| Keynote 1||October 13, 2022｜13:30-14:30|
In-Memory Sensing and Computing
Institute of Electrical and Micro Engineering, Engineering Faculty
EPFL, École Polytechnique Fédérale de Lausanne
The concept of in-Memory Computing is nowadays a well-established principle. Instead of separating the processing device by the memory units, as usually done in traditional von Neumann architectures, it proposes new architectures based on memory devices providing simultaneous computing. Indeed, this keynote speech proposes the new concept of in-Memory Sensing and Computing as a disruptive novel approach in edge-computing. This novel concept is here proposed as based on the fusion of three architectural functions: sensing, computing and memorizing. This novel concept is proposed by using a simple architecture based on a single-kind of devices simultaneously providing these three functions: the memristors. The proposed novel approach also provides a breakthrough in cancer diagnostics. If fact, the concept is here demonstrated by showing a well-known case in oncology: the estimation of the risk of prostate cancer based on the measure of Prostate Specific Antigen (PSA) and its Membrane isoform (PSMA). So, this keynote discusses the first-ever-reported direct computation of the cancer risk on cancer markers detected with memristive biosensors simultaneously with the computation and data storing. Memristive biosensors are quite a novelty emerged in literature with first publications starting from 2011. These new kind of devices are of interest for many reasons but especially for their excellent Limit-of-Detection, which is down to the attomolar-ranges in cancer markers detection. They are often fabricated on silicon nanowires and manufactured with standard lithographic processes. This means the whole architecture may be CMOS-based and the biosensors themselves can be physically microfabricated onto the same dye. Therefore, this keynote talk opens to an important new area of research and development: the possibility to build innovative circuits and systems providing simultaneous sensing, computing, and storing for true lab-on-a-chip applications.
Sandro Carrara (F’15) is an IEEE Fellow for his outstanding record of accomplishments in the field of design of nanoscale biological CMOS sensors. He is also the recipient of the IEEE Sensors Council Technical Achievement Award in 2016 for his leadership in the emerging area of co-design in Bio/Nano/CMOS interfaces. He is faculty at the EPFL in Lausanne (CH), former professor at the Universities of Genoa and Bologna (IT). He holds a PhD in Biochemistry and Biophysics from University of Padua (IT), a Master degree in Physics from University of Genoa (IT), and a diploma in Electronics from National Institute of Technology in Albenga (IT). Along his carrier, he published 7 books with prestigious publishers such as Springer/NATURE and Cambridge University Press. He has authored more than 340 publications and 15 patents. He is Editor-in-Chief of the IEEE Sensors Journal, the largest journal among 220 IEEE publications per topic, and Associate Editor of IEEE Transactions on Biomedical Circuits and Systems. He is a member of the IEEE Sensors Council and his Executive Committee. He was a member of the Board of Governors (BoG) of the Circuits And Systems IEEE Society (CASS). He has been appointed as IEEE Sensors Council Distinguished Lecturer for the years 2017-2019, and CASS Distinguished Lecturer for the years 2013-2014. His work received several international recognition as best-cited papers and best conference papers. He has been the General Chairman of the Conference IEEE BioCAS 2014, the premier worldwide international conference in the area of circuits and systems for biomedical applications, and he also was the General Chairman of the 16th Edition of IEEE International Symposium on Medical Measurements and Applications, IEEE MeMeA 2021.
|Keynote 2||October 14, 2022｜08:00-09:00|
SOCs Powering Intelligent Neuro-Modulation Biomedical Systems - Innovations and Challenges
Emeritus Chair Professor
Institute of Electronics, National Yang Ming Chiao Tung University
Closed-loop neuro-modulation has been proven as an adaptive and optimal treatment for a range of intractable neurological disorders or diseases like drug-resistant epilepsy, Parkinson’s diseases, chronic pain, dementia, etc. The biomedical systems realizing implantable closed-loop neuro-modulation have become a rapid growing and challenging research frontier. Enabled by CMOS IC technologies, the core circuits of implantable closed-loop neuro-modulation systems can be integrated together to form a SoC (System-on-Chip), instead of discrete components as in nowadays commercial products. Greatly powered by SoCs, the SoC-inside implantable neuro-modulation systems have the advantages of small size, low power dissipation, high speed, and high accuracy. This makes them more effective and efficient in closed-loop neuro-modulation.
Epilepsy is defined as a tendency to have recurrent seizures. Epileptic seizures are caused by a sudden burst of excess electrical activity in the brain. As the fourth most common neurological disorder, 70 million people have epilepsy worldwide and about 30% of them are intractable. It is quite feasible to use SoC-inside implantable closed-loop neuro-modulation systems on these patients to suppress epileptic seizures through electrical stimulation. An implantable CMOS closed-loop neuro-modulation system for epilepsy control has been developed since 2008. It consists of an extraocular chip and an intraocular SoC with rechargeable battery. Both are coupled by a pair of coils operated at 13.56 MHz for wireless power and bilateral data telemetry. The implantable SoC consists of ECoG (Electrocorticography) acquisition unit, biphasic CCS (Constant Current Stimulation) stimulators, BSP (Bio-signal Processor), power management unit, battery charger, and wireless telemetry circuits whereas the extraocular chip contains power amplifier, charging control circuits, and wireless telemetry circuits. The SoC-inside system detects patient’s ECoG and automatically generates stimulus current pulses to suppress epileptic seizures. The design and measurement results of innovative SoC design and whole closed-loop neuro-modulation system will be presented. The results of initial clinical trial will be described.
The on-going research on closed-loop DBS (Deep Brain Stimulation) SoC for Parkinson’s diseases will be highlighted. Finally, design challenges on circuits and systems for implantable neuro-modulation will be addressed. New discovery on dementia paving the road of neuro-modulation treatment will also discussed as a future perspective.
Dr. Chung-Yu Wu was born in 1950. He received the M.S. and Ph.D. degrees from the Department of Electronics Engineering, National Chiao Tung University, Hsinchu, Taiwan, R.O.C., in 1976 and 1980, respectively.
Since 1980, he has served as a consultant to high-tech industry and research organizations and has built up strong research collaborations with high-tech industries. From 1980 to 1983, he was an Associate Professor at National Chiao Tung University. During 1984 to 1986, he was a Visiting Associate Professor in the Department of Electrical Engineering, Portland State University, Portland, OR. Since 1987, he has been a Professor at National Chiao Tung University. From 1991 to 1995, he was rotated to serve as the Director of the Division of Engineering and Applied Science on the National Science Council, Taiwan. From 1996-1998, he was honored as the Centennial Honorary Chair Professor at National Chiao Tung University. He received the National Chair Professorship from Ministry of Education, 2015-2017. Currently, he is an Emeritus Chair Professor at National Yang Ming Chiao Tung University and Chairman/CTO of A-Neuron Electronic Corporation. He has published more than 300 technical papers in international transactions/journals and conferences. He also has 56 patents including 23 U.S. patents. His research interests are implantable biomedical integrated circuits and systems, intelligent bio-inspired sensor systems, RF/microwave communication integrated circuits, neural network, analog/mixed-signal integrated circuits, and nanoelectronics.
Dr. Wu is a member of Eta Kappa Nu and Phi Tau Phi Honorary Scholastic Societies. He was a recipient of IEEE Fellow Award in 1998, Third Millennium Medal in 2000, and the IEEE Life Fellow Award in 2020. In Taiwan, he received numerous research awards from Ministry of Education, National Science Council, and professional foundations.
|Keynote 3||October 15, 2022｜08:00-09:00|
Data Harmonization: An Imaging-driven Omics Database / Repository for Retrospective Understanding of COPD and Planning for Future Care
Percy K. and Vida L. W. Hudson Professor of Biomedical Engineering and Professor of Radiology (Physics)
Consistent imaging protocols will require normalization / harmonization of data sourced from multiple platforms, hospitals and vendors. AI has shown a remarkable ability to generalize and group / tease out patterns from high-dimensional data. Machine / deep learning algorithms should rely on mix-omics integration of imaging and physiological measures. There is an urgent need for new models of multi-modal transfer learning (e.g., understanding lung and heart functional interactions), and incremental learning as cohorts grow at an ever-faster face, combining data from states/countries.
We are in the process developing harmonization methods that are applied to COPD patient imaging data. This phenotyping could lead to a better retrospective understanding of COPD disease pathways and prepare for future management of pulmonary-derived chronic pathologies. In addition, there are significant new chronic pathologies expected in COVID survivors (cardiomyopathy, pulmonary aspergillosis, hemoglobin / iron deficiencies) in the longer term, which will be challenging to treat and / or recognize. The harmonized baseline data during acute phases of disease would help tremendously in our ability to understand the implications of these pathologies.
The proposed harmonization platform would include normalization across vendors, sites, possible variations in protocols and patient size. We describe AI based harmonization methods to leverage a large number of baseline scans from existing and ongoing studies for density measures, texture and later airway topology. During this initial phase, the Columbia cohort would harmonize 2,500 subjects in total, sampling in proportion five distinct cohorts. In the long term we aspire to develop data sharing tools, with possible partnerships for long term / global infrastructure and computing, integrate expertise in multiple imaging modalities, lead an open AI approach to model, predict and understand stages of pulmonary disease including COPD.
Andrew F. Laine received his D.Sc. degree from Washington University (St. Louis) School of Engineering and Applied Science in Computer Science, in 1989 and BS degree from Cornell University (Ithaca, NY). He was a Professor in the Department of Computer and Information Sciences and Engineering at the University of Florida (Gainesville, FL) from 1990-1997. He joined the Department of Biomedical Engineering in 1997 and served as Vice Chair of the Department of Biomedical Engineering at Columbia University since 2003 – 2011, and Chair of the Department of Biomedical Engineering (2012 – 2017). He is currently Director of the Heffner Biomedical Imaging at Columbia University and the Percy K. and Vida L. W. Hudson Professor of Biomedical Engineering and Professor of Radiology (Physics).
He has served on the program committee for the IEEE-EMBS Workshop on Wavelet Applications in Medicine in 1994, 1998, 1999, and 2004. He was the founding chair of the SPIE conference on “Mathematical Imaging: Wavelet Application in Signal and Image Processing”, and served as co-chair during the years 1993-2003. Dr. Laine has served as Chair of Technical Committee (TC-BIIP) on Biomedical Imaging and Image Processing for EMBS 2004-2009, and has been a member of the TC of IEEE Signal Processing Society, TC-BISP (Biomedical Imaging and Signal Processing) 2003-present. Professor Laine served on the IEEE ISBI (International Symposium on Biomedical Imaging) steering committee, 2006-2009 and 2009 – 2012. He was the Program Chair for the IEEE EMBS annual conference in 2006 held in New York City and served as Program Co-Chair for IEEE ISBI in 2008 (Paris, France). He served as Area Editor for IEEE Reviews in BME in Biomedical Imaging since 2007-2013. He was Program Chair for the EMBS annual conference for 2011 (Boston, MA). Professor Laine Chaired the Steering committee for IEEE ISBI, 2011-2013, and Chairs the Council of Societies for AIMBE (American Institute for Medical and Biological Engineers). He was the General Co-Chair for IEEE ISBI in 2022. Finally, he served as the IEEE EMBS Vice President of Publications 2008 – 2012, and was the President of IEEE EMBS (Engineering in Biology and Medicine Society) 2015 and 2016. He is a Fellow of IEEE, AIMBE and IFMBE.