Literature DB >> 34541898

The science and engineering behind sensitized brain-controlled bionic hands.

Chethan Pandarinath1,2, Sliman J Bensmaia3,4,5.   

Abstract

Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the way for brain-machine interfaces (BMIs), which harness neural signals to reanimate the limbs via electrical activation of the muscles or to control extracorporeal devices, thereby bypassing the muscles and senses altogether. BMIs consist of reading out motor intent from the neuronal responses monitored in motor regions of the brain and executing intended movements with bionic limbs, reanimated limbs, or exoskeletons. BMIs also allow for the restoration of the sense of touch by electrically activating neurons in somatosensory regions of the brain, thereby evoking vivid tactile sensations and conveying feedback about object interactions. In this review, we discuss the neural mechanisms of motor control and somatosensation in able-bodied individuals and describe approaches to use neuronal responses as control signals for movement restoration and to activate residual sensory pathways to restore touch. Although the focus of the review is on intracortical approaches, we also describe alternative signal sources for control and noninvasive strategies for sensory restoration.

Entities:  

Keywords:  artificial touch; brain-machine interfaces; motor control; neuroprosthetics; sensory feedback

Mesh:

Year:  2021        PMID: 34541898      PMCID: PMC8742729          DOI: 10.1152/physrev.00034.2020

Source DB:  PubMed          Journal:  Physiol Rev        ISSN: 0031-9333            Impact factor:   37.312


  396 in total

1.  Minimally invasive endovascular stent-electrode array for high-fidelity, chronic recordings of cortical neural activity.

Authors:  Thomas J Oxley; Nicholas L Opie; Sam E John; Gil S Rind; Stephen M Ronayne; Tracey L Wheeler; Jack W Judy; Alan J McDonald; Anthony Dornom; Timothy J H Lovell; Christopher Steward; David J Garrett; Bradford A Moffat; Elaine H Lui; Nawaf Yassi; Bruce C V Campbell; Yan T Wong; Kate E Fox; Ewan S Nurse; Iwan E Bennett; Sébastien H Bauquier; Kishan A Liyanage; Nicole R van der Nagel; Piero Perucca; Arman Ahnood; Katherine P Gill; Bernard Yan; Leonid Churilov; Christopher R French; Patricia M Desmond; Malcolm K Horne; Lynette Kiers; Steven Prawer; Stephen M Davis; Anthony N Burkitt; Peter J Mitchell; David B Grayden; Clive N May; Terence J O'Brien
Journal:  Nat Biotechnol       Date:  2016-02-08       Impact factor: 54.908

2.  Functional restoration of elbow extension after spinal-cord injury using a neural network-based synergistic FES controller.

Authors:  Joseph P Giuffrida; Patrick E Crago
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2005-06       Impact factor: 3.802

3.  Targeting recovery: priorities of the spinal cord-injured population.

Authors:  Kim D Anderson
Journal:  J Neurotrauma       Date:  2004-10       Impact factor: 5.269

4.  Brain-machine interface in chronic stroke rehabilitation: a controlled study.

Authors:  Ander Ramos-Murguialday; Doris Broetz; Massimiliano Rea; Leonhard Läer; Ozge Yilmaz; Fabricio L Brasil; Giulia Liberati; Marco R Curado; Eliana Garcia-Cossio; Alexandros Vyziotis; Woosang Cho; Manuel Agostini; Ernesto Soares; Surjo Soekadar; Andrea Caria; Leonardo G Cohen; Niels Birbaumer
Journal:  Ann Neurol       Date:  2013-08-07       Impact factor: 10.422

5.  Temporal encoding of movement kinematics in the discharge of primate primary motor and premotor neurons.

Authors:  Q G Fu; D Flament; J D Coltz; T J Ebner
Journal:  J Neurophysiol       Date:  1995-02       Impact factor: 2.714

6.  Bias, optimal linear estimation, and the differences between open-loop simulation and closed-loop performance of spiking-based brain-computer interface algorithms.

Authors:  Steven M Chase; Andrew B Schwartz; Robert E Kass
Journal:  Neural Netw       Date:  2009-05-22

Review 7.  Myoelectric control of prosthetic hands: state-of-the-art review.

Authors:  Purushothaman Geethanjali
Journal:  Med Devices (Auckl)       Date:  2016-07-27

8.  The Largest Response Component in the Motor Cortex Reflects Movement Timing but Not Movement Type.

Authors:  Matthew T Kaufman; Jeffrey S Seely; David Sussillo; Stephen I Ryu; Krishna V Shenoy; Mark M Churchland
Journal:  eNeuro       Date:  2016-08-30

Review 9.  Optically pumped magnetometers: From quantum origins to multi-channel magnetoencephalography.

Authors:  Tim M Tierney; Niall Holmes; Stephanie Mellor; José David López; Gillian Roberts; Ryan M Hill; Elena Boto; James Leggett; Vishal Shah; Matthew J Brookes; Richard Bowtell; Gareth R Barnes
Journal:  Neuroimage       Date:  2019-05-26       Impact factor: 6.556

10.  Long-term stability of cortical population dynamics underlying consistent behavior.

Authors:  Juan A Gallego; Matthew G Perich; Raeed H Chowdhury; Sara A Solla; Lee E Miller
Journal:  Nat Neurosci       Date:  2020-01-06       Impact factor: 24.884

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  2 in total

Review 1.  Behaviorist approaches to investigating memory and learning: A primer for synthetic biology and bioengineering.

Authors:  Charles I Abramson; Michael Levin
Journal:  Commun Integr Biol       Date:  2021-12-14

Review 2.  Clinical neuroscience and neurotechnology: An amazing symbiosis.

Authors:  Andrea Cometa; Antonio Falasconi; Marco Biasizzo; Jacopo Carpaneto; Andreas Horn; Alberto Mazzoni; Silvestro Micera
Journal:  iScience       Date:  2022-09-16
  2 in total

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