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A New Approach to Detection of Muscle Activation by Independent Component Analysis and Wavelet Transform [chapter]

Bruno Azzerboni, Giovanni Finocchio, Maurizio Ipsale, Fabio La Foresta, Francesco Carlo Morabito
2002 Lecture Notes in Computer Science  
In this paper we propose to detect single muscle activation, when the arms reach a target, by means of ICs time-scale decomposition.  ...  In this way we obtain a signal set each representing single muscle activity. The wave-let transform, lastly, is utilised to detect muscle activation intervals.  ...  Then, wavelet analysis is used to detect the activation instant of single muscles.  ... 
doi:10.1007/3-540-45808-5_11 fatcat:dewcfslwyjey3jcafo5sq43gty

Automatic Removal of Artifacts from EEG Signal based on Spatially Constrained ICA using Daubechies Wavelet

Vandana Roy, Shailja Shukla
2014 International Journal of Modern Education and Computer Science  
This is achieved based on higher order statistics of dormant sources, and using the deflation approach Spatially-Constrained Independent Component Analysis (SCICA) to separate the Independent Components  ...  As the next phase, level-4 daubechies wavelet db-4 is applied to extract the brain activity from purged artifacts, and lastly the artifacts are projected back and detracted from EEG signals to get clean  ...  The common signal separation approaches to artifact removal are: principal components analysis, maximum signal fraction analysis, canonical correlation analysis, and independent component analysis.  ... 
doi:10.5815/ijmecs.2014.07.05 fatcat:hwaksujbdnaype5ldjf3a45xi4

Removal of Artifacts from EEG Signals: A Review

Xiao Jiang, Gui-Bin Bian, Zean Tian
2019 Sensors  
Then, a general overview of the state-of-the-art methods and their detail analysis are presented.  ...  However, the recorded electrical activity always be contaminated with artifacts and then affect the analysis of EEG signal.  ...  Wavelet Transform Wavelet transform, transforming a time domain signal into time and frequency domain, has good time-frequency features relative to Fourier transform due to the better tunable time-frequency  ... 
doi:10.3390/s19050987 fatcat:aaj7kldei5clrl7j7g7xi66ih4

Novel Pseudo-Wavelet Function for MMG Signal Extraction during Dynamic Fatiguing Contractions

Mohammed Al-Mulla, Francisco Sepulveda
2014 Sensors  
A genetic algorithm was used to evolve a pseudo-wavelet function for optimizing the detection of muscle fatigue.  ...  Results show that the evolved pseudo-wavelet improved the classification rate of muscle fatigue by 4.70 percentage points to 16.61 percentage points when compared to other standard wavelet functions, giving  ...  Discussion Developing new methods to classify the MMG signal is an interesting approach which is mainly used in the field of prosthetic control and muscle activity research.  ... 
doi:10.3390/s140609489 pmid:24878591 pmcid:PMC4118328 fatcat:kez5mp4avnb3xkybtcjghir7ky

Surface Electromyography Signal Processing and Classification Techniques

Rubana Chowdhury, Mamun Reaz, Mohd Ali, Ashrif Bakar, Kalaivani Chellappan, Tae Chang
2013 Sensors  
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  ...  The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.  ...  Acknowledgments The author would like to thank and acknowledge the medical services of Teknologi Kasihatan dan Perubatan Research Group.  ... 
doi:10.3390/s130912431 pmid:24048337 pmcid:PMC3821366 fatcat:dpmex65sbfgsljq5edqn3qzmki

ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA

Sara Abbaspour, Maria Lindén, Hamid Gholamhosseini
2015 Studies in Health Technology and Informatics  
Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter.  ...  Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal.  ...  Acknowledgment The study was financed by the Knowledge Foundation's research profile Embedded Sensor System for Health (ESS-H).  ... 
pmid:25980853 fatcat:wzlaal2vqjh5zbtpdqzdixs72m

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis

Mojtaba Taherisadr, Omid Dehzangi, Hossein Parsaei
2017 Sensors  
In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its  ...  We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution.  ...  Omid contributed in concept of the study, data analytics, and writing the manuscript. Hossein contributed in data analytics and preparing the manuscript.  ... 
doi:10.3390/s17122895 pmid:29236042 pmcid:PMC5750748 fatcat:ng4p4flsk5bmrp7nwhg4d2q27y

A Comparison of Denoising Methods in Onset Determination in Medial Gastrocnemius Muscle Activations during Stance

Jian Zhang, Rahul Soangra, Thurmon E. Lockhart
2020 Sci  
In order to precisely identify muscle activation and to determine the onset and cessation times of the muscles, we have explored here onset and cessation epochs with denoised EMG signals using different  ...  A comprehensive comparison is discussed on denoising EMG signals using EMD, EEMD, and wavelet denoising in order to accurately define an onset of muscle under different walking conditions.  ...  Acknowledgments: We would like to thank Misha Pavel and Wendy Nilsen for their encouragement in the development of wireless health monitoring systems and fostering the support of wearable wireless health  ... 
doi:10.3390/sci2020039 fatcat:nivipypauzb6hlqrjze32wqcli

A Comparison of Denoising Methods in Onset Determination in Medial Gastrocnemius Muscle Activations during Stance

Jian Zhang, Rahul Soangra, Thurmon E. Lockhart
2020 Sci  
In order to precisely identify muscle activation and to determine the onset and cessation times of the muscles, we have explored here onset and cessation epochs with denoised EMG signals using different  ...  A comprehensive comparison is discussed on denoising EMG signals using EMD, EEMD, and wavelet denoising in order to accurately define an onset of muscle under different walking conditions.  ...  Acknowledgments: We would like to thank Misha Pavel and Wendy Nilsen for their encouragement in the development of wireless health monitoring systems and fostering the support of wearable wireless health  ... 
doi:10.3390/sci2030053 fatcat:d5t5nehfb5eo5jomgtwi4icuca

Artifacts Removal of EEG Signals By the Application of ICA and Double Density DWT Algorithm

Vandana Roy, Shailja Shukla
2014 International Journal of Engineering and Manufacturing  
Independent Component Analysis is used for the automation and detection of brain artifacts. The Independent Component Analysis (ICA) here is used for the segmentation of artifact peaks in the signal.  ...  Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result.  ...  Hence a new and approved method of Independent Component Analysis (ICA) is applied for the detection and removal of artifacts.  ... 
doi:10.5815/ijem.2014.02.04 fatcat:dfjjwiibh5g2picj32j2ys664y

A fully automatic ocular artifact suppression from EEG data using higher order statistics: Improved performance by wavelet analysis

Hosna Ghandeharion, Abbas Erfanian
2010 Medical Engineering and Physics  
In this paper we present a new identification procedure based on an efficient combination of independent component analysis (ICA), mutual information, and wavelet analysis for fully automatic ocular artifact  ...  Independent component analysis (ICA) is now a widely accepted tool for detection of artifacts in EEG data.  ...  Acknowledgment This work supported by Iran Neural Technology Center, Iran University of Science and Technology.  ... 
doi:10.1016/j.medengphy.2010.04.010 pmid:20466582 fatcat:u3zc2qyrabazphptjxrlp2qkve

sEMG Techniques to Detect and Predict Localised Muscle Fatigue [chapter]

M. R., F. Sepulveda, M. Colley
2012 EMG Methods for Evaluating Muscle and Nerve Function  
Wavelet analysis By using a wavelet function (WF), the wavelet transform (WT) decomposes a signal into numerous multi-resolution components (Kleissen et al., 1998; Laterza & Olmo, 1997) .  ...  Another method for estimating muscle fatigue during dynamic contraction is to use a source separation technique related to independent component analysis to test whether the firing of MUs becomes more  ...  SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force, ICS'08: Proceedings of the 12th WSEAS international conference on systems, World  ... 
doi:10.5772/25678 fatcat:2opemtcg4nedjc7mr5wayhkza4

A novel method of identifying motor primitives using wavelet decomposition

Anton Popov, Erienne V. Olesh, Sergiy Yakovenko, Valeriya Gritsenko
2018 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN)  
The method allows to quantify coincident activation of muscle groups caused by the physiological processes of fixed duration, thus enabling the extraction of wavelet modules of arbitrary groups of muscles  ...  .; Yakovenko, Sergiy; and Gritsenko, Valeriya, "A novel method of identifying motor primitives using wavelet decomposition" (Abstract This study reports a new technique for extracting muscle synergies  ...  The wavelet modules obtained with this method detected co-activation between two or more muscles that occurred at a selected biomimetic temporal scale determined by the wavelet mother function scaled to  ... 
doi:10.1109/bsn.2018.8329674 pmid:29756041 pmcid:PMC5942196 dblp:conf/bsn/PopovOYG18 fatcat:7xrexykc45aydim7vyvmuavydy

Wavelet analysis for detection of phasic electromyographic activity in sleep: Influence of mother wavelet and dimensionality reduction

Jacqueline A. Fairley, George Georgoulas, Otis L. Smart, George Dimakopoulos, Petros Karvelis, Chrysostomos D. Stylios, David B. Rye, Donald L. Bliwise
2014 Computers in Biology and Medicine  
High rates of such activity may have clinical relevance. This paper presents wavelet (WT) analyses to detect phasic EMG, examining both Symlet and Daubechies approaches.  ...  Feature extraction included 1s epoch processing with 24 WT-based features and dimensionality reduction involved comparing two techniques: principal component analysis and a feature/variable selection algorithm  ...  "Action support post-doctoral fellows of the Operational Programme Education and Lifelong Learning" of the Greek Ministry of Education, Lifelong Learning and Religious Affairs, co-financed by the European  ... 
doi:10.1016/j.compbiomed.2013.12.011 pmid:24657906 pmcid:PMC4169047 fatcat:gwtemlal6nf7bbdhgnnb5l7zey

Spatial and Transform Domain Filtering Method for Image De-noising: A Review

Vandana Roy
2013 International Journal of Modern Education and Computer Science  
The search on efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics.  ...  One filter in each category has been taken in consideration to understand the characteristics of both spatial and transform do main filters.  ...  In this paper authors presented a new algorith m using a merger of Independent Component Analysis and Translation Invariant Wavelet Transform.  ... 
doi:10.5815/ijmecs.2013.07.05 fatcat:3ckk6hm65bdodeummg7bbi35ye
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