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   Articles with "emg signals" as a keyword



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DWT-based electromyogram signal classification using maximum likelihood-estimated features for neurodiagnostic applications

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recommendations! Published in 2020 at "Signal, Image and Video Processing"

DOI: 10.1007/s11760-019-01590-6

Abstract: Automated diagnosis of neuromuscular disorders such as myopathy and neuropathy can be done by measuring and analyzing the nonlinear and non-stationary trends in electromyogram (EMG) signals. This paper introduces a new automated diagnostic approach with… read more here.

Keywords: classification; dwt based; maximum likelihood; based electromyogram ... See more keywords

A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG

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recommendations! Published in 2017 at "Computers in biology and medicine"

DOI: 10.1016/j.compbiomed.2017.02.006

Abstract: Many studies have demonstrated the feasibility and benefits of Conduction Velocity (CV) estimation from surface electromyograms (EMGs) in various experimental conditions. Among them, a method based on optical flow was proposed recently, demonstrating relatively accurate… read more here.

Keywords: estimation; emg; velocity estimation; conduction velocity ... See more keywords

Percentage estimation of muscular activity of the forearm by means of EMG signals based on the gesture recognized using CNN

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recommendations! Published in 2020 at "Sensing and bio-sensing research"

DOI: 10.1016/j.sbsr.2020.100353

Abstract: Abstract Within muscle activity based on surface electromyographic (EMG) signals, the percentage estimate of muscle activation, which is the level of intensity with which muscles have been activated, has not been exploited. This work presents… read more here.

Keywords: estimation; percentage estimation; gesture; emg signals ... See more keywords

StressFit: a hybrid wearable physicochemical sensor suite for simultaneously measuring electromyogram and sweat cortisol

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recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-81042-5

Abstract: This study introduces StressFit, a novel hybrid wearable sensor system designed to simultaneously monitor electromyogram (EMG) signals and sweat cortisol levels. Our approach involves the development of a noninvasive skin patch capable of monitoring skin… read more here.

Keywords: sweat cortisol; sensor; emg signals; hybrid wearable ... See more keywords

Toward a generalizable deep CNN for neural drive estimation across muscles and participants

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recommendations! Published in 2022 at "Journal of Neural Engineering"

DOI: 10.1088/1741-2552/acae0b

Abstract: Objective. High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit (MU) spike trains, which collectively constitute the neural code of movements, to predict motor intent. This approach has advanced from offline to… read more here.

Keywords: emg signals; neural drive; drive estimation; cnn ... See more keywords

Day-to-Day Stability of Wrist EMG for Wearable-Based Hand Gesture Recognition

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3225761

Abstract: Wrist electromyography (EMG) signals have been explored for incorporation into subtle wrist-worn wearable devices for decoding hand gestures. Previous studies have now shown that wrist EMG can even outperform the more commonly used forearm EMG,… read more here.

Keywords: emg signals; day; emg; forearm emg ... See more keywords

Development of Consumer-Friendly Surface Electromyography System for Muscle Fatigue Detection

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3237557

Abstract: In this study, a low-cost, wireless, and smartphone-controlled surface electromyography (EMG) system was designed and developed for consumers, and the recorded EMG signals were evaluated against a reference laboratory EMG system during fatiguing contraction. Using… read more here.

Keywords: emg signals; system; consumer friendly; emg ... See more keywords

Comparing EMG Continuous Movement Decoding With Joints Unconstrained and Constrained

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recommendations! Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3191533

Abstract: Electromyography (EMG) signals have been employed for continuous movement decoding in recent years. However, several studies demonstrated that due to physiological factors, the EMG signals of amputees were poorer with respect to that of the… read more here.

Keywords: continuous movement; emg signals; movement; mcp wrist ... See more keywords
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Deep Learning for Robust Decomposition of High-Density Surface EMG Signals

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recommendations! Published in 2021 at "IEEE Transactions on Biomedical Engineering"

DOI: 10.1109/tbme.2020.3006508

Abstract: Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trains. Once the separation matrix is… read more here.

Keywords: density surface; high density; emg signals; decomposition ... See more keywords

Diagnosis of Neuromuscular Disorders Using DT-CWT and Rotation Forest Ensemble Classifier

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recommendations! Published in 2020 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2019.2918596

Abstract: Electromyographic (EMG) signals are utilized to analyze the neuromuscular disorders. Machine learning algorithms have been employed as a decision support system to detect neuromuscular disorders. EMG signals contain noise from different sources, such as electrical… read more here.

Keywords: emg signals; forest ensemble; neuromuscular disorders; rotation forest ... See more keywords

Hardware Implementation for Lower Limb Surface EMG Measurement and Analysis Using Explainable AI for Activity Recognition

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recommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2022.3198443

Abstract: Electromyography (EMG) signals are gaining popularity for several biomedical applications, including pattern recognition, disease detection, human–machine interfaces, medical image processing, and robotic limb or exoskeleton fabrication. In this study, a two-channel data acquisition system for… read more here.

Keywords: emg signals; limb; activity recognition; lower limb ... See more keywords