IEEE Italy Sensors Chapter

Nowadays we are assisting to the fourth industrial revolution. This was the main theme of the World Economy Forum 2016 (WeF), the worldwide foundation organizes each year in Davos a symposium where the main political and economic leaders in the World discuss about the emerging trends of economy, technology, environment and health. The title of the last event was “Mastering the Fourth Industrial Revolution”, the summit launched an alarm: until 2020 at least 5 million of work positions will be lost in the world because they will be substituted by robots and artificial intelligence. The report “The Future of Jobs” published by the WeF, highlights that we are assisting to the fourth industrial revolution that implies evolutions and developments in fields, such as artificial intelligence, machine-learning, robotic, nanotechnologies 3D Printer, genetics and biotechnologies. This revolution will determine a wide disruption not only of field of business models but also in the job market as highlighted by the responsible of the human resources of 350 among the most important factories in world representing 13 millions of employers located in 15 of the most important Countries in the world such as China, India, France, Germany, UK and USA. According to the same analysis the emerging job sectors of the fourth revolution that are (i) Energy, (ii) Financial Services, (iii) Health, (iv) ICT, (v) Media & Entertainment, and (vi) Logistic. All these changes are possible also thank to the recent developments in the field of metrology. As a matter of fact, monitoring remote physical phenomena and try to control them, it is possible thank to the developments of new sensors, acquisition techniques, improve data acquisition systems, and so on.

Andrea Nicolò, PhD Department of Movement Human and Health Sciences, University of Rome “Foro Italico”   Abstract Technological development is helping athletes and exercise practitioners optimize performance and minimize the risk of injury and illness. Yet, monitoring exercise is challenging due to several factors, including motion artefacts and the need to minimize the invasiveness of wearable devices. The challenge is even greater when attempting to extract simple and useful information from a myriad of data that are currently gathered during training and competitions. Furthermore, most sensors and devices currently used in sports have not been scientifically validated. Moreover, technological development is often guided by market forces rather than athlete or scientific needs, which may reduce the use of new technologies. A good example of how the development of wearable sensors should follow athletes’ needs and be informed by scientific findings is given by the increasing attention devoted to respiratory frequency (fR) monitoring during exercise. Substantial evidence suggests that fR plays an important role during exercise as a strong marker of physical effort, more so than other traditionally monitored physiological variables such as oxygen uptake, heart rate and blood lactate. Indeed, fR is closely linked with perceived exertion during a variety of exercise paradigms and experimental interventions affecting performance, including muscle fatigue, glycogen depletion, hyperthermia and hypoxia. Therefore, fR is sensitive to different fatigue states, and thus presents potentially important implications for training and recovery monitoring. Furthermore, fR is a good predictor of time to exhaustion during constant-work rate exercise and can help understand how effort is distributed during self-paced time trials. Moreover, monitoring fR may not only benefit endurance sports but also team sports and other intermittent-based sporting activities, given the very fast response observed to abrupt changes in work rate. However, the importance of fR as a marker of physical effort has emerged from recent investigations and fR is not currently measured during training. Furthermore, there is a paucity of respiratory sensors specifically designed for sporting activities, which is very relevant for companies, researchers and sensor developers. The talk will present: i) current evidence suggesting the importance of respiratory frequency monitoring during exercise; ii) our current understanding of the mechanisms underlying the control of breathing during exercise; iii) currently available techniques and sensors for measuring respiratory frequency. Biography Andrea Nicolò received his BSc (2009), MSc (2011) and PhD in Sports, Exercise and Ergonomics (2015) from the University of Rome “Foro Italico”. He is currently a post-doc researcher at the University of Rome “Foro Italico”. His research focuses on endurance physiology and performance, with special attention to the mechanisms and practical applications underlying the control of breathing during exercise. He has worked for different research projects funded by major national and international sports companies, with the aim of developing new exercise tests and training metrics, and of validating training devices and algorithms. Details  

Lecturer.  Dr. Hugo TALBOT, PhD Abstract. As in many engineering sectors, numerical simulation has become invaluable, namely for medical education, therapy planning, and implant design. However, simulation softwares remain expensive and require a high level of expertise to be used correctly and effectively. SOFA (Software Open Framework Architecture) is an open-source framework primarily targeted at real-time simulation, with an emphasis on medical simulation. This innovative and collaborative tool is developed by a worldwide community of experts in physics simulations and gathers about 12 years of scientific research. Both academic and industrial developers create their own proprietary simulations based on SOFA, benefiting from its LGPL license. Many research centers actively work and publish using SOFA while five startups have been created for the last five years. This talk will present you SOFA, how to use it and the various fields of applications. Details