Comprehensive Systematic Literature Review on Cognitive Workload: Trends on Methods, Technologies, and Case Studies

Abstract

Cognitive workload (CWL) assessment has gained traction in Industry 4.0 and 5.0, where human-machine interactions are becoming more intricate. However, there is a lack of comprehensively addressed CWL assessment by considering methodologies, technologies, and case studies. The present work reviews 70 articles related to the CWL assessment. The review identifies five main methodologies for the CWL assessment: physiological measures (e.g. EEG, HRV, and eye-tracking), subjective evaluation (e.g. NASA-TLX), performance evaluation, cognitive load models, and multimodal approaches. The analysis shows an increasing trend towards multimodal approaches that combine subjective assessment methods with physiological measures obtained from electroencephalography, eye-tracking, and heart rate monitoring devices. Additionally, emerging technologies such as augmented reality and collaborative robots are increasingly considered in case studies that address the CWL assessment in current work environments. Results reveal significant advancements in physiological and multimodal assessment methods, particularly emphasising real-time monitoring capabilities and context-specific applications. Case studies underscore the key role of CWL management in assembly, maintenance, and construction tasks, demonstrating its impact on performance, safety, and adaptability in dynamic environments. This review establishes a framework for advancing CWL research by addressing methodological limitations and proposing future research directions, including the development of personalised, adaptive systems for real-time workload management.