Quantifying Cognitive Workload Using a Non-Contact Magnetocardiography (MCG) Wearable Sensor

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 23; p. 9115
• Main Authors: Wang, Zitong, Zhu, Keren, Kaur, Archana, Recker, Robyn, Yang, Jingzhen, Kiourti, Asimina
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24.11.2022; MDPI
• Subjects: Accuracy; Body mass index; Cognition - physiology; cognitive workload classification; Digital signal processors; Electrocardiography; Electrodes; Electroencephalography; Evaluation; Heart; Heart beat; Heart Rate - physiology; heart rate variability; Humans; Machine learning; Magnetic fields; Magnetocardiography; Portable computers; Sensors; Signal processing; Signal Processing, Computer-Assisted; Skin; wearable and non-shielded sensor; Workload; Workloads; cognitive workload classification; heart rate variability; magnetocardiography; wearable and non-shielded sensor

Quantifying cognitive workload, i.e., the level of mental effort put forth by an individual in response to a cognitive task, is relevant for healthcare, training and gaming applications. However, there is currently no technology available that can readily and reliably quantify the cognitive workload...