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Neural and Physiological Measures to Classify User’s Intention and Control Exoskeletons for Rehabilitation or Assistance: The Experience @NearLab

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Advances in Service and Industrial Robotics (RAAD 2017)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 49))

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Abstract

Robotic systems to restore, augment and support human capabilities hinder the natural interaction with the world. Different approaches based on physiological measurements such as brain activity, muscle contraction, kinematics, or eye movement, can be exploited to automatically and reliably detect the intention of the user to perform a movement. Once the intention of the user is detected or classified, it can trigger or control an exoskeleton supporting the target gesture. All these features together provide a personalized communication between the robot and the user making human-robot interaction natural and seamless. Thus, the acceptability and usability of the system is maximized. Several integrated robotic actuators driven by user’s intention are here described to demonstrate the potentiality of these technologies both for rehabilitation and assistance purposes.

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Authors and Affiliations

  1. NearLab, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy

    Simona Ferrante, Emilia Ambrosini, Claudia Casellato, Marta Gandolla, Alessandra Pedrocchi & Giancarlo Ferrigno

Authors
  1. Simona Ferrante
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  2. Emilia Ambrosini
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  3. Claudia Casellato
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  4. Marta Gandolla
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  5. Alessandra Pedrocchi
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  6. Giancarlo Ferrigno
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Corresponding author

Correspondence to Simona Ferrante .

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Editors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy

    Carlo Ferraresi

  2. Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy

    Giuseppe Quaglia

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Ferrante, S., Ambrosini, E., Casellato, C., Gandolla, M., Pedrocchi, A., Ferrigno, G. (2018). Neural and Physiological Measures to Classify User’s Intention and Control Exoskeletons for Rehabilitation or Assistance: The Experience @NearLab. In: Ferraresi, C., Quaglia, G. (eds) Advances in Service and Industrial Robotics. RAAD 2017. Mechanisms and Machine Science, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-61276-8_78

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  • DOI: https://doi.org/10.1007/978-3-319-61276-8_78

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61275-1

  • Online ISBN: 978-3-319-61276-8

  • eBook Packages: EngineeringEngineering (R0)

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