The Promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response.


Journal

BMC neurology
ISSN: 1471-2377
Titre abrégé: BMC Neurol
Pays: England
ID NLM: 100968555

Informations de publication

Date de publication:
27 Jun 2020
Historique:
received: 21 05 2020
accepted: 10 06 2020
entrez: 29 6 2020
pubmed: 1 7 2020
medline: 21 10 2020
Statut: epublish

Résumé

Stroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The "Promotoer" study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements. This longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures. We expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice. Name of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer). NCT04353297 ; registration date on the ClinicalTrial.gov platform: April, 15/2020.

Sections du résumé

BACKGROUND BACKGROUND
Stroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The "Promotoer" study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements.
METHODS METHODS
This longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures.
DISCUSSION CONCLUSIONS
We expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice.
TRIAL REGISTRATION BACKGROUND
Name of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer).
TRIAL REGISTRATION NUMBER BACKGROUND
NCT04353297 ; registration date on the ClinicalTrial.gov platform: April, 15/2020.

Identifiants

pubmed: 32593293
doi: 10.1186/s12883-020-01826-w
pii: 10.1186/s12883-020-01826-w
pmc: PMC7320550
doi:

Banques de données

ClinicalTrials.gov
['NCT04353297']

Types de publication

Clinical Trial Protocol Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

254

Subventions

Organisme : Ministero della Salute
ID : RF-2018-12365210

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Auteurs

Donatella Mattia (D)

Fondazione Santa Lucia, IRCCS, Rome, Italy. d.mattia@hsantalucia.it.

Floriana Pichiorri (F)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Emma Colamarino (E)

Fondazione Santa Lucia, IRCCS, Rome, Italy.
Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Rome, Italy.

Marcella Masciullo (M)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Giovanni Morone (G)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Jlenia Toppi (J)

Fondazione Santa Lucia, IRCCS, Rome, Italy.
Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Rome, Italy.

Iolanda Pisotta (I)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Federica Tamburella (F)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Matteo Lorusso (M)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Stefano Paolucci (S)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

Maria Puopolo (M)

Istituto Superiore di Sanità, Rome, Italy.

Febo Cincotti (F)

Fondazione Santa Lucia, IRCCS, Rome, Italy.
Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Rome, Italy.

Marco Molinari (M)

Fondazione Santa Lucia, IRCCS, Rome, Italy.

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