AIMC Topic: Electromyography

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Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition.

Computers in biology and medicine Mar 25, 2020
Convolutional Neural Networks (CNNs) have been subject to extensive attention in the pattern recognition literature due to unprecedented performance in tasks of information extraction from unstructured data. Whereas available methods for supervised t...
Movement Databases, Factual Electromyography Neural Networks, Computer Algorithms
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Robot-Driven Locomotor Perturbations Reveal Synergy-Mediated, Context-Dependent Feedforward and Feedback Mechanisms of Adaptation.

Scientific reports Mar 25, 2020
Humans respond to mechanical perturbations that affect their gait by changing their motor control strategy. Previous work indicates that adaptation during gait is context dependent, and perturbations altering long-term stability are compensated for e...
Adult Male Robotics Electromyography Muscle, Skeletal Humans Female Feedback, Physiological Reference Values Gait Disorders, Neurologic Walking Leg Gait Adaptation, Physiological
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Laser-Induced Graphene for Electrothermally Controlled, Mechanically Guided, 3D Assembly and Human-Soft Actuators Interaction.

Advanced materials (Deerfield Beach, Fla.) Mar 16, 2020
Mechanically guided, 3D assembly has attracted broad interests, owing to its compatibility with planar fabrication techniques and applicability to a diversity of geometries and length scales. Its further development requires the capability of on-dema...
Biomimetics Graphite Fingers Robotics Electromyography Muscles Lasers, Gas Finite Element Analysis Temperature Wearable Electronic Devices Humans
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Performance Evaluation of Convolutional Neural Network for Hand Gesture Recognition Using EMG.

Sensors (Basel, Switzerland) Mar 15, 2020
Electromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still ins...
Electromyography Artificial Limbs Gestures Signal Processing, Computer-Assisted Hand Adult Male Humans Algorithms Young Adult Neural Networks, Computer
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A Myoelectric Control Interface for Upper-Limb Robotic Rehabilitation Following Spinal Cord Injury.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 10, 2020
Spinal cord injury (SCI) is a widespread, life-altering injury leading to impairment of sensorimotor function that, while once thought to be permanent, is now being treated with the hope of one day being able to restore function. Surface electromyogr...
Exoskeleton Device Humans Robotics Upper Extremity Robotic Surgical Procedures Electromyography Spinal Cord Injuries
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Assistance Robotics and Biosensors 2019.

Sensors (Basel, Switzerland) Feb 29, 2020
This Special Issue is focused on breakthrough developments in the field of assistive and rehabilitation robotics. The selected contributions include current scientific progress from biomedical signal processing and cover applications to myoelectric p...
Exoskeleton Device Electroencephalography Biosensing Techniques Prostheses and Implants Robotics Electromyography
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High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network.

Sensors (Basel, Switzerland) Feb 21, 2020
High-density surface electromyography (HD-sEMG) and deep learning technology are becoming increasingly used in gesture recognition. Based on electrode grid data, information can be extracted in the form of images that are generated with instant value...
Neural Networks, Computer Deep Learning Humans Electromyography Gestures
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Feature Extraction of Surface Electromyography Based on Improved Small-World Leaky Echo State Network.

Neural computation Feb 18, 2020
Surface electromyography (sEMG) is an electrophysiological reflection of skeletal muscle contractile activity that can directly reflect neuromuscular activity. It has been a matter of research to investigate feature extraction methods of sEMG signals...
Muscle, Skeletal Electromyography Neural Networks, Computer Algorithms Humans
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Identification of the best strategy to command variable stiffness using electromyographic signals.

Journal of neural engineering Feb 18, 2020
OBJECTIVE: In the last decades, many EMG-controlled robotic devices were developed. Since stiffness control may be required to perform skillful interactions, different groups developed devices whose stiffness is real-time controlled based on EMG sign...
Wrist Isometric Contraction Male Exoskeleton Device Robotics Electromyography Range of Motion, Articular Young Adult Adult Female Muscle Fatigue Humans
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Deep Learning in Physiological Signal Data: A Survey.

Sensors (Basel, Switzerland) Feb 11, 2020
Deep Learning (DL), a successful promising approach for discriminative and generative tasks, has recently proved its high potential in 2D medical imaging analysis; however, physiological data in the form of 1D signals have yet to be beneficially expl...
Humans Electroencephalography Signal Processing, Computer-Assisted Electromyography Deep Learning Electrocardiography Databases, Factual
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