Eros Pasero of Politecnico of Turin

Medicine today has the availability of advanced technologies and new devices for diagnosis. Telemedicine gives a new scenario that allows remote diagnosis, control and treatment of patients at home without physical contact with the doctor. Routine checkups can be outsourced to small care facilities or even to the patient's own home. In Europe the elderly are more than the young but the funds for the health system are decreasing. The medicine paradigm must be rethought. E-Health can be the solution to support for the delocalization of some medical services: new micro and nano electronic circuits, IOT for pervasive and efficient communication, Artificial Intelligence to solve problems where models are not easy to apply but a lot of data is available. The ability to combine the power of AI algorithms and data from different sensors and databases can greatly increase the reliability of the final choice of the right therapy. This is the new Medicine 4.0. The digitalization of the processes and the improvement of technology allow interfacing the human body with computers and Artificial Intelligence allows you to work with a large amount of data (big data) and identify unknown correlations between the parameters to allow a new diagnosis. Several new perspectives will be discussed in this presentation.

• Telemedicine: Difficult, diverse and vast geographical areas are important factors for poor access to healthcare systems. Even in wealthy countries people have to travel up to 100 km to reach a health facility. A smartphone, wearable devices, smart sensors can solve this problem without any transfer. Technology does not replace a doctor but is an answer for an objective need that the patient can directly request. The de-localization of the medical services is the answer to this problem.
• E-Health: correct and rapid measurement can be crucial in many cases. ECG showing heart disease (e.g. atrial fibrillation) can be a life-saving indication.
• Electronic Health Record (HER): the ability to store and share medical data between the Physician located, for example in New York, a specialist in Chicago and the patient on vacation in Mexico is a new reality. Great advantages but also great challenges to find what information to store in order not to have big unnecessary records.
• Artificial Intelligence: these algorithms can be used for advanced diagnostic systems. In a hospital intensive care unit, for example, a patient is connected to advanced medical equipment that can measure many parameters giving beeps and rings when they are outside the normal parameters. Too many parameters for a single therapist and too many patients for a team. All this information can be managed by AI systems that can keep the patient in optimal condition.
• Artificial Intelligence models: Mathematical models of human parameters are often not usable but data measured under disease conditions are often available. AI systems can use these data to predict other parameters without using models. We’ll see how ECG and PPG can give blood pressure with better precision than a sphygmomanometer using an Artificial Neural Network.

We will investigate both new technologies showing wearable devices that can be used both to monitor patients at home (this topic was very important with the Covid 19) and Artificial Intelligence applied to medical image processing to perform remote diagnoses (once again used to distinguish pneumonia from lung problems due to Covid 19).

After this difficult period Medicine 4.0 will change several aspects of the interface between doctors and patients by improving the performance of national health services and reducing unnecessary costs. The future will provide a new digital hospital and a comprehensive monitoring system that integrates the interface between patients and hospitals.

Biography:

Eros G. Pasero is Professor of Electronics at the Politecnico of Turin since 1991 after a four year appointment as Professor at the University of Roma, Electronics Engineering. He was also Visiting Professor at ICSI, UC Berkeley, CA in 1991, Professor of digital electronics and electronic systems at Tongji University, Shanghai, China in 2011, 2015 and 2017, and Professor of digital electronics and electronic systems at TTPU (Turin Tashkent Politechnic University), Tashkent, Uzbekistan since 2012 to 2014 where he was also vice rector in the first period of 2014.

Prof. Pasero established in 1990 the Neuronica Lab where hardware and software neurons and synapses are studied practical applications; innovative wired and wireless sensors are also developed for biomedical, environmental, and automotive applications. Data coming from sensors are post processed by means of artificial neural networks.

Prof. Pasero is now the President of SIREN, the Italian Society for Neural Networks; he was v. General Chairman of IJCNN2000 in Como, General Chairman of SIRWEC2006 in Turin, general Chairman of WIRN2015, WIRN2016 and WIRN2017, WIRN 2018 and WIRN 2019 in Vietri. He holds 6 international patents (two were the first silicon European neurons and synapse together Texas Instruments). He was supervisor of tenths of international Ph.D and hundredths of Master students and he is author of more than 100 international publications.

Together his group he was awarded with the 1982 CILEA-Sperry award for complex application systems and local distributed architecture”, with the ASSIPE Design-In-Award in 2003 and 2004, with premio "Innova S@alute2017" at the “forum dell'innovazione per la salute” on September 2017; he was IEEE key note speaker at 2014 Symposium series on Computational Intelligence in Orlando, Fl, USA; Distinguished Lecturer of the 2016 IEEE Medical Information Summer School, Distinguished Lecturer of the 2017 IEEE school "Smarter Engineering for Industry 4.0"

Email:

Address:Politecnico of Turin, , Turin, Italy