Interfacing brain with computer to improve communication and rehabilitation after brain damage

Riccio, Angela; Pichiorri, Floriana; Schettini, Francesca; Toppi, Jlenia; Risetti, Monica; Formisano, Rita; Molinari, Marco; Astolfi, Laura; Cincotti, Febo; Mattia, Donatella

doi:10.1016/bs.pbr.2016.04.018

Cited by 30 publications

(21 citation statements)

References 151 publications

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“…In fact, most of common rehabilitation tools require a minimal level of motor control to perform the therapeutic tasks; therefore, patients with severe motor deficits are not allowed to accomplish traditional rehabilitation training. Some recent reviews have presented and discussed main advances in the use of BCIs for rehabilitation purposes [ 5 – 7 ]. A further work has discussed the current status of BCI as a rehabilitation strategy in stroke patients [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation

Carelli

Solca

Faini

et al. 2017

BioMed Research International

101

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Alongside the best-known applications of brain-computer interface (BCI) technology for restoring communication abilities and controlling external devices, we present the state of the art of BCI use for cognitive assessment and training purposes. We first describe some preliminary attempts to develop verbal-motor free BCI-based tests for evaluating specific or multiple cognitive domains in patients with Amyotrophic Lateral Sclerosis, disorders of consciousness, and other neurological diseases. Then we present the more heterogeneous and advanced field of BCI-based cognitive training, which has its roots in the context of neurofeedback therapy and addresses patients with neurological developmental disorders (autism spectrum disorder and attention-deficit/hyperactivity disorder), stroke patients, and elderly subjects. We discuss some advantages of BCI for both assessment and training purposes, the former concerning the possibility of longitudinally and reliably evaluating cognitive functions in patients with severe motor disabilities, the latter regarding the possibility of enhancing patients' motivation and engagement for improving neural plasticity. Finally, we discuss some present and future challenges in the BCI use for the described purposes.

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Section: Introductionmentioning

confidence: 99%

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation

Carelli

Solca

Faini

et al. 2017

BioMed Research International

101

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“…RAIN computer interface (BCI) based on motor imagination (MI) has wide range of applications, spanning from spellers to assistive devices [1][2][3][4][5][6][7]. Yet MI BCI has most often been used as a part of rehabilitative and assistive systems to repair or restore motor functions.…”

Section: Introductionmentioning

confidence: 99%

“…Yet MI BCI has most often been used as a part of rehabilitative and assistive systems to repair or restore motor functions. This is due to its reliance on the activity of the sensory-motor cortex [4,6]. For these applications, MI-BCI is typically combined with virtual reality, functional electrical stimulation or robots.…”

Section: Introductionmentioning

confidence: 99%

“…A Vuckovic is with the Biomedical Engineering, School of Engineering, University of Glasgow, G12 8QQ, UK (email: Aleksandra.vuckovic@glasgow.ac.uk). extremities in stroke patients and patients with incomplete spinal cord injury [4][5][6] and assistive devices for people with complete high level spinal cord injury (tetraplegia) for restoration of motor functions [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…Although many activities of daily living require use of both hands [8], most MI BCI rehabilitation systems have been designed to assist single limb movements [1][2][3][4][5][6][7]. Applications range from the detection of MI of different limbs to detection of direction, speed and target location of a single limb [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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Unimanual Versus Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces

Vučković

Pangaro

Putri

2018

IEEE Trans. Neural Syst. Rehabil. Eng.

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Bimanual movements are an integral part of everyday activities and are often included in rehabilitation therapies. Yet electroencephalography (EEG) based assistive and rehabilitative brain computer interface (BCI) systems typically rely on motor imagination (MI) of one limb at the time. In this study we present a classifier which discriminates between uni-and bimanual MI. Ten able bodied participants took part in cue based motor execution (ME) and MI tasks of the left (L), right (R) and both (B) hands. A 32 channel EEG was recorded. Three linear discriminant analysis classifiers, based on MI of L-B, B-R and B-L hands were created, with features based on wide band Common Spatial Patterns (CSP) 8-30 Hz, and band specifics Common Spatial Patterns (CSPb). Event related desynchronization (ERD) was significantly stronger during bimanual compared to unimanual ME on both hemispheres. Bimanual MI resulted in bilateral parietally shifted ERD of similar intensity to unimanual MI. The average classification accuracy for CSP and CSPb was comparable for L-R task (73±9% and 75±10% respectively) and for L-B task (73±11% and 70±9% respectively). However, for R-B task (67±3% and 72±6% respectively) it was significantly higher for CSPb (p=0.0351). Six participants whose L-R classification accuracy exceeded 70% were included in an on-line task a week later, using the unmodified offline CSPb classifier, achieving 69±3% and 66±3% accuracy for the L-R and R-B tasks respectively. Combined uni and bimanual BCI could be used for restoration of motor function of highly disabled patents and for motor rehabilitation of patients with motor deficits.

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An All-in-One BCI-Supported Motor Imagery Training Station: Validation in a Real Clinical Setting with Chronic Stroke Patients

Pichiorri

Colamarino

Cincotti

et al. 2018

Biosystems &Amp; Biorobotics

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Interfacing brain with computer to improve communication and rehabilitation after brain damage

Cited by 30 publications

References 151 publications

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation

Unimanual Versus Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces

An All-in-One BCI-Supported Motor Imagery Training Station: Validation in a Real Clinical Setting with Chronic Stroke Patients

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