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Reinforcing Motor Re-Training and Rehabilitation through Games: A Machine-Learning Perspective

Frontiers in Neuroengineering
Frontiers Media SA
Publication Date
DOI: 10.3389/neuro.16.003.2009
  • Neuroscience
  • Opinion
  • Computer Science
  • Engineering
  • Mathematics
  • Medicine


untitled Frontiers in Neuroengineering March 2009 | Volume 2 | Article 3 | 1 NEUROENGINEERING OPINION ARTICLE published: 31 March 2009 doi: 10.3389/neuro.16.003.2009 Reinforcing motor re-training and rehabilitation through games: a machine-learning perspective Maurizio Schmid1,2* 1 Department of Applied Electronics, Roma Tre University, Rome, Italy 2 Harvard Medical School, Spaulding Rehabilitation Hospital, Cambridge, MA, USA * Correspondence: [email protected] tation is usually obtained by either a real teacher (e.g. the physical therapist), or a vir- tual teacher (such as in virtual reality-based rehabilitation), thus triggering an instance of the learning-by- imitation scheme. If the rehabilitation exercises are administered in a game fashion, which means asking the player to choose a solution in terms of movement execution out of a number of discrete possi- ble alternatives, we can hypothesize that this is an example of a reinforcement-learning scheme (Sutton and Barto, 1998). The internal model hypothesis, i.e. the presence of an internal representation of the dynamics and kinematics of movement at the neural level, is acknowledged as one of the leading theories of motor control and learning in neuroscience (Jordan and Rumelhart, 1992), and many authors pro- posed different mathematical proxies of this empirical paradigm (see e.g. Tin and Poon, 2005). In the framework of rehabilitation, it is assumed that, in the brain (the con- troller), this internal representation is re- trained by changing its functional structure over time through interaction with modifi - cations either in the environment or in the affordances of the body. It is acknowledged that most of the computational models that can simulate this ability towards change are based on the presence of rules (needed to adjust the parameters of the controller), where the interaction between the con- troller and the controlled plant (the body) allows some kind of modifi catio

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