Results 11 to 20 of about 226,860 (381)
Bioscience Journal, 2018 The muscle co-contraction is a phenomenon characterized by the simultaneous contraction of two or more muscles around a joint. The objective of this study was to compare the antagonist co-contraction of the local and global trunk muscles during side ...
Frederico Balbino Lizardo +7 more
doaj +3 more sources
Proprioceptive exercise with bosu maximizes electromyographic activity of the ankle muscles
Bioscience Journal, 2017 Ankle sprains are commonly related to sporty activities and often associated with decreases in sensorimotor control, including proprioception, muscle strength and balance.
Frederico Balbino Lizardo +7 more
doaj +3 more sources
FS-HGR: Few-Shot Learning for Hand Gesture Recognition via Electromyography [PDF]
IEEE transactions on neural systems and rehabilitation engineering, 2020 This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their widespread applications in human-machine interfaces. DNNs have been recently used for detecting the intended hand gesture through the processing of surface ...
E. Rahimian +5 more
semanticscholar +1 more source
Italian National Conference on Sensors, 2020 Today, daily life is composed of many computing systems, therefore interacting with them in a natural way makes the communication process more comfortable. Human–Computer Interaction (HCI) has been developed to overcome the communication barriers between
Andrés Jaramillo-Yánez +2 more
semanticscholar +1 more source
Brachial and lumbosacral plexopathies: A review
Clinical Neurophysiology Practice, 2020 Diseases of the brachial and lumbosacral plexus are uncommon and complex. The diagnosis of plexopathies is often challenging for the clinician, both in terms of localizing a patient’s symptoms to the plexus as well as determining the etiology.
Devon I. Rubin
doaj +1 more source
Hand Gesture Recognition Using Compact CNN via Surface Electromyography Signals
Italian National Conference on Sensors, 2020 By training the deep neural network model, the hidden features in Surface Electromyography(sEMG) signals can be extracted. The motion intention of the human can be predicted by analysis of sEMG.
Lin Chen +4 more
semanticscholar +1 more source
Safety of Needle Electromyography in Critically Ill Patients [PDF]
, 2020 Introduction: To evaluate the safety of needle electromyography (EMG) in critically ill intensive care unit (ICU) patients who are on anticoagulants and have comorbidities that increase the risk of bleeding and infections.
Bollu, Pradeep +5 more
core +2 more sources
A study of uterine inertia on the spontaneous of labor using uterine electromyography
Taiwanese Journal of Obstetrics & Gynecology, 2021 Objective: The purpose of this study is to analyze uterine electromyography burst patterns in patients with spontaneous labor and patients with uterine inertia.
Pin Li +5 more
doaj +1 more source
Activation of the gluteus maximus during performance of the back squat, split squat and barbell hip thrust and the relationship with maximal sprinting [PDF]
, 2021 The purpose of this research was to compare muscle activation of the gluteus maximus and ground reaction force between the barbell hip thrust, back squat, and split squat and to determine the relationship between these outcomes and vertical and ...
Andersen +37 more
core +3 more sources
An Investigation Into the Electrical Activity of Tender, Resting Paraspinal Muscles Using Surface Electromyography: A Pilot Study [PDF]
, 1988 Abnormal resting paraspinal muscle activity has been claimed to be responsible for changes in spinal tissue texture which are detectible by manual palpation.
Hubbard, A, Fryer, Gary, Ball, Kevin
core +3 more sources