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Keynote Lectures

Neural Engineering: Restoring, Replacing, and Extending Cognition
Moritz Grosse-Wentrup, Max Planck Institute for Inteligent Systems, Germany

Available Soon
Eugenio Guglielmelli, Università Campus Bio-Medico, Italy

Brain Computer Interfaces and Immersive Virtual Reality for Post-Stroke Motor Rehabilitation
Sergi Bermudez i Badia, Madeira Interactive Technologies Institute/Universidade da Madeira, Portugal

Virtual Reality paradigms for the Rehabilitation of Stroke
Mónica Cameirão, Universidade da Madeira, Portugal

 

Neural Engineering: Restoring, Replacing, and Extending Cognition

Moritz Grosse-Wentrup
Max Planck Institute for Inteligent Systems
Germany
 

Brief Bio
Moritz Grosse-Wentrup is a group leader at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He studied engineering at the Technische Universität München and the University of Maryland, College Park. After obtaing his Dr.-Ing. at the Technische Universität München, he worked as a postdoc with Bernhard Schölkopf at the Max Planck Institute for Biological Cybernetics. He has been the recipient of the 2011 Annual BCI Research Award and the 2016 IEEE Brain Initiative Best Paper Award. He serves as chair of the steering committee for the International Workshop on Pattern Recognition for Neuroimaging (PRNI) and is a founding member of the EURASIP special area team for Biomedical Image and Signal Analysis. His research focuses on machine learning for neural engineering, with applications in brain-computer interfacing for communication and rehabilitation.


Abstract
Neural engineering restores, replaces, or extends cognitive functions by establishing bi-directional interfaces to the brain. These interfaces require sensors to record neural activity, machine learning algorithms to decode cognitive states from neural signals in real-time, and actuators to steer neural activity towards desired target states. In this talk, I give an overview of the primary challenges for neural engineering and highlight solutions developed in my group. On the algorithmic side, I focus on two key problems: How can we build brain decoding models that generalise across heterogeneous subjects, and how can we use these models to predict how neural activity should be altered, e.g., by transcranial electrical stimulation, to achieve a desired cognitive state? On the hardware side, I present a low-cost system that enables high-quality EEG recordings outside of laboratory environments, and introduce a brain-robot interface that combines real-time brain decoding with haptic feedback. I demonstrate the impact of our work on two translational projects in the domain of personalised medicine: A brain-computer interface for communication with severely paralysed patients in late-stages of amyotrophic lateral sclerosis, and a brain-robot interface for post-stroke motor rehabilitation. I conclude by outlining my vision for translating neural engineering into everyday applications that benefit patient populations as well as healthy users.



 

 

Keynote Lecture

Eugenio Guglielmelli
Università Campus Bio-Medico
Italy
 

Brief Bio

Eugenio Guglielmelli, IEEE Senior Member, is Full Professor of Bioengineering at Università Campus Bio-Medico di Roma (UCBM, Italy) where he serves as Prorector for Research and as the Head of the Research Unit of Biomedical Robotics and Biomicrosystems, which he founded in 2004. From 1991 to 2004, he worked with at the Advanced Robotics Technology and Systems Laboratory (ARTS Lab, now The BioRobotics Institute) of the Scuola Superiore Sant’Anna in Pisa, Italy, which he also co-ordinated (2002-2004). His main current research interests are in the fields of human-centered robotics, biomechatronic design and biomorphic control of robotic systems, and in their application to robot-mediated motor therapy, assistive robotics, neuroengineering and neurorobotics. He is author/co-author of more than 350 papers appeared on peer-reviewed international journals, conference proceedings and books. He served as Associate Editor of the IEEE Transactions on Robotics (2009-2012), as Editor-in-Chief of the IEEE Robotics & Automation Magazine (2013-2015) and also as Secretary (2002-2004) and Associate Vice-President for Technical Activities of the IEEE Robotics & Automation Society (RAS). He currently serves as IEEE RAS Vice-President for Publication Activities.


Abstract
Available Soon



 

 

Brain Computer Interfaces and Immersive Virtual Reality for Post-Stroke Motor Rehabilitation

Sergi Bermudez i Badia
Madeira Interactive Technologies Institute/Universidade da Madeira
Portugal
 

Brief Bio
Sergi Bermúdez i Badia is a Senior Researcher at the Madeira Interactive Technologies Institute (Madeira-ITI), and Assistant Professor at the University of Madeira (UMa) and Adjunct Faculty of the Human Computer Interaction Institute of Carnegie Mellon University (HCII, CMU). He received a degree in telecommunications engineering from the Universitat Politècnica de Catalunya (UPC) and a PhD from the Swiss Federal Institute of Technology Zürich (ETHZ). He has pursued research at several institutes in Europe and the USA, including the Laboratoire de Production Microtechnique at the EPFL (Lausanne), the Institute of Neuroinformatics at the ETHZ (Zurich), at the Institute of Audiovisual Studies at the Technology Department of the Universitat Pompeu Fabra (Barcelona) and the Quality of Life Technologies and Entertainment technology centers of the Carnegie Mellon University (Pittsburgh). Since he arrived in Madeira, he contributed to the establishment of the NeuroRehabLab research group (http://neurorehabilitation.m-iti.org) with the scientific goal of investigating the use of multimedia, interactive technologies and robots to exploit them in real world applications, with special emphasis in neuro-rehabilitation systems, educational and entertainment applications.


Abstract
Stroke is one of the most common causes of acquired disability, leaving numerous adults with cognitive and motor impairments, and affecting patients’ capability to live independently. In recent years, novel rehabilitation paradigms have been proposed to address the life-long plasticity of the brain to regain motor function. Among them, the use of a hybrid brain–computer interface (BCI)—virtual reality (VR) approach can combine a personalized motor training in a VR environment, exploiting brain mechanisms for action execution and observation, and a neuro-feedback paradigm using mental imagery as a way to engage secondary or indirect pathways to access undamaged cortico-spinal tracts. I will present the development and validation experiments of the proposed technology. More specifically, I will discuss the underlying neuroscientific principles, use of low cost EEG acquisition systems, the integration in immersive VR and the use of haptic technology. I will show how the proposed motor imagery driven BCI-VR system is usable, engaging and able to engage the desired brain motor areas. This novel technology enables stroke survivors without active movement to engage in more effective rehabilitation paradigms.



 

 

Virtual Reality paradigms for the Rehabilitation of Stroke

Mónica Cameirão
Universidade da Madeira
Portugal
 

Brief Bio

Mónica is an Assistant Professor and researcher at the University of Madeira (UMa) and the Madeira Interactive Technologies Institute (Madeira-ITI) in Portugal. She is co-principal investigator and co-founder of the NeuroRehabLab research group (http://neurorehabilitation.m-iti.org), an interdisciplinary research group that investigates at the intersection of technology, neuroscience and clinical practice to find novel solutions to increase the quality of life of those with special needs. During the last years, Mónica has been involved in the development and clinical assessment of virtual reality (VR) technologies for stroke rehabilitation and her work gave rise to publications in journals such as Stroke, Restorative Neurology and Neuroscience, and the Journal of Neuroengineering and Rehabilitation. Mónica's work in VR explores specific brain mechanisms that relate to functional recovery to approach motor and cognitive stroke rehabilitation by means of non-invasive and low-cost technologies. Her research addresses aspects such as serious gaming, personalization of training, integrative motor-cognitive tasks, and physiological computing. More recently, Mónica also started applying these principles to technology mediated fitness training for the elderly population. In 2016, Mónica has been awarded the ISVR Early Career Investigator Award, an award granted by the International Society for Virtual Rehabilitation to acknowledge important contributions by early career scientists whose research relates to virtual rehabilitation.


Abstract
Stroke remains a major cause of adult disability, with very high economic and social costs. We need new rehabilitation delivery models and for this purpose new approaches have been proposed in the last years that rely on the use of interactive and virtual reality technologies. Virtual reality has a lot of potential because it allows the creation of novel paradigms that explore the role of personalization of training, the use of various types of feedback, and engagement incorporating rehabilitation tasks in game contexts. In addition, through these tools we can monitor patients and have a precise and objective quantification of their performance and recovery over time. In this presentation, I will describe different paradigms that combine virtual reality, neurosciences, and rehabilitation guidelines with the objective of developing and validating interactive systems specifically designed for maximizing motor and cognitive rehabilitation after a stroke. I will address aspects such as task personalization, cognitive-motor interference based on patient profile, and the role of the type of content used in the virtual scenarios. The impact of these paradigms will be illustrated with the results from controlled studies with stroke survivors in acute and chronic stages of stroke.



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