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Quantitative EEG for predicting upper limb motor recovery in chronic stroke robot-Assisted rehabilitation

Academic Article
Publication Date:
2017
abstract:
Stroke is a leading cause for adult disability, which in many cases causes motor deficits. Despite the developments in motor rehabilitation techniques, recovery of upper limb functions after stroke is limited and heterogeneous in terms of outcomes, and knowledge of important factors that may affect the outcome of the therapy is necessary tomake a reasonable prediction for individual patients. In this paper, we assessed the relationship between quantitative electroencephalographic (QEEG) measures and the motor outcome in chronic stroke patients that underwent a robot-Assisted rehabilitation program to evaluate the utility ofQEEG indices to predictmotor recovery. For this purpose, we acquired resting-state electroencephalographic signals fromwhich the power ratio index (PRI), delta/alpha ratio, and brain symmetry index were calculated. The outcome of the motor rehabilitationwas evaluated using upper limb section of the Fugl-Meyer Assessment. We found that PRI was significantly correlatedwith themotor recovery, suggesting that this indexmay provide useful information to predict the rehabilitation outcome. Index Terms-Chronic stroke, robot-Assisted rehabilitation, quantitative electroencephalography(QEEG), outcome prediction.
Iris type:
01.01 Articolo in rivista
Keywords:
Chronic stroke; robot-assisted rehabilitation; quantitative electroencephalography(QEEG); outcome prediction.
List of contributors:
Caimmi, Marco; Chiavenna, Andrea; Mastropietro, Alfonso; TRUJILLO DIAZ, Paula; Rizzo, Giovanna; MRAKIC SPOSTA, Simona; Scano, Alessandro
Authors of the University:
CAIMMI MARCO
MASTROPIETRO ALFONSO
MRAKIC SPOSTA SIMONA
RIZZO GIOVANNA
SCANO ALESSANDRO
Handle:
https://iris.cnr.it/handle/20.500.14243/340222
Published in:
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
Journal
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URL

https://ieeexplore.ieee.org/document/7870705/authors#authors
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