Robotic therapy: a novel approach in upper-limb neurorehabilitation after stroke

Masiero, Stefano; Carraro, Elena; Celia, Andrea; Rosati, Giulio; Armani, Mario

doi:10.1007/s10072-007-0840-y

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. INTRODUCTION obotic rehabilitation has been proposed as a valuable tool to aid the recovery of motor function after neurological damage [1]. Several approaches on how best to control robotic assistive devices have been described.…”

Section: Takedownmentioning

confidence: 99%

Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans

Semprini

Cuppone

Delis

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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Electrophysiological recordings from human muscles can serve as control signals for robotic rehabilitation devices. Given that many diseases affecting the human sensorimotor system are associated with abnormal patterns of muscle activation, such biofeedback can optimize human-robot interaction and ultimately enhance motor recovery. To understand how mechanical constraints and forces imposed by a robot affect muscle synergies, we mapped the muscle activity of seven major arm muscles in healthy individuals performing goal-directed discrete wrist movements constrained by a wrist robot. We tested six movement directions and four force conditions typically experienced during robotic rehabilitation. We analyzed electromyographic (EMG) signals using a space-by-time decomposition and we identified a set of spatial and temporal modules that compactly described the EMG activity and were robust across subjects. For each trial, coefficients expressing the strength of each combination of modules and representing the underlying muscle recruitment, allowed for a highly reliable decoding of all experimental conditions. The decomposition provides compact representations of the observable muscle activation constrained by a robotic device. Results indicate that a low-dimensional control scheme incorporating EMG biofeedback could be an effective add-on for robotic rehabilitative protocols seeking to improve impaired motor function in humans.

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Section: Takedownmentioning

confidence: 99%

Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans

Semprini

Cuppone

Delis

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Various rehabilitation approaches have been used to improve skill reacquisition of the impaired arm 5 ) . New therapeutic strategies are under investigation in an effort to improve the functional outcomes for UE, including abduction and flexion training 6 , 7 ) , robotics 8 , 9 ) , constraint induced movement therapy 10 , 11 ) , and electrotherapeutics 12 , 13 , 14 , 15 ) . Among these, task-related reaching training (TRT), practice of goal-directed functional movements in a natural environment, has recently become a common rehabilitation approach that addresses these goals.…”

Section: Introductionmentioning

confidence: 99%

Effect of spatial target reaching training based on visual biofeedback on the upper extremity function of hemiplegic stroke patients

Kim

Lee

et al. 2015

J Phys Ther Sci

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[Purpose] The aim of this study was to determine the effect of spatial target reaching training (TRT) based on visual biofeedback (VB) on the upper extremity (UE) function of hemiplegic subjects. [Subjects and Methods] Forty subjects between six and eighteen months post-stroke were enrolled in this study. They were randomly allocated to an experimental group (EG, n=20) and a control group (CG, n=20). All subjects received an hour of routine therapy for stroke three times a week for four weeks. Subjects in EG received additional spatial TRT based on VB using a 2-dimensional motion capture analysis system. Both groups were tested at pre and post-intervention. The motor function of each subject’s UE was assessed using the Fugl-Meyer (FM) test of UE and the Wolf Motor Function Test (WMFT). The reaching speed, angle and maximum reach distance were recorded using the motion capture analysis system. The experimental data were analyzed using the paired and independent t-tests. [Results] The mean change scores of the FM Test of UE and WMFT show there was significantly more improvement at post-intervention in EG than in CG. Also, the speed and angle reached showed significantly more increase in the EG compared with the CG. [Conclusions] The findings indicate that UE motor recovery of hemiplegic stroke patients can be enhanced through the use of TRT based on VB.

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Robotic therapy: a novel approach in upper-limb neurorehabilitation after stroke

Cited by 2 publications

References 3 publications

Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans

Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans

Effect of spatial target reaching training based on visual biofeedback on the upper extremity function of hemiplegic stroke patients

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