Literature DB >> 23206681

Current challenges to the clinical translation of brain machine interface technology.

Charles W Lu1, Parag G Patil, Cynthia A Chestek.   

Abstract

Development of neural prostheses over the past few decades has produced a number of clinically relevant brain-machine interfaces (BMIs), such as the cochlear prostheses and deep brain stimulators. Current research pursues the restoration of communication or motor function to individuals with neurological disorders. Efforts in the field, such as the BrainGate trials, have already demonstrated that such interfaces can enable humans to effectively control external devices with neural signals. However, a number of significant issues regarding BMI performance, device capabilities, and surgery must be resolved before clinical use of BMI technology can become widespread. This chapter reviews challenges to clinical translation and discusses potential solutions that have been reported in recent literature, with focuses on hardware reliability, state-of-the-art decoding algorithms, and surgical considerations during implantation.
Copyright © 2012 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2012        PMID: 23206681     DOI: 10.1016/B978-0-12-404706-8.00008-5

Source DB:  PubMed          Journal:  Int Rev Neurobiol        ISSN: 0074-7742            Impact factor:   3.230


  4 in total

1.  Control for multifunctionality: bioinspired control based on feeding in Aplysia californica.

Authors:  Victoria A Webster-Wood; Jeffrey P Gill; Peter J Thomas; Hillel J Chiel
Journal:  Biol Cybern       Date:  2020-12-10       Impact factor: 2.086

2.  Enhancing brain-machine interface (BMI) control of a hand exoskeleton using electrooculography (EOG).

Authors:  Matthias Witkowski; Mario Cortese; Marco Cempini; Jürgen Mellinger; Nicola Vitiello; Surjo R Soekadar
Journal:  J Neuroeng Rehabil       Date:  2014-12-16       Impact factor: 4.262

Review 3.  A New Frontier: The Convergence of Nanotechnology, Brain Machine Interfaces, and Artificial Intelligence.

Authors:  Gabriel A Silva
Journal:  Front Neurosci       Date:  2018-11-16       Impact factor: 4.677

4.  Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys.

Authors:  David A Schwarz; Mikhail A Lebedev; Timothy L Hanson; Dragan F Dimitrov; Gary Lehew; Jim Meloy; Sankaranarayani Rajangam; Vivek Subramanian; Peter J Ifft; Zheng Li; Arjun Ramakrishnan; Andrew Tate; Katie Z Zhuang; Miguel A L Nicolelis
Journal:  Nat Methods       Date:  2014-04-28       Impact factor: 28.547

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.