AIMC Topic: Electromyography
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Robust Real-Time Embedded EMG Recognition Framework Using Temporal Convolutional Networks on a Multicore IoT Processor.
IEEE transactions on biomedical circuits and systems
Dec 11, 2019
Hand movement classification via surface electromyographic (sEMG) signal is a well-established approach for advanced Human-Computer Interaction. However, sEMG movement recognition has to deal with the long-term reliability of sEMG-based control, limi...
Estimating Biomechanical Time-Series with Wearable Sensors: A Systematic Review of Machine Learning Techniques.
Sensors (Basel, Switzerland)
Nov 28, 2019
Wearable sensors have the potential to enable comprehensive patient characterization and optimized clinical intervention. Critical to realizing this vision is accurate estimation of biomechanical time-series in daily-life, including joint, segment, a...
A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG and Deep Learning.
IEEE transactions on biomedical circuits and systems
Nov 25, 2019
This paper presents a real-time fine gesture recognition system for multi-articulating hand prosthesis control, using an embedded convolutional neural network (CNN) to classify hand-muscle contractions sensed at the forearm. The sensor consists in a ...
The Effect of Optic Flow Speed on Active Participation During Robot-Assisted Treadmill Walking in Healthy Adults.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Nov 25, 2019
This study aimed to investigate: 1) the effect of optic flow speed manipulation on active participation during robot-assisted treadmill walking (RATW), 2) the influence of the type of virtual environment, and 3) the level of motion sickness and enjoy...
Muscle endurance time estimation during isometric training using electromyogram and supervised learning.
Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Nov 16, 2019
UNLABELLED: Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earlier studies have shown that muscle fatigue characteristics can be used for evaluating muscle enduranc...
Adaptive Calibration of Electrode Array Shifts Enables Robust Myoelectric Control.
IEEE transactions on bio-medical engineering
Nov 11, 2019
OBJECTIVE: The objective of this work is to develop a novel method for adaptive calibration of the electrode array shifts toward achieving robust myoelectric pattern-recognition control.
Comparison of Bagging and Boosting Ensemble Machine Learning Methods for Automated EMG Signal Classification.
BioMed research international
Oct 31, 2019
The neuromuscular disorders are diagnosed using electromyographic (EMG) signals. Machine learning algorithms are employed as a decision support system to diagnose neuromuscular disorders. This paper compares bagging and boosting ensemble learning met...
Myoelectric Control of a Soft Hand Exoskeleton Using Kinematic Synergies.
IEEE transactions on biomedical circuits and systems
Oct 28, 2019
Soft hand exoskeletons offer a lightweight, low-profile alternative to rigid rehabilitative robotic systems, enabling their use to restore activities of daily living (ADL) in those with hand paresis due to stroke or other conditions. The hand exoskel...
Machine learning prediction of emesis and gastrointestinal state in ferrets.
PloS one
Oct 18, 2019
Although electrogastrography (EGG) could be a critical tool in the diagnosis of patients with gastrointestinal (GI) disease, it remains under-utilized. The lack of spatial and temporal resolution using current EGG methods presents a significant roadb...
A Subject-Transfer Framework Based on Single-Trial EMG Analysis Using Convolutional Neural Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 11, 2019
In recent years, electromyography (EMG)-based practical myoelectric interfaces have been developed to improve the quality of daily life for people with physical disabilities. With these interfaces, it is very important to decode a user's movement int...
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