Peñalver de Andrés, Joaquín Álvaro; Duarte, Jaime; Vallery, Heike; Klamroth-Marganska, Verena; Riener, Robert; Marchal Crespo, Laura; Rauter, Georg (29 July 2019). Do we need complex rehabilitation robots for training complex tasks? IEEE International Conference on Rehabilitation Robotics (ICORR), 2019, pp. 1085-1090. IEEE 10.1109/ICORR.2019.8779384
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One key question in motor learning is how the complex tasks in daily life – those that require coordinated movements of multiple joints – should be trained. Often, complex tasks are directly taught as a whole, even though training of simple movement components before training the entire movement has been shown to be more effective for particularly complex tasks (“part-whole transfer paradigm”). The important implication of the part-whole transfer paradigm, e.g. on the field of rehabilitation robotics, is that training of most complex tasks could be simplified and, subsequently, devices used to train can become simpler and more affordable. In this way, robot-assisted rehabilitation could become more accessible. However, often the last step in the training process is forgotten: the recomposition of several simple movement components to a complete complex movement. Therefore, at least for the last training step, a complex rehabilitation device may be required. In a pilot study, we wanted to investigate if a complex robotic device (e.g. an exoskeleton robot with many degrees of freedom), such as the ARMin rehabilitation robot, is really beneficial for training the coordination between several simpler movement components or if training using visual feedback would lead to equal benefits. In a study, involving 16 healthy participants, who were instructed in a complex rugby motion, we could show first trends on the following two aspects: i) the partwhole transfer paradigm seems to hold true and therefore, simple robots might be used for training movement primitives. ii) Visual feedback does not seem to have the same potential, at least in healthy humans, to replace visuo-haptic guidance for movement recomposition of complex tasks. Therefore, complex rehabilitation robots seem to be beneficial for training complex real-life tasks.
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