Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients.


Journal

European journal of physical and rehabilitation medicine
ISSN: 1973-9095
Titre abrégé: Eur J Phys Rehabil Med
Pays: Italy
ID NLM: 101465662

Informations de publication

Date de publication:
21 Nov 2023
Historique:
medline: 21 11 2023
pubmed: 21 11 2023
entrez: 21 11 2023
Statut: aheadofprint

Résumé

Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed. We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub-acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end-effector kinematics. We aimed at identifying neural correlates of the participants' upper limb motor function recovery, following an intensive 2-week rehabilitation protocol. Prospective cohort study. Inpatients and outpatients from the Neurorehabilitation Unit of Pisa University Hospital, Italy. Sub-acute and chronic stroke survivors. Thirty-one stroke survivors (14 sub-acute, 17 chronic) with mild-to-moderate UL paresis were enrolled. All participants underwent ten rehabilitative sessions of task-oriented exercises with a planar end-effector robotic device. All patients were evaluated with the Fugl-Meyer Assessment Scale and the Wolf Motor Function Test, at recruitment (T0), end-of-treatment (T1), and one-month follow-up (T2). Along with clinical scales, kinematic parameters and quantitative EEG were collected for each patient. Kinematics metrics were related to velocity, acceleration and smoothness of the movement. Relative power in four frequency bands was extracted from the EEG signals. The evolution over time of kinematic and EEG features was analyzed, in correlation with motor recovery. Both groups displayed significant gains in motility after treatment. Sub-acute patients displayed more pronounced clinical improvements, significant changes in kinematic parameters, and a larger increase in Beta-band in the motor area of the affected hemisphere. In both groups these improvements were associated to a decrease in the Delta-band of both hemispheres. Improvements were retained at T2. The intensive two-week rehabilitation protocol was effective in both chronic and sub-acute patients, and improvements in the two groups shared similar dynamics. However, stronger cortical and behavioral changes were observed in sub-acute patients suggesting different reorganizational patterns. This study paves the way to personalized approaches to UL motor rehabilitation after stroke, as highlighted by different neurophysiological modifications following recovery in subacute and chronic stroke patients.

Sections du résumé

BACKGROUND BACKGROUND
Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed.
AIM OBJECTIVE
We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub-acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end-effector kinematics. We aimed at identifying neural correlates of the participants' upper limb motor function recovery, following an intensive 2-week rehabilitation protocol.
DESIGN METHODS
Prospective cohort study.
SETTING METHODS
Inpatients and outpatients from the Neurorehabilitation Unit of Pisa University Hospital, Italy.
POPULATION METHODS
Sub-acute and chronic stroke survivors.
METHODS METHODS
Thirty-one stroke survivors (14 sub-acute, 17 chronic) with mild-to-moderate UL paresis were enrolled. All participants underwent ten rehabilitative sessions of task-oriented exercises with a planar end-effector robotic device. All patients were evaluated with the Fugl-Meyer Assessment Scale and the Wolf Motor Function Test, at recruitment (T0), end-of-treatment (T1), and one-month follow-up (T2). Along with clinical scales, kinematic parameters and quantitative EEG were collected for each patient. Kinematics metrics were related to velocity, acceleration and smoothness of the movement. Relative power in four frequency bands was extracted from the EEG signals. The evolution over time of kinematic and EEG features was analyzed, in correlation with motor recovery.
RESULTS RESULTS
Both groups displayed significant gains in motility after treatment. Sub-acute patients displayed more pronounced clinical improvements, significant changes in kinematic parameters, and a larger increase in Beta-band in the motor area of the affected hemisphere. In both groups these improvements were associated to a decrease in the Delta-band of both hemispheres. Improvements were retained at T2.
CONCLUSIONS CONCLUSIONS
The intensive two-week rehabilitation protocol was effective in both chronic and sub-acute patients, and improvements in the two groups shared similar dynamics. However, stronger cortical and behavioral changes were observed in sub-acute patients suggesting different reorganizational patterns.
CLINICAL REHABILITATION IMPACT CONCLUSIONS
This study paves the way to personalized approaches to UL motor rehabilitation after stroke, as highlighted by different neurophysiological modifications following recovery in subacute and chronic stroke patients.

Identifiants

pubmed: 37987741
pii: S1973-9087.23.07922-4
doi: 10.23736/S1973-9087.23.07922-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Michael Lassi (M)

The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.

Stefania Dalise (S)

Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy.

Andrea Bandini (A)

The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Health Science Interdisciplinary Research Center, Scuola Superiore Sant'Anna, Pisa, Italy.

Vincenzo Spina (V)

Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy.

Valentina Azzollini (V)

Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy.

Matteo Vissani (M)

The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Harvard Medical School, Boston, MA, USA.
Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA.

Silvestro Micera (S)

The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fèdèrale de Lausanne, Lausanne, Switzerland.

Alberto Mazzoni (A)

The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.

Carmelo Chisari (C)

Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy - c.chisari@ao-pisa.toscana.it.

Classifications MeSH