Purpose: The purpose of this study is to evaluate the efficacy of surface electrical stimulation on the spasticity occurring in the wrist flexor muscles after a cerebrovascular event.
Method: Hemiplegic patients with stage 2-3 spasticity in the wrist muscles based on the Ashworth scale were divided into two groups. Both groups were applied stretching. One group was additionally administered neuromuscular electrical stimulation (NMES) to the wrist extensors, in the form of pulsed current, 100 Hz, with a pulse duration of 0.1 msec, and a resting duration of 9 seconds, for 15 minutes to provide the maximum muscular contraction. The efficacy of the treatment was evaluated using the following: modified Ashworth scale (MAS), Fmax/Mmax ratio, Hmax/Mmax ratio, wrist extension range of motion (ROM). The daily activities were assessed by Functional Independence Measurement (FIM) and the motor recovery was evaluated by Brunnstrom motor staging.
Results: Both groups revealed a significant recovery after the treatment based on the MAS, the electrophysiological evaluation results, wrist ROM, FIM and Brunnstrom motor staging. The group receiving the combined treatment showed a better recovery in terms of MAS, wrist ROM, FIM and Brunnstrom motor staging compared to the group doing the stretching alone.
Conclusions: The results of this study showed that NMES given together with stretching of the wrist extensor muscles was more effective than stretching of the wrist extensor muscles alone in reducing spasticity.
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http://dx.doi.org/10.3109/09638288.2011.593679 | DOI Listing |
Sci Rep
December 2024
State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China.
Microelectrode arrays (MEAs) have been widely used in studies on the electrophysiological features of neuronal networks. In classic MEA experiments, spike or burst rates and spike waveforms are the primary characteristics used to evaluate the neuronal network excitability. Here, we introduced a new method to assess the excitability using the voltage threshold of electrical stimulation.
View Article and Find Full Text PDFNat Commun
December 2024
Neuroengineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Peripheral neuropathy (PN), the most common complication of diabetes, leads to sensory loss and associated health issues as pain and increased fall risk. However, present treatments do not counteract sensory loss, but only partially manage its consequences. Electrical neural stimulation holds promise to restore sensations, but its efficacy and benefits in PN damaged nerves are yet unknown.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Psychology, Cornell University, Ithaca, NY, USA.
Subjective feelings are thought to arise from conceptual and bodily states. We examine whether the valence of feelings may also be decoded directly from objective ecological statistics of the visual environment. We train a visual valence (VV) machine learning model of low-level image statistics on nearly 8000 emotionally charged photographs.
View Article and Find Full Text PDFEpilepsia
December 2024
Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia.
Objective: The 5xFAD mouse model of Alzheimer disease (AD) recapitulates amyloid-beta (Aβ) deposition and pronounced seizure susceptibility observed in patients with AD. Forty-hertz audiovisual stimulation is a noninvasive technique that entrains gamma neural oscillations and can reduce Aβ pathology and modulate glial expression in AD models. We hypothesized that 40-Hz sensory stimulation would improve seizure susceptibility in 5xFAD mice and this would be associated with reduction of plaques and modulation of glial phenotypes.
View Article and Find Full Text PDFHum Brain Mapp
January 2025
Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Espoo, Finland.
State-of-the-art navigated transcranial magnetic stimulation (nTMS) systems can display the TMS coil position relative to the structural magnetic resonance image (MRI) of the subject's brain and calculate the induced electric field. However, the local effect of TMS propagates via the white-matter network to different areas of the brain, and currently there is no commercial or research neuronavigation system that can highlight in real time the brain's structural connections during TMS. This lack of real-time visualization may overlook critical inter-individual differences in brain connectivity and does not provide the opportunity to target brain networks.
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