Assessing mental workload with wearable devices – Reliability and applicability of heart rate and motion measurements. (November 2022)

• Record Type: Journal Article
• Authors: Mach, Sebastian; Storozynski, Pamela; Halama, Josephine; Krems, Josef F.
• Is Part Of: Applied ergonomics. Volume 105(2022)
• Publication Date: 2022-11
• Subjects: Workload assessment -- Wearable devices -- Validation; Human engineering -- Periodicals; 620.82
• DOI: 10.1016/j.apergo.2022.103855
• Languages: English
• ISSNs: 0003-6870

Abstract

Abstract: Wearable devices are increasingly used for assessing physiological data. Industry 4.0 aims to achieve the real-time assessment of the workers' condition to adapt processes including the current mental workload. Mental workload can be assessed via physiological data. This paper researches the potential of wearable devices for mental workload assessment by utilizing heart rate and motion data collected with a smartwatch. A laboratory study was conducted with four levels of mental workload, ranging from none to high and during sitting and stepping activities. When sitting, a difference in the heart rate and motion data from the smartwatch was only found between no mental workload and any mental workload task. For the stepping condition, differences were found for the movement data. Based on these results, wearable devices could be useful in the future for detecting whether a mental demanding task is currently performed during low levels of physical activity. Highlights: Wearable devices assess heart rate accurately in absence of physical activity. Heart rate data of wearable devices detect the presence of mental demanding task. arm motion data for detection of mental workload was investigated. arm motion indicates the presence of a mental demanding task.