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A Human–Robot Interaction Perspective on Assistive and Rehabilitation Robotics

Beckerle, Philipp and Salvietti, Gionata and Unal, Ramazan and Prattichizzo, Domenico and Rossi, Simone and Castellini, Claudio and Hirche, Sandra and Endo, Satoshi and Amor, Heni Ben and Ciocarlie, Matei and Mastrogiovanni, Fulvio and Argall, Brenna D. and Bianchi, Matteo (2017):
A Human–Robot Interaction Perspective on Assistive and Rehabilitation Robotics.
11, In: Frontiers in Neurorobotics, ISSN 1662-5218,
DOI: 10.3389/fnbot.2017.00024,

Available under CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Origin: Secondary publication via sponsored Golden Open Access
Title: A Human–Robot Interaction Perspective on Assistive and Rehabilitation Robotics
Language: English

Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human–robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.

Journal or Publication Title: Frontiers in Neurorobotics
Volume: 11
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Institute for Mechatronic Systems in Mechanical Engineering (IMS)
Date Deposited: 17 Jul 2017 12:33
Last Modified: 22 Jan 2020 13:41
DOI: 10.3389/fnbot.2017.00024
URN: urn:nbn:de:tuda-tuprints-66164
Identification Number: 10.3389/fnbot.2017.00024
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/6616
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