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Human–Machine Interfaces for Motor Rehabilitation

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Advanced Computational Intelligence in Healthcare-7

Part of the book series: Studies in Computational Intelligence ((SCI,volume 891))

Abstract

Neurological disorders affect a large part of the population, causing cognitive and motor impairments. To that end, non-pharmacological interventions targeting support and restoration of the disrupted functions have been a major issue in modern society. New technologies enable effective communication between the affected individual and an external system, establishing the concept of a human–machine interface (HMI). This chapter seeks to describe the principles of modern noninvasive HMI systems and to present current trends regarding the methods used to capture physiological and non-physiological motor-related data in order to control external devices within a rehabilitation framework. Furthermore, in regard to classification and parameter complexity, computational intelligence tools, machine learning approaches and simulation testing are presented. The relevant applications are discussed within a taxonomy based on the nature of the motor-related source data, while methodological aspects and future challenges concerning the design of HMI systems for rehabilitation purposes are also included.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, National Technical University of Athens, 15780, Athens, Greece

    Ioannis Kakkos, Stavros-Theofanis Miloulis, Kostakis Gkiatis, Georgios N. Dimitrakopoulos & George K. Matsopoulos

  2. Department of Medicine, University of Patras, Patras, Greece

    Georgios N. Dimitrakopoulos

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  1. Ioannis Kakkos
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  2. Stavros-Theofanis Miloulis
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  3. Kostakis Gkiatis
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  4. Georgios N. Dimitrakopoulos
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  5. George K. Matsopoulos
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Correspondence to Ioannis Kakkos .

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  1. Department of Digital Systems, University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  2. Computer Information Systems, Missouri State University, Springfield, MO, USA

    Sheryl Brahnam

  3. School of Electrical and Information Engineering, University of South Australia, Adelaide, Australia

    Lakhmi C. Jain

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Kakkos, I., Miloulis, ST., Gkiatis, K., Dimitrakopoulos, G.N., Matsopoulos, G.K. (2020). Human–Machine Interfaces for Motor Rehabilitation. In: Maglogiannis, I., Brahnam, S., Jain, L. (eds) Advanced Computational Intelligence in Healthcare-7. Studies in Computational Intelligence, vol 891. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-61114-2_1

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