The program will be composed by regular, special and poster sessions, and workshops. Furthermore, plenary lectures will be given by well-known scientists in the field of NeuroRehabilitation. The program will aim at enriching the knowledge of the participants, widening their point of view on specific topics related to NeuroRehabilitation, and getting in closer contact with experts in this field.

Confirmed plenary speakers:


Dr. Ales Holobar
Faculty of Electrical Engineering and Computer Science, University of Maribor


Title: Non-invasive muscle excitation assessment revised

Abstract:In the recent two decades, methodologies for non-invasive surface electromyographic (sEMG) recordings of skeletal muscles and analysis of these recordings substantially improved our understanding of human motor system and human-machine interaction. They opened new ways to objective assessment of muscle synergies, robot-assisted rehabilitation, intuitive prosthetics, and objective assessment and tracking of various pathologies. However, assessment of muscle excitation out of sEMG recordings is frequently non-trivial as sEMG often reflects commands from central nervous system (CNS) as well as anatomical properties and geometric changes of recorded skeletal muscles. Discrimination of these factors requires advanced sEMG decomposition either into individual motor unit spike trains or into their cumulative spike train, removing motor unit action potentials (MUAPs) from sEMG recordings. Several sEMG decomposition techniques have been proposed in the past and in this talk we will review their properties in terms of methodological assumptions, muscle excitation assessment errors and experimental costs. We will systematically compare multichannel and single channel sEMG analysis and sEMG decomposition methodologies, such as independent component analysis (ICA), non-negative matrix factorisation (NMF), recently introduced cumulative activity index (CAI) and others. We will also outline the advantages and methodological limitations of these techniques in various rehabilitation applications, especially in rehabilitation after stroke.



Dr. Vivian K Mushahwar
University of Alberta. Division of Physical Medicine and Rehabilitation



Dr. Ferdinando A. Mussa-Ivaldi
Northwestern University and Shirley Ryan Ability Lab



Title: Model-based motor learning and its clinical implications

Abstract: A growing body of evidence suggests that when we interact physically with our environments our brains form models of the deterministic connection between our actions and the ensuing sensory information. Theories of motor learning posit that the formation of internal models is a key mechanism though which the brain forms predictions about the outcomes of actions, overcoming certain limitations of the biological feedback system. Consistent with these theories, experiments with human-robot interactions have demonstrated the ability of the brain to capture the difference between random and deterministic forces. After a brief review of some earlier studies, I will focus on a family of human-machine interfaces that create a many-to-one mapping between body motions and movements of an external controlled object. In this context, the user learns to control the external object by forming an inverse model of the interface mapping. I will describe this learning process as a state-based dynamical system and will discuss how machine learning may connect with human learning to facilitate the acquisition of motor skills and their recovery after injury to the nervous system.



Dr. Natalie Mrachacz-Kersting
Aalborg University





Dr. Jonathan R. Wolpaw
Director, National Center for Adaptive Neurotechnologies
Wadsworth Center. New York State Deparment of Health
Department of Neurology, Albany Stratton VA Medical Center
Department of Neurology, Neurological Institute, Columbia University





Dr. John W. Krakauer
John C. Malone Professor of Neurology, Neuroscience, & PMR, Johns Hopkins University





Dr. Nadia Dominici
AMS. iBBA. Faculty of Behavioural and Movement Sciences. Vrije Universiteit Amsterdam



Title: Modular organization of locomotion in human and animal

Abstract: In order to walk we must set into motion the body and the legs using literally hundreds of different muscles. The idea that the CNS may control these complex interactions between muscles by using a small number of elementary commands, also known as muscle synergies, has received considerable attention. We explored this idea by examining this modular organization in three different cases: 1. Evolution of number and type of muscle synergies during the development of walking in children, as it evolves from ‘stepping reflex’ in neonates to independent walking in toddlers. 2. Changes in cortico-synergy coherence accompanying short-term balance training in healthy adults. 3. Synergies-based neuromodulation therapies aimed to stimulate and improve gait quality after spinal cord injury.