J Neuroeng Rehabil
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Case Reports
Two ways to improve myoelectric control for a transhumeral amputee after targeted muscle reinnervation: a case study.
Myoelectric control of multifunctional prostheses is challenging for individuals with high-level amputations due to insufficient surface electromyography (sEMG) signals. A surgical technique called targeted muscle reinnervation (TMR) has achieved impressive improvements in myoelectric control by providing more sEMG control signals. In this case, some channels of sEMG signals are coupled after TMR, which limits the performance of conventional amplitude-based control for upper-limb prostheses. ⋯ Although the sEMG signals were still coupled after rehabilitation training on the TMR patient, the online performance of the prosthetic operation was improved through application of PR control with combination of the MAV-based threshold switches.
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Randomized Controlled Trial
Shaping neuroplasticity by using powered exoskeletons in patients with stroke: a randomized clinical trial.
The use of neurorobotic devices may improve gait recovery by entraining specific brain plasticity mechanisms, which may be a key issue for successful rehabilitation using such approach. We assessed whether the wearable exoskeleton, Ekso™, could get higher gait performance than conventional overground gait training (OGT) in patients with hemiparesis due to stroke in a chronic phase, and foster the recovery of specific brain plasticity mechanisms. ⋯ Ekso™ gait training seems promising in gait rehabilitation for post-stroke patients, besides OGT. Our study proposes a putative neurophysiological basis supporting Ekso™ after-effects. This knowledge may be useful to plan highly patient-tailored gait rehabilitation protocols.
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Freezing of gait and falls represent a major burden in patients with advanced forms of Parkinson's disease (PD). These axial motor signs are not fully alleviated by drug treatment or deep-brain stimulation. Recently, virtual reality has emerged as a rehabilitation option for these patients. In this pilot study, we aim to determine the feasibility and acceptability of rehabilitation with a customised videogame to treat gait and balance disorders in PD patients, and assess its effects on these disabling motor signs. ⋯ This study suggests that rehabilitation with a customised videogame to treat gait and balance disorders is feasible, well accepted, and effective in parkinsonian patients. These data serve as preliminary evidence for further larger and controlled studies to propose this customised videogame rehabilitation programme at home.
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Impairment of hand and finger function after stroke is common and affects the ability to perform activities of daily living. Even though many of these coordination deficits such as finger individuation have been well characterized, it is critical to understand how stroke survivors learn to explore and reorganize their finger coordination patterns for optimizing rehabilitation. In this study, I examine the use of a body-machine interface to assess how participants explore their movement repertoire, and how this changes with continued practice. ⋯ Stroke survivors show deficits in movement repertoire in their paretic hand, but facilitating movement exploration during training can increase the movement repertoire. This suggests that exploration may be an important element of rehabilitation to regain optimal function.
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NLR, MLP, SVM, and LDA: a comparative analysis on EMG data from people with trans-radial amputation.
Currently, the typically adopted hand prosthesis surface electromyography (sEMG) control strategies do not provide the users with a natural control feeling and do not exploit all the potential of commercially available multi-fingered hand prostheses. Pattern recognition and machine learning techniques applied to sEMG can be effective for a natural control based on the residual muscles contraction of amputated people corresponding to phantom limb movements. As the researches has reached an advanced grade accuracy, these algorithms have been proved and the embedding is necessary for the realization of prosthetic devices. The aim of this work is to provide engineering tools and indications on how to choose the most suitable classifier, and its specific internal settings for an embedded control of multigrip hand prostheses. ⋯ The proposed analysis would provide innovative engineering tools and indications on how to choose the most suitable classifier based on the application and the desired results for prostheses control.