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The neural resource allocation problem when enhancing human bodies with extra robotic limbs

Dominijanni, Giulia; Shokur, Solaiman; Salvietti, Gionata; Buehler, Sarah; Palmerini, Erica; Rossi, Simone; De Vignemont, Frederique; ... Micera, Silvestro; + view all (2021) The neural resource allocation problem when enhancing human bodies with extra robotic limbs. Nature Machine Intelligence , 3 (10) pp. 850-860. 10.1038/s42256-021-00398-9. Green open access

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Abstract

The emergence of robotic body augmentation provides exciting innovations that will revolutionize the fields of robotics, human–machine interaction and wearable electronics. Although augmentative devices such as extra robotic arms and fingers are informed by restorative technologies in many ways, they also introduce unique challenges for bidirectional human–machine collaboration. Can humans adapt and learn to operate a new robotic limb collaboratively with their biological limbs, without restricting other physical abilities? To successfully achieve robotic body augmentation, we need to ensure that, by giving a user an additional (artificial) limb, we are not trading off the functionalities of an existing (biological) one. Here, we introduce the ‘neural resource allocation problem’ and discuss how to allow the effective voluntary control of augmentative devices without compromising control of the biological body. In reviewing the relevant literature on extra robotic fingers and arms, we critically assess the range of potential solutions available for this neural resource allocation problem. For this purpose, we combine multiple perspectives from engineering and neuroscience with considerations including human–machine interaction, sensory–motor integration, ethics and law. In summary, we aim to define common foundations and operating principles for the successful implementation of robotic body augmentation.

Type: Article
Title: The neural resource allocation problem when enhancing human bodies with extra robotic limbs
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s42256-021-00398-9
Publisher version: https://doi.org/10.1038/s42256-021-00398-9
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Biomedical engineering, Brain–machine interface
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Institute of Cognitive Neuroscience
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/10144056
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