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Annals of Biomedical Engineering

, Volume 42, Issue 8, pp 1573–1593 | Cite as

Closed-Loop Brain–Machine–Body Interfaces for Noninvasive Rehabilitation of Movement Disorders

  • Frédéric D. Broccard
  • Tim Mullen
  • Yu Mike Chi
  • David Peterson
  • John R. Iversen
  • Mike Arnold
  • Kenneth Kreutz-Delgado
  • Tzyy-Ping Jung
  • Scott Makeig
  • Howard Poizner
  • Terrence Sejnowski
  • Gert Cauwenberghs
Article

Abstract

Traditional approaches for neurological rehabilitation of patients affected with movement disorders, such as Parkinson’s disease (PD), dystonia, and essential tremor (ET) consist mainly of oral medication, physical therapy, and botulinum toxin injections. Recently, the more invasive method of deep brain stimulation (DBS) showed significant improvement of the physical symptoms associated with these disorders. In the past several years, the adoption of feedback control theory helped DBS protocols to take into account the progressive and dynamic nature of these neurological movement disorders that had largely been ignored so far. As a result, a more efficient and effective management of PD cardinal symptoms has emerged. In this paper, we review closed-loop systems for rehabilitation of movement disorders, focusing on PD, for which several invasive and noninvasive methods have been developed during the last decade, reducing the complications and side effects associated with traditional rehabilitation approaches and paving the way for tailored individual therapeutics. We then present a novel, transformative, noninvasive closed-loop framework based on force neurofeedback and discuss several future developments of closed-loop systems that might bring us closer to individualized solutions for neurological rehabilitation of movement disorders.

Keywords

Brain–machine–body interface Closed-loop systems Movement disorders Noninvasive Rehabilitation 

Notes

Acknowledgments

The authors acknowledge support from National Science Foundation grant EFRI-1137279 (M3C: Mind, Machines, and Motor Control). DP would like to acknowledge support from the Bachmann-Strauss Dystonia & Parkinson’s Foundation, the Benign Essential Blepharospasm Research Foundation, the dystonia Coalition (NS065701), the Kavli Institute for Brain and Mind and a grant from the NSF to the Temporal Dynamics of Learning Center (SBE-0542013). HP is supported by the NSF grant #SMA-1041755 and the ONR MURI Award No.: N00014-10-1-0072. SM would like to acknowledge a gift from The Swartz Foundation (Old Field NY) and the NINDS grant R01-NS047293-09A1. The authors would like to recognize the contributions of Alejandro Ojeda Gonzalez for designing the MoBILAB environment and Christian Kothe for designing the data collection system LSL and the BCILAB extension for the MoBI setup. The authors would like to thank Nikil Govil and Abraham Akinin for carrying out preliminary experiments on proprioception with Parkinson’s disease patients and Trevor Kerth from Cognionics for help and assistance during data collection with the 64-channel dry EEG headset. The authors also would like to thank all the participants at the 2012 IEEE EMB/CAS/SMC workshop on Brain–Machine–Body Interfaces in San Diego, as well as the participants at the 2012 NSF EFRI Grantees Conference in Washington DC, for insightful interactions and discussions.

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Copyright information

© Biomedical Engineering Society 2014

Authors and Affiliations

  • Frédéric D. Broccard
    • 1
    • 2
  • Tim Mullen
    • 3
  • Yu Mike Chi
    • 4
  • David Peterson
    • 1
    • 5
  • John R. Iversen
    • 3
  • Mike Arnold
    • 6
  • Kenneth Kreutz-Delgado
    • 3
  • Tzyy-Ping Jung
    • 3
  • Scott Makeig
    • 3
  • Howard Poizner
    • 1
  • Terrence Sejnowski
    • 1
    • 5
    • 7
  • Gert Cauwenberghs
    • 1
    • 2
  1. 1.Institute for Neural ComputationUniversity of California San DiegoLa JollaUSA
  2. 2.Department of BioengineeringUniversity of California San DiegoLa JollaUSA
  3. 3.Swartz Center for Computational NeuroscienceUniversity of California San DiegoLa JollaUSA
  4. 4.Cognionics Inc.San DiegoUSA
  5. 5.Computational Neuroscience LaboratorySalk Institute for Biological StudiesLa JollaUSA
  6. 6.Isoloader USA Inc.EncinitasUSA
  7. 7.Howard Hughes Medical InstituteLa JollaUSA

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