From spinal central pattern generators to cortical network

Integrated BCI for walking rehabilitation

G. Cheron, M. Duvinage, C. De Saedeleer, T. Castermans, A. Bengoetxea, M. Petieau, K. Seetharaman, T. Hoellinger, B. Dan, T. Dutoit, F. Sylos Labini, F. Lacquaniti, Y. Ivanenko

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

Original languageEnglish
Article number375148
JournalNeural Plasticity
Volume2012
DOIs
Publication statusPublished - 2012

Fingerprint

Central Pattern Generators
Brain-Computer Interfaces
Locomotion
Walking
Rehabilitation
Brain
Supine Position
Touch
Electromyography
Cerebral Palsy
Gait
Upper Extremity
Multiple Sclerosis
Electroencephalography
Lower Extremity
Stroke
Equipment and Supplies
Wounds and Injuries
Research

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology

Cite this

Cheron, G., Duvinage, M., De Saedeleer, C., Castermans, T., Bengoetxea, A., Petieau, M., ... Ivanenko, Y. (2012). From spinal central pattern generators to cortical network: Integrated BCI for walking rehabilitation. Neural Plasticity, 2012, [375148]. https://doi.org/10.1155/2012/375148

From spinal central pattern generators to cortical network : Integrated BCI for walking rehabilitation. / Cheron, G.; Duvinage, M.; De Saedeleer, C.; Castermans, T.; Bengoetxea, A.; Petieau, M.; Seetharaman, K.; Hoellinger, T.; Dan, B.; Dutoit, T.; Sylos Labini, F.; Lacquaniti, F.; Ivanenko, Y.

In: Neural Plasticity, Vol. 2012, 375148, 2012.

Research output: Contribution to journalArticle

Cheron, G, Duvinage, M, De Saedeleer, C, Castermans, T, Bengoetxea, A, Petieau, M, Seetharaman, K, Hoellinger, T, Dan, B, Dutoit, T, Sylos Labini, F, Lacquaniti, F & Ivanenko, Y 2012, 'From spinal central pattern generators to cortical network: Integrated BCI for walking rehabilitation', Neural Plasticity, vol. 2012, 375148. https://doi.org/10.1155/2012/375148
Cheron G, Duvinage M, De Saedeleer C, Castermans T, Bengoetxea A, Petieau M et al. From spinal central pattern generators to cortical network: Integrated BCI for walking rehabilitation. Neural Plasticity. 2012;2012. 375148. https://doi.org/10.1155/2012/375148
Cheron, G. ; Duvinage, M. ; De Saedeleer, C. ; Castermans, T. ; Bengoetxea, A. ; Petieau, M. ; Seetharaman, K. ; Hoellinger, T. ; Dan, B. ; Dutoit, T. ; Sylos Labini, F. ; Lacquaniti, F. ; Ivanenko, Y. / From spinal central pattern generators to cortical network : Integrated BCI for walking rehabilitation. In: Neural Plasticity. 2012 ; Vol. 2012.
@article{eb381e3c2fbe447db6a922a1029be879,
title = "From spinal central pattern generators to cortical network: Integrated BCI for walking rehabilitation",
abstract = "Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.",
author = "G. Cheron and M. Duvinage and {De Saedeleer}, C. and T. Castermans and A. Bengoetxea and M. Petieau and K. Seetharaman and T. Hoellinger and B. Dan and T. Dutoit and {Sylos Labini}, F. and F. Lacquaniti and Y. Ivanenko",
year = "2012",
doi = "10.1155/2012/375148",
language = "English",
volume = "2012",
journal = "Neural Plasticity",
issn = "2090-5904",
publisher = "Hindawi Publishing Corporation",

}

TY - JOUR

T1 - From spinal central pattern generators to cortical network

T2 - Integrated BCI for walking rehabilitation

AU - Cheron, G.

AU - Duvinage, M.

AU - De Saedeleer, C.

AU - Castermans, T.

AU - Bengoetxea, A.

AU - Petieau, M.

AU - Seetharaman, K.

AU - Hoellinger, T.

AU - Dan, B.

AU - Dutoit, T.

AU - Sylos Labini, F.

AU - Lacquaniti, F.

AU - Ivanenko, Y.

PY - 2012

Y1 - 2012

N2 - Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

AB - Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

UR - http://www.scopus.com/inward/record.url?scp=84856393142&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856393142&partnerID=8YFLogxK

U2 - 10.1155/2012/375148

DO - 10.1155/2012/375148

M3 - Article

VL - 2012

JO - Neural Plasticity

JF - Neural Plasticity

SN - 2090-5904

M1 - 375148

ER -