Direct current (DC) nerve block has been shown to provide a complete block of nerve conduction without unwanted neural firing. Previous work shows that high capacitance electrodes can be used to safely deliver a DC block. Another way of delivering DC safely is through a separated interface nerve electrode (SINE), such that any reactive species that are generated by the passage of DC are contained in a vessel away from the nerve.
Electroencephalography (EEG) is an effective non-invasive measurement method to infer user intent in brain-computer interface (BCI) systems for control and communication, however, these systems often lack sufficient accuracy and speed due to low separability of class-conditional EEG feature distributions. Many factors impact system performance, including inadequate training datasets and models’ ignorance of the temporal dependency of brain responses to serial stimuli.
Lower-limb exoskeletons used to improve free-living mobility for individuals with neuromuscular impairment must be controlled to prescribe assistance that adapts to the diverse locomotor conditions encountered during daily life, including walking at different speeds and across varied terrain.
Trans-spinal Direct Current Stimulation (tsDCS) is a technique considered for the treatment of corticospinal damage or dysfunction. TsDCS aims to induce functional modulation in the corticospinal circuitry via a direct current (DC) generated electric field.
The rapid increase in the number of older adults around the world is accelerating research in applications to support age-related conditions, such as brain–computer interface (BCI) applications for post-stroke neurorehabilitation.
Here, we present the design of a novel unpowered ankle exoskeleton that is low profile, lightweight, quiet, and low cost to manufacture, intrinsically adapts to different walking speeds, and does not restrict non-sagittal joint motion; while still providing assistive ankle torque that can reduce demands on the biological calf musculature.
Shoes were invented to provide user comfort using rubber soles, despite marginal improvement in human mobility. Unlike shoes, current lower-limb exoskeletons use fixed stiffness springs to store and recycle energy to improve mobility.
More and more studies propose that high frequency brain signals are promising biomarkers of epileptogenic zone. In this paper, our aim is to investigate the neuromagnetic changes and brain network topological alterations during an interictal period at high frequency ranges (80–1000 Hz) between healthy controls and epileptic patients with Magnetoencephalography.
Data-driven spatial filtering algorithms optimize scores, such as the contrast between two conditions to extract oscillatory brain signal components. Most machine learning approaches for the filter estimation, however, disregard within-trial temporal dynamics and are extremely sensitive to changes in training data and involved hyperparameters.
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.