  In today's world, many patients with cognitive impairments and motor
dysfunction seek the attention of experts to perform specific conventional
therapies to improve their situation. However, due to a lack of
neurorehabilitation professionals, patients suffer from severe effects that
worsen their condition. In this paper, we present a technological approach for
a novel robotic neurorehabilitation training system. It relies on a combination
of a rehabilitation device, signal classification methods, supervised machine
learning models for training adaptation, training exercises, and socially
interactive agents as a user interface. Together with a professional, the
system can be trained towards the patient's specific needs. Furthermore, after
a training phase, patients are enabled to train independently at home without
the assistance of a physical therapist with a socially interactive agent in the
role of a coaching assistant.
