Special Sessions

The integration of wearable sensors and artificial intelligence reached a great popularity in several research fields, including clinical applications. In fact, sensor- and AI-based methods can be used as advanced clinical decision support systems to help decision-makers and healthcare systems to improve how they approach information, insights, and the surrounding contexts, as well as to promote the uptake of personalized medicine on an individualized basis. 

Over the last decade, the growing demand for micro- and nano-sensors and devices presents unprecedented opportunities and challenges to improve the quality of life. Nanomaterials-based sensors and devices have attracted intensive interest among researchers and scientists worldwide due to their exceptional physical, mechanical, biological, chemical, and electrical properties. Among the most widely used materials are nanoparticles, nanofibers, including carbon nanotubes, and 2D materials such as graphene. 

Healthcare 4.0 extends the concept of Industry 4.0 in a scenario where patients and healthcare professionals are strictly correlated with the organization, the methodology and the technology. A patient-oriented system based on data sharing amongst the varied players can lead to improved healthcare delivery. 

This Special Session intends to encourage submission of original research papers concerning models, data processing and decisional algorithms based on measurement data for diagnostic purpose. Nowadays, models and decision-making algorithms are widely used for diagnosing or taking a decision on patient’s health status. Such models and algorithms are based on signals and data referring to patient’s vital signs or bio-signals, subsequently, diagnoses and decisions are taken.

The rapid advancements in integrated circuit technology and sensing techniques have made the widespread use of sensor instruments possible in different fields of modern biomedical engineering, as application in health science, clinical and experimental medicine, pharmacology and proteomics, including (but are not limited to) system control, measurement and monitoring devices, and micro and nanotechnology. 

Wearables are gaining broad interest and are becoming popular in a wide range of biomedical applications, from the monitoring of physiological signs to human activities and habits. The knowledge of these parameters may be useful in a variety of applications, among others telemonitoring, telecare, rehabilitation, well-being assessment, sport sciences, workers’ safety. A crucial aspect is the design, the metrological characterization and validation of sensors and wearable devices, to obtain high quality data and extract useful features for developing models that can really support decision-making processes.

Healthcare and sport science domains are increasingly taking advantage of unobtrusive sensing solutions that provide unprecedented possibilities for real-time monitoring of the health status. Sweat is an attractive biofluid for unobtrusive monitoring as it is easily accessible and rich of biochemical information including electrolytes, metabolites, proteins, hormones, and nucleic acid.