Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106610
Title: Evaluation of sweat-based biomarkers using wearable biosensors for monitoring stress and fatigue : a systematic review
Authors: Ma, J 
Li, H 
Anwer, S 
Umer, W
Antwi-Afari, MF
Xiao, EB 
Issue Date: 2024
Source: International journal of occupational safety and ergonomics, Published online: 06 Apr 2024, Latest Articles, https://doi.org/10.1080/10803548.2024.2330242
Abstract: Objectives. This systematic review aims to report the evaluation of wearable biosensors for the real-time measurement of stress and fatigue using sweat biomarkers. Methods. A thorough search of the literature was carried out in databases such as PubMed, Web of Science and IEEE. A three-step approach for selecting research articles was developed and implemented. Results. Based on a systematic search, a total of 17 articles were included in this review. Lactate, cortisol, glucose and electrolytes were identified as sweat biomarkers. Sweat-based biomarkers are frequently monitored in real time using potentiometric and amperometric biosensors. Wearable biosensors such as an epidermal patch or a sweatband have been widely validated in scientific literature. Conclusions. Sweat is an important biofluid for monitoring general health, including stress and fatigue. It is becoming increasingly common to use biosensors that can measure a wide range of sweat biomarkers to detect fatigue during high-intensity work. Even though wearable biosensors have been validated for monitoring various sweat biomarkers, such biomarkers can only be used to assess stress and fatigue indirectly. In general, this study may serve as a driving force for academics and practitioners to broaden the use of wearable biosensors for the real-time assessment of stress and fatigue.
Keywords: Biomarkers
Cortisol
Fatigue
Lactate
Stress
Sweat analysis
Publisher: Taylor & Francis
Journal: International journal of occupational safety and ergonomics 
ISSN: 1080-3548
EISSN: 2376-9130
DOI: 10.1080/10803548.2024.2330242
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