Open challenges and future perspectives on stress-related emotions monitoring via smart wearables: A systematic literature review

Abstract

Wearable technology-empowered and Internet of Things (IoT)-based sensors are becoming attractive instruments for mental health monitoring on eHealth platforms. The detection of stress-related emotions, including anxiety and depression, is a rapidly developing research area due to the overlapping symptoms of these emotions and their significant impact on mental well-being. Al- though Machine Learning (ML) and consumer-grade wearables have improved emotion recognition, significant challenges in developing reliable, real-time monitoring systems for everyday use still remain. This Systematic Literature Review (SLR) aims to provide an overview of the types of wearables used, combinations of multimodal data collected on stress-related emotions, ML-based data processing techniques, and the key technical challenges and solutions reported in the literature. The review was conducted and reported following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 framework to ensure methodological transparency and reproducibility of the systematic review process. Altogether 34 articles were selected for the evaluation, with findings synthesized through narrative and thematic approaches to identify recurring patterns across wearable technologies, sensing modalities, and stress-monitoring approaches. Key trends are highlighted, including the integration of multimodal measurements and the exploration of various ML techniques. However, transitioning from controlled environments to real-world settings introduces remaining challenges, such as variability in user behaviors, environmental factors, and limitations of wearable devices. Two critical trade-offs are identified: balancing data collection with device battery usage and compromising between the performance of complex algorithms and effective situation assessment. This SLR provides insights into future research directions while addressing the unresolved challenges in the field.