Lecture Series

Chemical sensors for biomedical applications

Abstract

The availability of effective, low-cost and non-invasive diagnostic instrumentation is extremely important in the biomedical field due to the growing necessity of quick and effortless early diagnosis of several pathologies. In this framework, chemical sensors represent a safe and virtually non-invasive way to assess the presence of a pathology by detecting abnormal concentrations of specified biomarkers. The lecture will firstly give a brief summary of the sensing technologies currently employed in the biomedical field. Then, the discussion will focus on the metal-oxide conductometric gas sensors, introducing their basic sensing principles and discussing their advantages and drawbacks. Finally, some practical case study will be presented including details on sensor manufacturing and the metrological characterization of its sensing performance.

Biosketch

Luca Lombardo (Member, IEEE) was born in Italy, in 1986. He received the B.D. and M.S. degrees in Electronic Engineering from the University of Messina, Messina (Italy), in 2014 and 2016, respectively. He received the Ph.D. degree in Metrology in 2019 from Politecnico di Torino, Torino (Italy). Currently, he is research fellow with the Department of Electronics and Telecommunications at Politecnico di Torino, Torino (Italy). His research interests include the development and the characterization of innovative sensors, embedded systems and instrumentation in the fields of environmental monitoring, biomedical and metrological applications.

Past Events

Chemical and biochemical sensing meet optics: a successful marriage in biomedical applications

Fiber Optic Sensors

Abstract

Optics play a fundamental role in the development of biosensors for medical applications. In recent years, the demand from doctors has grown enormously for devices capable of measuring chemical and biochemical parameters of clinical interest in a reasonably short time and sufficiently compact, or better transportable, to be placed near the patient’s bed. In the case of necessity, the use of optical fibers can also lead to invasive continuous measurements within the human body, thanks to their invasive capabilities and unique performance that have allowed measurements inside the human body otherwise impracticable. A view from the past to the future will be given with particular attention to the new trends.

Biosketch

Francesco Baldini graduated in physics from the University of Florence magna cum laude in 1986. He joined immediately the Institute of Electromagnetic Wave of CNR in Florence (now named Institute of Applied Physics). His activity has been mainly devoted to the development of optical platforms and sensors for chemical and biochemical sensing. He is author of more than 200 publications in International Journals and delivered plenary and invited talks at many international conferences. He is/was responsible of many international and national projects in the field and in 2009 he was nominated fellow of SPIE for “his achievements in biological and chemical sensing in biomedicine”. He was President of the Italian Society of Optics and Photonics for the biennium 2015-2016

Wearable sensors for cardiovascular monitoring

Wearable Sensors

Abstract

One of the most popular wearable devices is a pulse rate (PR) monitor using photoplethysmography (PPG), which was first introduced in the late 1930s as an optical and non-invasive method used to detect volume changes in blood vessels. PPG provides information on the cardiovascular system, particularly pulse and respiratory rates. Currently, cardiovascular disease is the most morbidity-related disease following cancer. Blood pressure plays an especially important role in maintaining health. Applying PPG technology, cuffless blood pressure monitor has been attempted worldwide because of its wearability, easy to handle and low cost. In this presentation the wearable cardiovascular monitors are reviewed, and possibility of clinical practice are discussed.

Biosketch

Dr. Toshiyo Tamura (S75-M81-SML15) received his Ph.D. from Tokyo Medical and Dental University in 1980. He is currently a Visiting Professor, Future Robotics Organization, Waseda University, Japan. His research interests include biomedical instrumentation, biosignal processing, telemedicine telecare, home care technology and rehabilitation engineering. His and his colleagues’ book entitled “Biomedical sensors and instruments” and “Seamless healthcare monitoring” are popular textbooks for bioinstrumentation and medical devices. He also wrote several chapters including sensors for telemedicine and application of wearable inertia sensors. He has served as a chair of the Asian Pacific representative for the IEEE/EMBS from 2000 to 2004. He is fellows of IAMBE and Japanese Society of Medical Electronics and Biological Engineering.

Characterizing deeply quantized neural networks for in-sensor computing

Smart Sensors and Edge Computing

Abstract

Balancing storage and computing capabilities, accuracy, anomaly detection and modelling design is a real challenge when implementing Artificial Neural Networks on ultra-low power devices such as microcontrollers. Deeply Quantized Neural Networks (DQNNs) offer the most promising solution to these requirements, however, current state-of-the-art microcontrollers are not yet able to exploit its advantages. The design of custom energy efficient hardware accelerators therefore represents the most viable approach in terms of energy efficiency, especially with respect to in-sensing neural computing. The result is a novel quantized Neural Network model, or Hybrid Neural Network, able to achieve accuracies as high as 99% when classifying daily human activities from MEMS inertial sensors. Its custom ultra-low power hardware circuitry for the real-time execution of the Hybrid Neural Network is presented with CMOS technologies and implemented with a Field-programmable gate array, including associated demo.

Biosketch

One year before graduating from the Polytechnic University of Milan in 1992, Danilo PAU joined STMicroelectronics, where he worked on HDMAC and MPEG2 video memory reduction, video coding, embedded graphics, and computer vision. Today, his work focuses on developing solutions for deep learning tools and applications. Since 2019 Danilo is an IEEE Fellow, serves as Industry Ambassador coordinator for IEEE Region 8 South Europe and Member of the Machine Learning, Deep Learning and AI in the CE (MDA) Technical Stream Committee IEEE Consumer Electronics Society (CESoc). With over 80 patents, 100 publications, 113 MPEG authored documents and 37 invited talks/seminars at various worldwide Universities and Conferences, Danilo’s favorite activity remains mentoring undergraduate students, MSc engineers and PhD students from various universities in Italy, US, France and India.

Radar Old but Gold: current research challenges and activities in radar micro-Doppler signatures

Microwave and Millimeter-Wave Radar Sensors

Abstract

The concept and characterisation of radar micro-Doppler signatures have been around for some time in the research community, but they remain powerful source of information that can be exploited for many applications under the framework of radar-based target recognition. Advances in computational capabilities and in algorithms that enhance the intelligence of the radar system have recently refuelled interest in micro-Doppler signatures, or more in general in radar data used as all kinds of inputs to machine learning and deep learning algorithms. The talk aims to provide a quick introduction to micro-Doppler signatures and present examples of techniques that use them in several applications, mostly for the characterisation of human movements and drones.

Biosketch

Francesco graduated in Telecomm Engineering (summa cum laude) at the Università Politecnica delle Marche, Ancona, Italy for his Bachelor (2007) and Master (2010). He received his PhD on through-wall radar imaging at Durham University, UK, in January 2014. He then worked as a Research Associate on multistatic radar at University College London between February 2014 and March 2016, and as a Lecturer at the University of Glasgow between April 2016 and October 2019, where he established the radar research theme (5 PhD students, 2 PDRAs, about £550k of funding) in collaboration with Dr Julien Le Kernec, within the Communication, Sensing & Imaging (CSI) group led by Prof Muhammad Imran. He is currently an Assistant Professor at TU Delft in the MS3 (Microwave Sensing Signals & Systems) section led by Prof Alexander Yarovoy, where he is daily supervisor of 6 PhD candidates for a project portfolio of over €1M. Francesco is a Senior Member of the IEEE, member of the IET, Chartered Engineer (CEng), Fellow of the UK Higher Education Academy (FHEA), a reviewer for a number academic journals and funding bodies, and author of over 100 publications including the recent edited book on “Micro-Doppler Radar and Its Applications” published by IET-Scitech in 2020.