Brain-inspired Medical Image Analysis for Computer-aided Diagnosis
Bart H. Romeny, Eindhoven University of Technology (TU/e), Netherlands
Designing for Somaesthetic Experiences - Focusing on Actuation Rather than Sensing?
Kristina Höök, Royal Institute of Technology, Sweden
An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments
Bethany Bracken, Charles River Analytics Inc., United States
Off-the-person ECG-based Biometric Recognition
Hugo Plácido da Silva, IT- Instituto de Telecomunicações, Portugal
Brain-inspired Medical Image Analysis for Computer-aided Diagnosis
Bart H. Romeny
Eindhoven University of Technology (TU/e)
Netherlands
http://bmia.bmt.tue.nl/people/BRomeny/index.html
Brief Bio
Bart M. ter Haar Romeny received the MSc degree in Applied Physics from Delft University of Technology in 1978, Ph.D. from Utrecht University in 1983 in biophysics. He became principal physicist of the Utrecht University Hospital Radiology Department. He was co-founder and associate professor at the Image Sciences Institute (ISI) of Utrecht University (1989-2001). From 2001, ter Haar Romeny holds the chair of Biomedical Image Analysis at the Department of Biomedical Engineering of Eindhoven University of Technology in the Netherlands, and since 2011 is appointed distinguished professor at Northeastern University, Shenyang, China. He closely collaborates with Philips Healthcare and Philips Research, other industries and (national and international) hospitals and research groups. Currently he is project leader of the Sino-Dutch RetinaCheck project, a large screening project for early detection of diabetic retinopathy in Liaoning, China. He authored an interactive tutorial book on multi-scale computer vision techniques, edited a book on non-linear diffusion theory in computer vision and is involved in (resp. initiated) a number of international collaborations on these subjects. He is author/co-author of over 200 refereed journal and conference papers, 12 books and book chapters, and holds 2 patents. He supervised 29 PhD students, of which 4 graduated cum laude, and over 140 Master students. He is senior member of IEEE, associate member of the Chinese Brainnetome consortium, visiting professor at the Chinese Academy of Sciences in Beijing, member of the Governing Board of IAPR, Fellow of EAMBES, and chairman of the Dutch Society for Pattern Recognition and Image Processing.
Abstract
Discoveries on brain mechanisms have really taken off. Modern optical and new MRI technologies give insight in this spectacular organ, especially in the field of vision. Of mutual benefit are new developments in deep learning and neural network modeling, the mathematical understanding, and the availability of massively parallel computing power. The lecture will address a number of lessons to learn from the brain for medical computer-aided diagnosis, explain the mathematical intuition of a number of algorithms, and show some remarkable successes booked so far.
Designing for Somaesthetic Experiences - Focusing on Actuation Rather than Sensing?
Kristina Höök
Royal Institute of Technology
Sweden
Brief Bio
Kristina Höök is a professor in Interaction Design at the Royal Institute of Technology and also works part-time at RISE. Höök has published numerous journal papers, books and book chapters, and conference papers in highly renowned venues. A frequent keynote speaker, she is known for her work on social navigation, seamfulness, mobile services, affective interaction and lately, designing for bodily engagement in interaction through somaesthetics. Her competence lies mainly in interaction design and user studies helping to form design. She has obtained numerous national and international grants, awards, and fellowships including the Cor Baayen Fellowship by ERCIM (European Research Consortium for Informatics and Mathematics), the INGVAR award and she is an ACM Distinguished Scientist. She has been listed as one of the 50 most influential IT-women in Sweden every year since 2008. She is an elected member of Royal Swedish Academy of Engineering Sciences (IVA).
Abstract
In designing for bodily experiences, there has been a lack of theories that can provide the underpinnings we need to understand and deepen our design thinking. Despite all the work we have seen on designing for embodiment, the actual corporeal, pulsating, live, felt body has been notably absent from both theory and practical work. At the same time, digital products have become an integral part of the fabric of everyday life, the pleasures (and pains) they give, their contribution to our social identity, or their general aesthetics are now core features of their design. We see more and more attempts to design explicitly for bodily experiences with digital technology, but it is a notably challenging design task. With the advent of new technologies, such as biosensors worn on your body, interactive clothes, or wearable computers such as mobiles equipped with accelerometers, a whole space of possibilities for gesture-based, physical and body-based interaction is opened. How can we do a better job in interaction design involving our bodies? I will discuss how Shusterman’s theories of somaesthetics might provide some inspiration, and the need to focus on actuation rather than sensing.
An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments
Bethany Bracken
Charles River Analytics Inc.
United States
Brief Bio
Bethany Bracken is a Principal Scientist at Charles River Analytics. At Charles River, she currently works on projects using neurophysiological and physiological sensing methods to assess human states such as stress, focused attention, and cognitive workload and to predict upcoming performance deficits to allow time to enact augmentation strategies to optimize that performance. Dr. Bracken has a B.S. in Psychology from Clarion University of Pennsylvania, and a Ph.D. in Neuroscience from Brandeis University. Before joining Charles River Analytics, Dr. Bracken completed a postdoctoral fellowship, quickly followed with a promotion to the faculty level, in the Department of Psychiatry at McLean Hospital and Harvard Medical School.
Abstract
Bethany Bracken, Noa Palmon, Seth Elkin-Frankston, Scott Irvin, Michael Jenkins & Michael Farry
Across many careers, individuals face alternating periods of high and low attention and cognitive workload, which can result in impaired cognitive functioning and can be detrimental to job performance. For example, some professions (e.g., fire fighters, emergency medical personnel, doctors and nurses working in an emergency room, pilots) require long periods of low workload (boredom), followed by sudden, high-tempo operations during which they may be required to respond to an emergency and perform at peak cognitive levels. Conversely, other professions (e.g., air traffic controllers, market investors in financial industries, analysts) require long periods of high workload and multitasking during which the addition of just one more task results in cognitive overload resulting in mistakes.An unobtrusive system to measure, assess, and predict cognitive workload could warn individuals, their teammates, or their supervisors when steps should be taken to augment cognitive readiness. In this talk I will describe an approach to this problem that we have found to be successful across work domains includes: (1) a suite of unobtrusive, field-ready neurophysiological, physiological, and behavioral sensors that are chosen to best suit the target environment; (2) custom algorithms and statistical techniques to process and time-align raw data originating from the sensor suite; (3) probabilistic and statistical models designed to interpret the data into the human state of interest (e.g., cognitive workload, attention, fatigue); (4) and machine-learning techniques to predict upcoming performance based on the current pattern of events, and (5) display of each piece of information depending on the needs of the target user who may or may not want to drill down into the functioning of the system to determine how conclusions about human state and performance are determined. I will then focus in on our experimental results from our custom functional near-infrared spectroscopy sensor, designed to operate in real-world environments to be worn comfortably (e.g., positioned into a baseball cap or a surgeon’s cap) to measure changes in brain blood oxygenation without adding burden to the individual being assessed.
Off-the-person ECG-based Biometric Recognition
Hugo Plácido da Silva
IT- Instituto de Telecomunicações
Portugal
Brief Bio
PhD in Electrical and Computers Engineering from the Instituto Superior Técnico (IST) - University of Lisbon (UL), Hugo is a researcher at the IT - Instituto de Telecomunicações since 2004, and an Invited Auxiliary Professor at IST/UL since 2019. He is also an entrepreneur, having co-founded and contributing to the foundation of multiple innovative technology-based companies operating in the field of medical devices for healthcare and quality of life. More recently, Hugo has been actively working towards making the world a bit more physiological, through BITalino, an open source software and low-cost hardware toolkit for rapid prototyping and development of biomedical application. His main interests include biosignal research, system engineering, signal processing, and machine learning, and in these topics Hugo has participated and actively contributed to 30+ R&D projects funded by national and internacional agencies. His work has been distinguished with several academic and technical awards, examples of which include the “alumniIPS” career award in 2018 and the 1st place at the Ordem dos Engenheiros Young Engineer Innovation Award in 2015, or the “Most Innovative Technology” award at the MIT Portugal E3 Forum in 2013. Hugo is an ACM Senior Member, an IEEE Senior Member, and a officer-elect of the IEEE Engineering in Medicine and Biology Society Portugal Chapter.
Abstract
Electrocardiography (ECG) is an established standard medical practice and a mainstream diagnostic technique. Although the first practical implementations of devices for human use can be dated back to 1887, measurement methods are still mostly bound to hospital and short-time monitoring settings. However, the ECG has been used in other novel application domains, one of which being biometric recognition, where it has several convenient advantages to enhance existing modalities.
In this talk we will look into the state-of-the-art and future prospects enabled by what has been designated as "off-the-person" ECG sensing, focusing its use as a biometric modality, but describing also how it can lead to better cardiovascular disease management, especially in what concerns prevention and early detection.
By using sensors integrated in everyday use objects (e.g. a computer keyboard, a mobile phone, a PlayStation controller, or a TV remote control) rather than being attached to the body of the person, off-the-person ECG can pave the way for ECG data acquisition to become more pervasive and seamlessly integrated in multiple aspects of peoples everyday lives.