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Dataset provides cardiovascular and ocular signals from workers during assembly tasks, enabling better industrial well-being solutions.
<ns5:p>Workers in manufacturing environments are frequently exposed to demanding working conditions that can affect both their performance and overall well-being. However, due to the challenges associated with collecting high-quality physiological data in real industrial settings, publicly available datasets remain scarce, limiting the development of human-centric and affective computing applications for manufacturing. To address this gap, this work presents a dataset of workers’ cardiovascular and ocular signals collected while performing operations in a semi-automated assembly line at the facilities of Silverline Endustri Ve Ticaret A.S. (Silverline). The assembly line is composed of a human-robot cooperative workstation and a manual workstation where operators perform quality control and packaging operations. The dataset contains over 9 hours of cardiovascular and ocular measurements from four operators, linked to assembly operations. By making this dataset publicly available, the authors aim to facilitate access to physiological data for the development of human-centric industrial solutions that support workers’ well-being and advance affective computing research in manufacturing.</ns5:p>
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Eyam et al. (2026) studied this question.
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