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Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field of electromyographybased gesture recognition, deep learning algorithms are seldom employed as they require an unreasonable amount of effort from a single person, to generate tens of thousands of examples.
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Cortico-Muscular Coherence Modulated by High-Definition Transcranial Direct Current Stimulation in People With Chronic Stroke
High-definition transcranial direct current stimulation (HD-tDCS) is a potential neuromodulation apparatus for stroke rehabilitation. However, its modulatory effects in stroke subjects is still not well understood.
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Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions
Functional electrical stimulation (FES) is capable of activating muscles that are under-recruited in neurological diseases, such as stroke. Therefore, FES provides a promising technology for assisting upper-limb motor functions in rehabilitation following stroke.
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Voluntary Control of Residual Antagonistic Muscles in Transtibial Amputees: Feedforward Ballistic Contractions and Implications for Direct Neural Control of Powered Lower Limb Prostheses
Discrete, rapid (i.e., ballistic like) muscle activation patterns have been observed in ankle muscles (i.e., plantar flexors and dorsiflexors) of able-bodied individuals during voluntary posture control.
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Shear Waves Reveal Viscoelastic Changes in Skeletal Muscles after Hemispheric Stroke
We investigated alterations in material properties such as elasticity and viscoelasticity of stroke-affected muscles using ultrasound induced shear waves and mechanical models. We used acoustic radiation force to generate shear waves along fascicles of biceps muscles and measured their propagation velocity.
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Comparing Surface and Intramuscular Electromyography for Simultaneous and Proportional Control Based on a Musculoskeletal Model: A Pilot Study
Simultaneous and proportional control (SPC) of neural-machine interfaces uses magnitudes of smoothed electromyograms (EMG) as control inputs. Though surface EMG (sEMG) electrodes are common for clinical neural-machine interfaces, intramuscular EMG (iEMG) electrodes may be indicated in some circumstances (e.g., for controlling many degrees of freedom).
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Myoelectric Control Based on a Generic Musculoskeletal Model: Toward a Multi-User Neural-Machine Interface
This paper aimed to develop a novel electromyography (EMG)-based neural-machine interface (NMI) that is user-generic for continuously predicting coordinated motion between metacarpophalangeal (MCP) and wrist flexion/extension.
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Fine-Wire Electromyography Response to Neuromuscular Electrical Stimulation in the Triceps Surae
Neuromuscular electrical stimulation (NMES) has previously been used to enhance venous return from the lower leg…
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Cross-Comparison of Three Electromyogram Decomposition Algorithms Assessed With Experimental and Simulated Data
The reliability of clinical and scientific information provided by algorithms that automatically decompose the electromyogram (EMG) depends on the algorithms’ accuracies…
