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Keynote Lectures

Matching Users and Technology for Brain-Computer Interfaces
Febo Cincotti, Sapienza University of Rome, Italy

Robot-mediated Neurorehabilitation - A Bio-cooperative Approach
Eugenio Guglielmelli, Università Campus Bio-Medico, Italy

Towards Understanding Natural Behavior
Constantin A. Rothkopf, Technical University Darmstadt, Germany

Towards Harmony between Human and Machine in Personal Mobility
Danil Prokhorov, Toyota Tech Center, United States

 

Matching Users and Technology for Brain-Computer Interfaces

Febo Cincotti
Sapienza University of Rome
Italy
 

Brief Bio
Febo Cincotti (MSc in Biomedical Engineering, PhD in Biophysics) is assistant professor at the Sapienza University of Rome. His research interest include the design and assessment of methods and applications of neurophysiologic biosignal processing, including real-time Brain-Computer Interfaces (BCIs). He is coauthor of over 200 papers in the field of biomedical engineering. He is/was principal investigator in several EU projects, in the context of which he proposed new clinical applications of BCIs. He is coordinator of an national research project on the use of BCIs for domotic control, and received grants from the Italian ministries of health and education. He is co-founder of the Neuroelectrical Imaging and BCI lab at the Santa Lucia Foundation of Rome. 


Abstract
Brain–computer interfaces (BCIs) provide an avenue to translate activity of the central nervous system into actions, independent of the natural output pathways, thus helping to restore or enhance physiological functions. Basic research has progressed for more than two decades, and this technology is now being evaluated outside laboratory settings.New design issues have emerged in this process, primarily those related to usability. When BCIs are used as an artificial channel to restore communication in persons with severe motor disabilities, care must be taken that users are involved since the initial design of the assistive device, to maximize effectiveness, efficiency and user satisfaction. Use of BCI technology to improve motor functions, e.g. in neuromotor rehabilitation, should encompass the physiological principles of evidence based medicine, and account for the therapeutic practice conventionally carried on in the hospital ward.



 

 

Robot-mediated Neurorehabilitation - A Bio-cooperative Approach

Eugenio Guglielmelli
Università Campus Bio-Medico
Italy
 

Brief Bio
Eugenio Guglielmelli received the Laurea degree in Electronics Engineering and the PhD in Biomedical Robotics from the University of Pisa, Italy, in 1991 and in 1995. He is currently Full Professor of Bioengineering at Campus Bio-Medico University (Roma, Italy) where he serves as the Head of the Laboratory of Biomedical Robotics and Biomicrosystems, that he founded in 2004. From 1991 to 2004 he worked with prof. Paolo Dario at the Advanced Robotics Technology & Systems Laboratory (ARTS Lab) of the Scuola Superiore SantÕAnna (Pisa, Italy). From 2002 to 2004 he served as the Coordinator of the ARTS Lab.
His main current research interests are in the fields of human-centred robotics, biomechatronic design and biomorphic control of robotic systems, and in their application to robot-mediated motor therapy, assistive robotics, and neurorobotics. He is principal investigator and partner of several national and international projects in the area of biomedical robotics.


Abstract

Application of robots to rehabilitation has been proposed in the ‘80s, and it came to reality some ten years later. It is expected to be the next major medical domain, after diagnosis and surgery, to which robotics technology will be massively deployed in the short-medium term. The lecture will review basic design principles for rehabilitation robotic systems, which greatly benefit from a typical biomechatronic design approach. Main achievements in the field will be critically analyzed, with specific focus on neurorehabilitation applications for functional recovery and substitution. Also, a few research case-studies recently developed in my lab, such as the wearable EVRYON system (www.evryon.eu), the biocooperative MAAT system (hal.umh.es/maat/) and the LIFEHAND experiments on neural interfaces for hand prostheses will be discussed in more detail so to outline the open challenges for next generation robotic solutions for neurorehabilitation.



 

 

Towards Understanding Natural Behavior

Constantin A. Rothkopf
Technical University Darmstadt
Germany
 

Brief Bio
Constantin Rothkopf is an associate professor (W2) in the psychology department at the Technical University Darmstadt. After obtaining a joint PhD in Brain & Cognitive Sciences and Computer Science with Dana Ballard and Mary Hayhoe at the Center for Visual Science at the University of Rochester in 2008, he started a postdoc at the Frankfurt Institute for Advanced Studies (FIAS) working with Jochen Triesch in the theoretical neuroscience group. In 2009 he started as a lecturer at the Goethe University, Frankfurt and since 2010 he is the principal investigator of the 'beliefs, representations, and actions group' at FIAS. After a year as a substitute professor in the Institute of Cognitive Science at the University Osnabrück he is now an associate professor for 'psychology of information processing' in the department of psychology at the Technical University Darmstadt.


Abstract
Natural every-day sequential behavior is where biological systems need to succeed, yet most of our current knowledge about behavior and its neuronal underpinnings stems from experiments in highly controlled laboratory settings. There is both considerable theoretical as well as empirical evidence demonstrating that understanding behavior in natural tasks will require that perceptual, decision, and motor systems be considered together. I will present work from describing the human actome in natural environments, simulations of learning agents in naturalistic virtual environments, and computational analysis of goals in natural navigation tasks that are all directed towards making progress in describing and understanding extended sequential behavior of humans within naturalistic tasks.



 

 

Towards Harmony between Human and Machine in Personal Mobility

Danil Prokhorov
Toyota Tech Center
United States
 

Brief Bio

Dr. Danil Prokhorov began his career in St. Petersburg, Russia, in 1992. He was a research engineer in St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI. In 1997 he became a Ford Research staff member involved in application-driven research on neural networks and other machine learning methods. While at Ford, he was involved in several production-bound projects including neural network based engine misfire detection.  Since 2005 he is with Toyota Technical Center, Ann Arbor, MI.  He is currently in charge of future mobility research department at Toyota Research Institute North America, a TTC division.  He has more than 100 papers in various journals and conference proceedings, as well as 15 patents, to his credit.  He is honored to serve in a number of capacities including the International Neural Network Society (INNS) President, the National Science Foundation (NSF) Expert, and the Associate Editor/Program Committee member of many international journals/conferences.


Abstract

Automotive vehicles are increasingly complex machines under human control.  Well designed vehicles achieve a good balance between machine and human functions.  I will discuss perception and control systems available in current vehicles, as well as recent advances of relevance to future automotive vehicles.



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