product quality monitoring tasks. The data collection sessions were conducted in different manufacturing contexts. The collected data may be reused to compare stress intensity among different subjects considering individual factors and experimental conditions. In addition, the results of stress in manufacturing may be compared to the intensity of this phenomenon in other sectors. The consequent outcomes may have practical implications for work contexts and benefits for society as a whole.

Scientific DataVol. 11(1)
Institut polytechnique de Grenoble (FR), Mondragon Unibertsitatea (ES), Politecnico di Torino (IT), University of Bremen (DE), Institute of Mechanical Engineering and Industrial Mangement (PT), Université Grenoble Alpes (FR)
Openalex Percentile: Top 66%
Digital Transformation in Industry
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