Background: Skin is a multilayer interface between the body and the environment, responsible for many important functions, such as temperature regulation, water transport, sensation, and protection from external triggers.Objectives: This paper provides an overview of principal factors that influence human skin and describes the diversity of skin characteristics, its causes and possible consequences. It also discusses limitations in the barrier function of the skin, describing mechanisms of absorption.Methods: There are a number of in vivo investigations focusing on the diversity of human skin characteristics with reference to barrier properties and body‐dependent factors.Results: Skin properties vary among individuals of different age, gender, ethnicity, and skin types. In addition, skin characteristics differ depending on the body site and can be influenced by the body‐mass index and lifestyle. Although one of the main functions of the skin is to act as a barrier, absorption of some substances remains possible.Conclusions: Various factors can alter human skin properties, which can be reflected in skin function and the quality of everyday life. Skin properties and function are strongly interlinked.

Background: For many applications in research, material development and testing, physical skin models are preferable to the use of human skin, because more reliable and reproducible results can be obtained.Purpose: This article gives an overview of materials applied to model physical properties of human skin to encourage multidisciplinary approaches for more realistic testing and improved understanding of skin–material interactions.Methods: The literature databases Web of Science, PubMed and Google Scholar were searched using the terms ‘skin model’, ‘skin phantom’, ‘skin equivalent’, ‘synthetic skin’, ‘skin substitute’, ‘artificial skin’, ‘skin replica’, and ‘skin model substrate.’ Articles addressing material developments or measurements that include the replication of skin properties or behaviour were analysed.Results: It was found that the most common materials used to simulate skin are liquid suspensions, gelatinous substances, elastomers, epoxy resins, metals and textiles. Nano‐ and micro‐fillers can be incorporated in the skin models to tune their physical properties.Conclusion: While numerous physical skin models have been reported, most developments are research field‐specific and based on trial‐and‐error methods. As the complexity of advanced measurement techniques increases, new interdisciplinary approaches are needed in future to achieve refined models which realistically simulate multiple properties of human skin.

Electrospinning evolved as a powerful technology to produce membranes consisting of nano- to micron-scaled fibers offering unique membrane properties due to the extremely high surface-to-volume ratio and high membrane porosity. However, this technology is often far removed from a green and environmentally-friendly process, as it employs solvents with issues such as high flammability, toxicity, difficult disposal, or energy-intensive synthesis. Indeed, the most commonly used solvents in the electrospinning field are halogenated (e.g. chloroform, trifluoroethanol) and toxic solvents (e.g. dimethylformamide), the use of which is now restricted by the Chemical Control Regulation in the European Union (REACH). This is especially important when considering the commercialization of electrospun products due to the more limited solvent choice. In order to render electrospinning more attractive as a commercial technique and further improve scalability, solvent alternatives and other green routes have to be established, which adhere to societal and legal restrictions especially in regard to the environmental and health impact. Therefore, this review provides the current ecological and economical context of this technology, and summarizes recent approaches towards green electrospinning. Since electrospinning from solutions and dispersions constitutes the predominantly used form of this technique both in research and industry, the focus of this work is set on the use of solvents or solvent mixtures classified exclusively by the term “green”. The approaches presented comprehensively cover the production of polymeric fibers via solution, emulsion, suspension, and in situ cross-linking electrospinning.

The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems represent highly promising solutions for fatigue monitoring as they enable continuous, long-term monitoring of biomedical signals in unattended settings, with the required comfort and non-intrusiveness. This is a p rerequisite for the development of accurate models for fatigue monitoring in real-time. However, monitoring fatigue through wearable devices imposes unique challenges. To provide an overview of the current state-of-the-art in monitoring variables associated with fatigue via wearables and to detect potential gaps and pitfalls in current knowledge, a systematic review was performed. The Scopus and PubMed databases were searched for articles published in English since 2015, having the terms “fatigue,” “drowsiness,” “vigilance,” or “alertness” in the title, and proposing wearable device-based systems for non-invasive fatigue quantification. Of the 612 retrieved articles, 60 satisfied the inclusion criteria. Included studies were mainly of short duration and conducted in laboratory settings. In general, researchers developed fatigue models based on motion (MOT), electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), galvanic skin response (GSR), electromyogram (EMG), skin temperature (T_sk), eye movement (EYE), and respiratory (RES) data acquired by wearable devices available in the market. Supervised machine learning models, and more specifically, binary classification models, are predominant among the proposed fatigue quantification approaches. These models were considered to perform very well in detecting fatigue, however, little effort was made to ensure the use of high-quality data during model development. Together, the findings of this review reveal that methodological limitations have hindered the generalizability and real-world applicability of most of the proposed fatigue models. Considerably more work is needed to fully explore the potential of wearables for fatigue quantification as well as to better understand the relationship between fatigue and changes in physiological variables.