J Neuroeng Rehabil
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Millions of patients around the world are affected by neurological and psychiatric disorders. Deep brain stimulation (DBS) is a device-based therapy that could have fewer side-effects and higher efficiencies in drug-resistant patients compared to other therapeutic options such as pharmacological approaches. Thus far, several efforts have been made to incorporate a feedback loop into DBS devices to make them operate in a closed-loop manner. ⋯ The promising clinical effects of open-loop DBS have been demonstrated, indicating DBS as a pioneer technology and treatment option to serve neurological patients. However, like other commercial devices, DBS needs to be automated and modernized.
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Electrical stimulation of the peripheral nerves has been shown to be effective in restoring sensory and motor functions in the lower and upper extremities. This neural stimulation can be applied via non-penetrating spiral nerve cuff electrodes, though minimal information has been published regarding their long-term performance for multiple years after implantation. ⋯ The spiral nerve cuffs examined remain functional in motor and sensory neuroprostheses for 2-11 years after implantation. They exhibit stable charge thresholds, clinically relevant recruitment properties, and functional muscle selectivity. Non-penetrating spiral nerve cuff electrodes appear to be a suitable option for long-term clinical use on human peripheral nerves in implanted neuroprostheses.
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Limb prosthetics, exoskeletons, and neurorehabilitation devices can be intuitively controlled using myoelectric pattern recognition (MPR) to decode the subject's intended movement. In conventional MPR, descriptive electromyography (EMG) features representing the intended movement are fed into a classification algorithm. The separability of the different movements in the feature space significantly affects the classification complexity. Classification complexity estimating algorithms (CCEAs) were studied in this work in order to improve feature selection, predict MPR performance, and inform on faulty data acquisition. ⋯ This study deepens the understanding of the classification complexity in prediction of motor volition based on myoelectric information. It also provides researchers with tools to analyze myoelectric recordings in order to improve classification performance.
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Randomized Controlled Trial
The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial.
Many studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations. ⋯ The robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance.
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There is a need for objective movement assessment for clinical research trials aimed at improving gait and balance in persons with multiple sclerosis (PwMS). Wireless inertial sensors can accurately measure numerous walking and balance parameters but these measures require evaluation of reliability in PwMS. The current study determined the test-retest reliability of wireless inertial sensor measures obtained during an instrumented standing balance test and an instrumented Timed Up and Go test in PwMS. ⋯ Measures from the instrumented standing balance and instrumented TUG tests exhibit good to excellent reliability, demonstrating their potential as objective assessments for clinical trials. A subset of the most reliable measures is recommended for measuring walking and balance in clinical settings.