AIMC Topic: Electromyography

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Differences in muscle activity and fatigue of the upper limb between Task-Specific training and robot assisted training among individuals post stroke.

Journal of biomechanics Apr 10, 2019
OBJECTIVE: To compare the activity and fatigue of upper extremity muscles, pain levels, subject satisfaction levels, perceived exertion, and number of repetitions in Task-Specific Training (TST) compared with Robot-Assisted Training (RAT) in individu...
Male Stroke Rehabilitation Female Middle Aged Aged Adolescent Young Adult Robotics Electromyography Adult Humans Stroke Upper Extremity Muscles
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A CNN-Based Method for Intent Recognition Using Inertial Measurement Units and Intelligent Lower Limb Prosthesis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 9, 2019
Powered intelligent lower limb prosthesis can actuate the knee and ankle joints, allowing transfemoral amputees to perform seamless transitions between locomotion states with the help of an intent recognition system. However, prior intent recognition...
Algorithms Adult Biomechanical Phenomena Male Prosthesis Design Electromyography Humans Calibration Intention Neural Networks, Computer Locomotion Amputees Machine Learning Recognition, Psychology Walking Artificial Limbs
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Detection of movement onset using EMG signals for upper-limb exoskeletons in reaching tasks.

Journal of neuroengineering and rehabilitation Mar 29, 2019
BACKGROUND: To assist people with disabilities, exoskeletons must be provided with human-robot interfaces and smart algorithms capable to identify the user's movement intentions. Surface electromyographic (sEMG) signals could be suitable for this pur...
Electromyography Movement Exoskeleton Device Upper Extremity Machine Learning Female Adult Male Humans
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A deep learning-based decision support system for diagnosis of OSAS using PTT signals.

Medical hypotheses Mar 27, 2019
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...
Motivation Middle Aged Medical Informatics Deep Learning Sleep Wake Disorders Decision Support Systems, Clinical Electrocardiography Humans Female Neural Networks, Computer Aged Sleep Apnea, Obstructive Support Vector Machine Algorithms Adult Carbon Dioxide Electroencephalography Male Heart Rate Signal Processing, Computer-Assisted Healthy Volunteers Electromyography
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Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 25, 2019
Research on machine learning approaches for upper-limb prosthesis control has shown impressive progress. However, translating these results from the lab to patient's everyday lives remains a challenge because advanced control schemes tend to break do...
Humans Machine Learning Algorithms Signal Processing, Computer-Assisted Transfer, Psychology Electrodes Electromyography Patient Satisfaction Amputees Pattern Recognition, Automated Artificial Limbs Upper Extremity Prosthesis Design
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EMG Muscle Activation Pattern of Four Lower Extremity Muscles during Stair Climbing, Motor Imagery, and Robot-Assisted Stepping: A Cross-Sectional Study in Healthy Individuals.

BioMed research international Mar 25, 2019
BACKGROUND: Stair climbing can be a challenging part of daily life and a limiting factor for social participation, in particular for patients after stroke. In order to promote motor relearning of stair climbing, different therapeutical measures can b...
Robotics Electromyography Male Walking Humans Middle Aged Physical Therapy Modalities Female Lower Extremity Stair Climbing Aged Quadriceps Muscle Cross-Sectional Studies
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Regression convolutional neural network for improved simultaneous EMG control.

Journal of neural engineering Mar 8, 2019
OBJECTIVE: Deep learning models can learn representations of data that extract useful information in order to perform prediction without feature engineering. In this paper, an electromyography (EMG) control scheme with a regression convolutional neur...
Electromyography Humans Motion Neural Networks, Computer Random Allocation Movement Female Adult Male Regression Analysis Machine Learning
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Offline and online myoelectric pattern recognition analysis and real-time control of a robotic hand after spinal cord injury.

Journal of neural engineering Mar 5, 2019
OBJECTIVE: The objective of this study was to investigate the feasibility of applying myoelectric pattern recognition for controlling a robotic hand in individuals with spinal cord injury (SCI).
Adult Male Middle Aged Computer Systems Humans Female Aged Spinal Cord Injuries Exoskeleton Device Robotics Hand Electromyography Pattern Recognition, Automated
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Improving Reliability of Myocontrol Using Formal Verification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 5, 2019
In the context of assistive robotics, myocontrol is one of the so-far unsolved problems of upper-limb prosthetics. It consists of swiftly, naturally, and reliably converting biosignals, non-invasively gathered from an upper-limb disabled subject, int...
Self-Help Devices Young Adult Adult Male Robotics Electromyography Prosthesis Design Psychomotor Performance Upper Extremity Humans Algorithms Female Reproducibility of Results
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Development of a deep neural network for automated electromyographic pattern classification.

The Journal of experimental biology Mar 4, 2019
Determining the signal quality of surface electromyography (sEMG) recordings is time consuming and requires the judgement of trained observers. An automated procedure to evaluate sEMG quality would streamline data processing and reduce time demands. ...
Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Electromyography
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