Keynote Lectures

Brain-inspired Medical Image Analysis for Computer-aided Diagnosis
Bart M. ter Haar Romeny, Eindhoven University of Technology (TU/e), Netherlands, Netherlands

Designing for Somaesthetic Experiences - Focusing on Actuation Rather than Sensing?
Kristina Höök, Royal Institute of Technology, Sweden, Sweden

An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments
Bethany Bracken, Charles River Analytics Inc., United States, United States

Off-the-person ECG-based Biometric Recognition
Hugo Plácido da Silva, IT- Instituto de Telecomunicações, Portugal, Portugal

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.

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.

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.

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.