A highly-wearable single–channel instrument, conceived with off-the-shelf components and dry electrodes, is proposed for detecting human stress in real time by electroencephalography (EEG). The instrument exploits EEG robustness to movement artifacts with respect to other biosignals for stress assessment. The single-channel differential measurement aims at analyzing the frontal asymmetry, a well-claimed EEG feature for stress assessment. The instrument was characterized metrologically on human subjects. As triple metrological references, standardized stress tests, observational questionnaires given by psychologists, and performance measurements were exploited. Four standard machine learning classifiers (SVM, k-NN, Random Forest, and ANN), trained on 50% of the data set, reached more than 90% accuracy in classifying each 2-s epoch of EEG acquired from stressed subjects.

One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are a number of well established systems that offer adequate solutions for real-time, continuous patient monitoring. On the other hand, monitoring skin hydration still remains a challenging task. The continuous monitoring of this physiological parameter is extremely important in several contexts, for example for athletes, sick people, workers in hostile environments or for the elderly. State-of-the-art systems, however, exhibit some limitations, especially related with the possibility of continuous, real-time monitoring. Starting from these considerations, in this work, the feasibility of an innovative time-domain reflectometry (TDR)-based wearable, skin hydration sensing system for real-time, continuous monitoring of skin hydration level was investigated. The applicability of the proposed system was demonstrated, first, through experimental tests on reference substances, then, directly on human skin. The obtained results demonstrate the TDR technique and the proposed system holds unexplored potential for the aforementioned purposes.

In spite of the technological advancement of the healthcare system, monitoring skin hydration still remains a challenging task. In particular, the state-of-the-art solutions are inadequate to obtain continuous real-time monitoring, especially in a wearable perspective. Starting from these considerations, this article addresses the implementation of an innovative wearable device that can monitor skin hydration through microwave reflectometry technique. To this purpose, a new flexible wearable sensing element (SE) was designed, manufactured, and validated to sense variation of skin hydration of the body, ensuring simultaneously a better wearability, and surface adherence to the skin. The system was preliminarily validated through a numerical analysis and then experimental tests were carried out through a low-cost portable vector network analyzer (VNA), which is particularly convenient in view of fully-wearable applications and comparable, from the metrological point of view to more expensive VNAs operating in the frequency range of interest. Results showed that the proposed SE configuration and the low-cost VNA hold potential for achieving a fully-wearable system for monitoring skin hydration.

Brain-Computer Interfaces (BCIs) are an integration of hardware and software communication systems that allow a direct communication path between the human brain and external devices. Among the existing BCI paradigms, Steady-State Visually Evoked Potentials (SSVEPs) have gained momentum in the development of non-invasive BCI applications as they are characterized by adequate signal-to-noise ratio and information transfer rate. In recent years, the adoption of Augmented Reality (AR) head-mounted displays to render the flickering stimuli necessary for SSVEPs elicitation has become an attractive alternative to traditional computer screens. In fact, the increase in system wearability anticipates the possibility of adopting BCIs in contexts other than research laboratory. This has contributed to a steadily-increasing interest in BCIs, as also confirmed by the recent literature dedicated to the topic. In this evolving scenario, this review intends to provide a comprehensive picture of the current state-of-the-art in relation to the latest advancement of wearable BCIs based on SSVEPs classification and AR technology. The goal is to provide the reader with a systematic comparison of different technological solutions realized over the last years, thus making future research in this direction more efficient.

The most effective expression of the 4.0 Era is represented by cyber-physical systems (CPSs). Historically, measurement and monitoring systems (MMSs) have been an essential part of CPSs; however, by introducing the 4.0 enabling technologies into MMSs, a MMS can evolve into a cyber-physical measurement system (CPMS). Starting from this consideration, this work reports a preliminary case study of a CPMS, namely an innovative robotic platform to be used for measurement systems in confined and constrained remote environments. The innovative system is a soft growing robot composed of a robot base, to be placed outside the remote environments and a robot body that accesses the site through growth. A pneumatic actuation mechanism enables the controllable growth of the system through lengthening at its tip, as well as its controllable steering. The system can be endowed with sensors to enable remote measurement and monitoring tasks, or can be used to transport sensors in remote locations. A digital twin of the system is developed for simulation of a practical measurement scenario. The ultimate goal is to achieve a self-adapting, fully autonomous system for remote monitoring operations to be used reliably and safely for the inspection of unknown and/or constrained environments.

Measurement and monitoring systems (MMSs) are intrinsically part of 4.0 and, in particular, of cyber-physical systems (CPSs). However, by introducing the 4.0 enabling technologies into MMSs, also the vice versa can be accomplished, and MMSs can evolve into a cyber-physical measurement system (CPMS). Starting from this consideration, in the present work, a preliminary case study of a CPMS is presented: an innovative robotic platform to be used for measurement systems in confined and constrained remote environments. The proposed system is a soft growing robot that includes a robot base, to be placed outside the remote environments, and a robot body that accesses the site through growth. A pneumatic actuation mechanism enables the controllable growth of the system (through lengthening at its tip), as well as its controllable steering. The system can be equipped with sensors to enable remote monitoring tasks, or can be used to transport sensors in remote locations. The ultimate goal is to achieve a self-adapting, fully-autonomous, reliable and safe system for monitoring applications, particularly useful for the remote inspection of unknown and/or constrained environments.