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Neurocognitive and motor-control challenges for the realization of bionic augmentation

Nature Biomedical Engineering (2022)Cite this article

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Robotic fingers and arms that augment the motor abilities of non-disabled individuals are increasingly feasible yet face neurocognitive barriers and hurdles in efferent motor control.

Bionic limbs were science fiction a few decades ago. Today, individuals with motor disabilities can use brain–machine interfaces to control bionic arms only by thought1, as exemplified by an invasive brain–machine interface that allowed an individual with paralyzed arms to control an anthropomorphic robotic arm with 10 degrees of freedom (DOF) (ref. 2). These achievements have resulted from innovations in hardware for prosthetic limbs and in decoding and encoding algorithms, from more robust and sustainable bidirectional neural interfaces3, and from new surgical techniques4,5 to connect prosthetic technology to the body. Proofs of concept in small-scale clinical tests have raised expectations as to whether such innovations, procedures and devices can be leveraged for the development of assistive technologies1,6.

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Fig. 1: Motor augmentation for enhanced motor capabilities.
Fig. 2: Body parts used in current interfaces for the motor control of X-limbs.
Fig. 3: High-density arrays of recording electrodes for EMG can be used to extract the activity of single motor units using blind-source separation techniques.
Fig. 4: A monkey performing an isometric-force-generation task with their right arm, and a centre-out reaching task using a decoder of the primary motor cortex driven by input from the left contralateral arm.

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Acknowledgements

We thank D. Clode for her assistance with creating Figs. 1 and 2. T.R.M. was supported by an ERC Starting Grant (715022 EmbodiedTech), a Wellcome Trust Senior Research Fellowship (215575/Z/19/Z) and MRC funding award G116768 at the MRC Cognition and Brain Sciences Unit. S.M. was partly funded by the Bertarelli Foundation and the Swiss National Competence Center Research in Robotics. L.E.M was funded by the National Institute of Neurological Disorders and Stroke (R01NS095251, R01 NS053603, R01 NS109257).

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Authors and Affiliations

  1. Institute of Cognitive Neuroscience, University College London, London, UK

    Tamar R. Makin

  2. MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK

    Tamar R. Makin

  3. Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland

    Silvestro Micera

  4. The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy

    Silvestro Micera

  5. Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Lee E. Miller

  6. Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Lee E. Miller

  7. Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA

    Lee E. Miller

  8. Shirley Ryan AbilityLab, Chicago, IL, USA

    Lee E. Miller

Authors
  1. Tamar R. Makin
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  2. Silvestro Micera
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  3. Lee E. Miller
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All authors contributed equally to all aspects of this piece, from conceptualization through to the writing and editing.

Corresponding authors

Correspondence to Tamar R. Makin, Silvestro Micera or Lee E. Miller.

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Nature Biomedical Engineering thanks Daniel Ferris, Juan Moreno and Renaud Ronsse for their contribution to the peer review of this work.

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Makin, T.R., Micera, S. & Miller, L.E. Neurocognitive and motor-control challenges for the realization of bionic augmentation. Nat. Biomed. Eng (2022). https://doi.org/10.1038/s41551-022-00930-1

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