Literature DB >> 23060345

EMG-based visual-haptic biofeedback: a tool to improve motor control in children with primary dystonia.

Claudia Casellato1, Alessandra Pedrocchi, Giovanna Zorzi, Lea Vernisse, Giancarlo Ferrigno, Nardo Nardocci.   

Abstract

New insights suggest that dystonic motor impairments could also involve a deficit of sensory processing. In this framework, biofeedback, making covert physiological processes more overt, could be useful. The present work proposes an innovative integrated setup which provides the user with an electromyogram (EMG)-based visual-haptic biofeedback during upper limb movements (spiral tracking tasks), to test if augmented sensory feedbacks can induce motor control improvement in patients with primary dystonia. The ad hoc developed real-time control algorithm synchronizes the haptic loop with the EMG reading; the brachioradialis EMG values were used to modify visual and haptic features of the interface: the higher was the EMG level, the higher was the virtual table friction and the background color proportionally moved from green to red. From recordings on dystonic and healthy subjects, statistical results showed that biofeedback has a significant impact, correlated with the local impairment, on the dystonic muscular control. These tests pointed out the effectiveness of biofeedback paradigms in gaining a better specific-muscle voluntary motor control. The flexible tool developed here shows promising prospects of clinical applications and sensorimotor rehabilitation.

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Year:  2012        PMID: 23060345     DOI: 10.1109/TNSRE.2012.2222445

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  6 in total

1.  A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback.

Authors:  Borja Gamecho; Hugo Silva; José Guerreiro; Luis Gardeazabal; Julio Abascal
Journal:  J Med Syst       Date:  2015-08-30       Impact factor: 4.460

2.  Comparison of speed-accuracy tradeoff between linear and nonlinear filtering algorithms for myocontrol.

Authors:  Cassie N Borish; Adam Feinman; Matteo Bertucco; Natalie G Ramsy; Terence D Sanger
Journal:  J Neurophysiol       Date:  2018-01-31       Impact factor: 2.714

3.  Brain-Computer Interfaces for Treatment of Focal Dystonia.

Authors:  Kristina Simonyan; Stefan K Ehrlich; Richard Andersen; Jonathan Brumberg; Frank Guenther; Mark Hallett; Matthew A Howard; José Del R Millán; Richard B Reilly; Tanja Schultz; Davide Valeriani
Journal:  Mov Disord       Date:  2022-08-10       Impact factor: 9.698

Review 4.  A survey on robotic devices for upper limb rehabilitation.

Authors:  Paweł Maciejasz; Jörg Eschweiler; Kurt Gerlach-Hahn; Arne Jansen-Troy; Steffen Leonhardt
Journal:  J Neuroeng Rehabil       Date:  2014-01-09       Impact factor: 4.262

5.  EMG-based vibro-tactile biofeedback training: effective learning accelerator for children and adolescents with dystonia? A pilot crossover trial.

Authors:  Claudia Casellato; Emilia Ambrosini; Andrea Galbiati; Emilia Biffi; Ambra Cesareo; Elena Beretta; Francesca Lunardini; Giovanna Zorzi; Terence D Sanger; Alessandra Pedrocchi
Journal:  J Neuroeng Rehabil       Date:  2019-11-27       Impact factor: 4.262

6.  Artificial neural network EMG classifier for functional hand grasp movements prediction.

Authors:  Marta Gandolla; Simona Ferrante; Giancarlo Ferrigno; Davide Baldassini; Franco Molteni; Eleonora Guanziroli; Michele Cotti Cottini; Carlo Seneci; Alessandra Pedrocchi
Journal:  J Int Med Res       Date:  2016-09-27       Impact factor: 1.671

  6 in total

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