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Navigating public environments requires adjustments to one's walking patterns to avoid stationary and moving obstacles. It is known that physical inactivity induces alterations in motor capacities, but the impact of inactivity on anticipatory locomotor adjustments (ALA) has not been studied. The purpose of the present exploratory study was to compare ALAs and related muscle co-contraction during a pedestrian circumvention task between active (AA) and inactive young adults (IA).

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Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study.

J Neuroeng Rehabil

January 2025

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Vita Stråket 12, Floor 4, 41346, Gothenburg, Sweden.

Background: Myoelectric pattern recognition (MPR) combines multiple surface electromyography channels with a machine learning algorithm to decode motor intention with an aim to enhance upper limb function after stroke. This study aims to determine the feasibility and preliminary effectiveness of a novel intervention combining MPR, virtual reality (VR), and serious gaming to improve upper limb function in people with chronic stroke.

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Evaluation of flavor perception of strong-aroma Baijiu based on electroencephalography (EEG) and surface electromyography (EMG) techniques.

Food Chem

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Department of Food Science & Technology, School of Agriculture & Biology, Shanghai Jiao Tong University, Shanghai 200240, China; School of Food Science and Engineering, Ningxia University, Yinchuan 750021, China. Electronic address:

This study investigates the flavor perception of strong-aroma Baijiu through physiological electrical signals, focusing on electroencephalography (EEG) and electromyography (EMG) during olfactory and gustatory evaluations. It examines how sensory qualities, especially mellowness, influence brain and muscle responses. Results showed significant differences in EEG δ and β wavebands, mainly in the frontal and temporal lobes, reflecting varying brain activities across Baijiu types.

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Objective: Creating an intracortical brain-computer interface (iBCI) capable of seamless transitions between tasks and contexts would greatly enhance user experience. However, the nonlinearity in neural activity presents challenges to computing a global iBCI decoder. We aimed to develop a method that differs from a globally optimized decoder to address this issue.

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Opioid dependence is defined by an aversive withdrawal syndrome upon drug cessation that can motivate continued drug-taking, development of opioid use disorder, and precipitate relapse. An understudied but common opioid withdrawal symptom is disrupted sleep, reported as both insomnia and daytime sleepiness. Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions.

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