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Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition
2017
Sensors
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To evaluate the performance of the new EMD based method, ERS was computed from the basic and IMF signals. ...
Analyses are based on power spectral density computing in the band of interest using time-frequency analyses. ...
Signal processing methods, such as extraction of power spectral density (PSD) [6] , wavelet analysis [7] , independent component analysis (ICA) [8] , and local mean decomposition [9] , are used to ...
doi:10.3390/s17050989
pmid:28468250
pmcid:PMC5469342
fatcat:ccgohwq7fngtrhrbeczl4gotke
Filtering of surface EMG using ensemble empirical mode decomposition
2013
Medical Engineering and Physics
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The experimental results demonstrated that the EMD based methods achieved better performance than the conventional digital filters, especially when the signal to noise ratio of the processed signal was ...
Surface electromyogram (EMG) is often corrupted by three types of noises, i.e. power line interference (PLI), white Gaussian noise (WGN), and baseline wandering (BW). ...
Sample surface EMG recordings from the thenar group muscles of amyotrophic lateral sclerosis patients were used for this analysis [15] . ...
doi:10.1016/j.medengphy.2012.10.009
pmid:23245684
pmcid:PMC3769943
fatcat:iogqezvzsfeynago43sd4gshie
A Novel Quantitative Spasticity Evaluation Method Based on Surface Electromyogram Signals and Adaptive Neuro Fuzzy Inference System
2020
Frontiers in Neuroscience
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Before treatment of spasticity, there are often practical demands for objective and quantitative assessment of muscle spasticity. ...
To evaluate spasticity conveniently, a novel spasticity evaluation method based on surface electromyogram (sEMG) signals and adaptive neuro fuzzy inference system (i.e., the sEMG-ANFIS method) was presented ...
LX and YC designed the research and participated in the data collection and revisions of the manuscripts. QC, KM, and HZ participated in the data collection and analysis of the results. ...
doi:10.3389/fnins.2020.00462
pmid:32523505
pmcid:PMC7261936
fatcat:x5rhxzypcjcrre6fqh5kx3vqpe
Surface Electromyography Signal Processing and Classification Techniques
2013
Sensors
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Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and ...
of the different methods for processing and classifying EMG signals. ...
Conflicts of Interest The authors declare no conflict of interest. Sensors 2013, 13 ...
doi:10.3390/s130912431
pmid:24048337
pmcid:PMC3821366
fatcat:dpmex65sbfgsljq5edqn3qzmki
Automated Channel Selection in High-Density sEMG for Improved Force Estimation
2020
Sensors
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We developed and validated new approaches for selecting subsets of high-density (HD) EMG channels for improved and lower-dimensionality force estimation. ...
To select a subset of channels, principal component analysis (PCA) in the frequency domain and a novel index called the power-correlation ratio (PCR), which maximizes the spectral power while minimizing ...
Acknowledgments: The authors would like to thank Behnam Behinaein for his help and valuable discussions throughout this work.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s20174858
pmid:32867378
fatcat:rrfsvqjwkjftte7n3ngs7wtd4m
A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions
2016
Sensors
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For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. ...
This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s16081304
pmid:27548165
pmcid:PMC5017469
fatcat:wuvnfahaxnbpfbcgyibzji4kde
Classification of Cervical Disc Herniation Disease using Muscle Fatigue based surface EMG signals by Artificial Neural Networks
2017
International Journal of Intelligent Systems and Applications in Engineering
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In the first step of this study, EMG signals were filtered and adapted for analysis. ...
This study has contributed that AR and DWT are a suitable feature extraction methods for surface EMG signals by providing high accuracy classification with artificial intelligence methods for cervical ...
Subaşı ve Kıymık aimed to determine muscle fatigue in biceps by time-frequency methods and independent component analysis (ICA). ...
doi:10.18201/ijisae.2017533901
fatcat:56kugtsdhrbsfe2bzqhjrkhek4
Achieving Neural Compatibility with Human Sensorimotor Control in Prosthetic and Therapeutic Devices
2019
IEEE Transactions on Medical Robotics and Bionics
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Prosthetic and therapeutic devices have been developed to ameliorate the quality of daily living for people with amputation or neurological disorders. ...
control, natural module of synergy-based control, as well as advanced neural signal processing techniques. ...
B:
Fig. 4 . 4 Paradigm of synergy-based therapeutic FES for post-stroke upper extremity training and assessment. ...
doi:10.1109/tmrb.2019.2930356
fatcat:srs6eddhqjaydnpro6tsmndrrq
Topographical Characteristics of Motor Units of the Lower Facial Musculature Revealed by Means of High-Density Surface EMG
2006
Journal of Neurophysiology
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This was done by the analysis of motor unit action potentials (MUAPs) in the surface electromyogram. ...
Topographical characteristics of motor units of the lower facial musculature revealed by means of high-density surface EMG. . ...
This was done by the analysis of motor unit action potentials (MUAPs) in the surface electromyogram. ...
doi:10.1152/jn.00265.2005
pmid:16000526
fatcat:hnuuy6336zhkhm7ibui2cdzqiu
Fuzzy-Based Automatic Epileptic Seizure Detection Framework
2022
Computers Materials & Continua
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The empirical evaluation of the proposed model was conducted on the benchmark Bonn EEG dataset. ...
The proposed work extracts pattern features along with time-domain, frequencydomain, and non-linear analysis of signals. ...
In this method, Blind Source Separation of Canonical Correlation Analysis (BSSCCA) and Independent Component Analysis (ICA) removed Electromyogram (EMG) and Electrooculogram (EOG) artifacts, respectively ...
doi:10.32604/cmc.2022.020348
fatcat:yqsfnkzy3jeflgijk3hfboc4py
Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal
2018
Sensors
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It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published ...
methods of signal processing and have good accuracy and speed of algorithms. ...
Conflicts of Interest: The authors declare no conflicts of interest. ...
doi:10.3390/s18113648
fatcat:x3k6uromwzarpdsfobeogh5zk4
Properties of the surface electromyogram following traumatic spinal cord injury: a scoping review
2021
Journal of NeuroEngineering and Rehabilitation
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as well as to take fuller advantage of high-density EMG techniques. ...
Enhanced sEMG analysis could contribute to a more complete description of the effects of SCI on upper and lower motor neuron function and their interactions, and also assist in understanding the mechanisms ...
Acknowledgements We would like to acknowledge the direct and indirect support of the Rehabilitation Translational Continuum (ReCon) team, which was supported by the ...
doi:10.1186/s12984-021-00888-2
pmid:34187509
fatcat:efb3t3n7pva4jfjux774bdqp5y
Motor-commands decoding using peripheral nerve signals: a review
2018
Journal of Neural Engineering
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We also discuss the types of interfaces available and their applications, the kinds of peripheral nerve signals that are used, and the algorithms used to decode them. ...
Finally, we explore the prospects for future development in this area. ...
Acknowledgment This work was supported by the National Research Foun dation (NRF) of Korea under the auspices of the Ministry of Science and ICT, Republic of Korea (grant nos. ...
doi:10.1088/1741-2552/aab383
pmid:29498358
fatcat:uvh3wcjb3jc4vbce6hi2nrhdiq
Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control
2020
Frontiers in Neurology
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This study characterized, for the first time, the forearm high-density (HD) electromyograms of three individuals with DMD while performing seven hand/wrist-related tasks and compared them to eight healthy ...
We looked into the spatial distribution of HD-sEMG patterns by using principal component analysis (PCA) and also assessed the repeatability and the amplitude distributions of muscle activity. ...
In DMD individuals, the support of the upper extremity is central for ensuring daily life independence (7) . ...
doi:10.3389/fneur.2020.00231
pmid:32351441
pmcid:PMC7174775
fatcat:gxhoksjuljdedb6vizp6nhsa6u
A non-invasive brain-machine interface via independent control of individual motor units
[article]
2021
bioRxiv
pre-print
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These results demonstrate a yet-unexplored level of flexibility of the peripheral sensorimotor system and show that this can be exploited to create novel non-invasive, high-performance BMIs. ...
Concomitantly, dimensionality of the motor unit population increased significantly relative to naturalistic behaviors, largely violating recruitment orders displayed during stereotyped, isometric muscle ...
Tracking motor units longitudinally across experimental 937 sessions with high-density surface electromyography: Motor unit tracking with high-density 938 EMG. J. ...
doi:10.1101/2021.03.22.436518
fatcat:te6a45x52rdhngfdlq27yhlzre
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