Transactions on Neural Systems and Rehabilitation Engineering

Articles
Characterization of a Benchmark Database for Myoelectric Movement Classification
In this paper, we characterize the Ninapro database and its use as a benchmark for hand prosthesis evaluation. The database is a publicly available resource that aims to support research on advanced myoelectric hand prostheses. The database is obtained by... Read more
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Design and Preliminary Assessment of a Passive Elastic Leg Exoskeleton for Resistive Gait Rehabilitation
While devices that assist walking can enable individuals with neuromusculoskeletal impairments, recovery is often better facilitated by devices that resist walking. Moreover, current robotic interfaces for gait rehabilitation are typically huge, bulky, and come with a large price tag. This article describes the design and development of a novel, wearable, passive elastic exoskeleton for resistive gait rehabilitation. The system uses counteracting compressional springs, pulleys, and clutches and can be configured to resist flexion, extension, or bidirectionally. Thus, the device can target user-specific muscle weaknesses and accommodate range of motion limitations. These concepts were validated using benchtop and human subject experiments... Read more
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Experimental results using force-feedback cueing in robot-assisted stroke therapy
Abstract:Stroke is the leading cause of disability among adults in the United States. Behaviors such as learned nonuse hinder hemiplegic stroke survivors from the full use of both arms in activities of daily living. Active force-feedback cues, designed to restrain... Read more
Articles
Semi-automated control system for reaching movements in EMG shoulder disarticulation prosthesis based on mixed reality device
Goal: The development of a control system for an electromyographic shoulder disarticulation (EMG-SD) prosthesis to rapidly achieve a task with a reduction in the operational failure of the user. Methods: The motion planning of an EMG-SD prosthesis was automated using... Read more
Articles
Massage Therapy’s Effectiveness on the decoding EEG rhythms of Left/Right Motor Imagery and Motion Execution in Patients with Skeletal Muscle Pain
Objective: Most of effectiveness assessments of the widely-used Massage therapy were based on subjective routine clinical assessment tools, such as Visual Analogue Scale (VAS) score. However, few studies demonstrated the impact of massage on the Electroencephalograph (EEG) rhythm decoding of... Read more
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Should Hands Be Restricted When Measuring Able-Bodied Participants to Evaluate Machine Learning Controlled Prosthetic Hands?
When evaluating methods for machine-learning controlled prosthetic hands, able-bodied participants are often recruited, for practical reasons, instead of participants with upper limb absence (ULA). However, able-bodied participants have been shown to often perform myoelectric control tasks better than participants with ULA... Read more
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Adaptive Spatial Filtering of High-Density EMG for Reducing the Influence of Noise and Artefacts in Myoelectric Control
Electromyography (EMG) is a source of neural information for controlling neuroprosthetic devices. To enhance the information content of conventional bipolar EMG, high-density EMG systems include tens to hundreds of closely spaced electrodes that non-invasively record the electrical activity of muscles with high spatial resolution... Read more
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Stable Responsive EMG Sequence Prediction and Adaptive Reinforcement with Temporal Convolutional Networks
Movement prediction from EMG can be performed by compressing a short window of EMG into a feature-encoding that is meaningful for classification— an approach that can cause erratic prediction behavior. Temporal convolutional networks (TCN) leverage temporal information from EMG to achieve superior predictions for 3 simultaneous degrees-of-freedom that are more accurate and stable, have a very low response delay, and allow for novel types of interactive training. Addressing EMG decoding as a sequential prediction problem requires a new set of considerations that will lead to enhancements in the reliability, responsiveness, and movement complexity available from prosthesis control systems... Read more
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Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex
Understanding how the human brain controls locomotion is a considerable neuroscience challenge that has required advancements in mobile neuroimaging methods. Mobile high-density electroencephalography (EEG) allows electrical brain activity to be measured non-invasively during gait, but these signals are prone to... Read more
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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... Read more