Mach Sebastian, Storozynski Pamela, Halama Josephine, Krems Josef F
Research Group Cognitive and Engineering Psychology, Chemnitz University of Technology, Germany.
Research Group Cognitive and Engineering Psychology, Chemnitz University of Technology, Germany.
Appl Ergon. 2022 Nov;105:103855. doi: 10.1016/j.apergo.2022.103855. Epub 2022 Aug 10.
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.
可穿戴设备越来越多地用于评估生理数据。工业4.0旨在实现对工人状况的实时评估,以调整包括当前心理负荷在内的流程。心理负荷可以通过生理数据进行评估。本文通过利用智能手表收集的心率和运动数据,研究了可穿戴设备在心理负荷评估方面的潜力。进行了一项实验室研究,设置了四个心理负荷水平,从无到高,涵盖坐着和行走活动。坐着时,仅在无心理负荷和任何心理负荷任务之间发现了智能手表的心率和运动数据存在差异。对于行走状态,在运动数据方面发现了差异。基于这些结果,可穿戴设备未来可能有助于检测在低水平身体活动期间是否正在执行需要脑力的任务。