Filters








145 Hits in 5.4 sec

Machine Learning-Based Epileptic Seizure Detection Methods Using Wavelet and EMD-Based Decomposition Techniques: A Review

Rabindra Gandhi Thangarajoo, Mamun Bin Ibne Reaz, Geetika Srivastava, Fahmida Haque, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Mohammad Arif Sobhan Bhuiyan
<span title="2021-12-20">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
This paper intends to review the relevant studies of wavelet and empirical mode decomposition-based feature extraction techniques used for seizure detection in epileptic EEG data.  ...  Epileptic seizures are temporary episodes of convulsions, where approximately 70 percent of the diagnosed population can successfully manage their condition with proper medication and lead a normal life  ...  [11] used the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) for extracting features from EEG signals [45] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21248485">doi:10.3390/s21248485</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34960577">pmid:34960577</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8703715/">pmcid:PMC8703715</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rqtwgpqna5bx7nebddapbhwunu">fatcat:rqtwgpqna5bx7nebddapbhwunu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211228104702/https://mdpi-res.com/d_attachment/sensors/sensors-21-08485/article_deploy/sensors-21-08485.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fc/ec/fcec2f77642dc1cde8ee17b087b68146db51ab8c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21248485"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8703715" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Detecting Epileptic Seizures in EEG Signals with Complementary Ensemble Empirical Mode Decomposition and Extreme Gradient Boosting

Wu, Zhou, Li
<span title="2020-01-24">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
To achieve accurate detection of epileptic seizures, an automatic detection approach of epileptic seizures, integrating complementary ensemble empirical mode decomposition (CEEMD) and extreme gradient  ...  Epilepsy is a common nervous system disease that is characterized by recurrent seizures. An electroencephalogram (EEG) records neural activity, and it is commonly used for the diagnosis of epilepsy.  ...  discrete wavelet transform; SVM: support vector machine; KNN: k-nearest neighbor; NB: naive Bayes; CEEMDAN: complete ensemble empirical mode decomposition with adaptive noise; LPBoost: linear programming  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e22020140">doi:10.3390/e22020140</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33285915">pmid:33285915</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7516550/">pmcid:PMC7516550</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pgutkpnmljdszfjalja26cmh6i">fatcat:pgutkpnmljdszfjalja26cmh6i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209084039/https://res.mdpi.com/d_attachment/entropy/entropy-22-00140/article_deploy/entropy-22-00140.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/77/67/77672912c705ee741d2b1637e7556a3fddf98fe8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e22020140"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516550" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Minireview of Epilepsy Detection Techniques Based on Electroencephalogram Signals

Guangda Liu, Ruolan Xiao, Lanyu Xu, Jing Cai
<span title="2021-05-20">2021</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/j33hgvvadjhazfxeupgxga54ai" style="color: black;">Frontiers in Systems Neuroscience</a> </i> &nbsp;
Epilepsy is one of the most common neurological disorders typically characterized by recurrent and uncontrollable seizures, which seriously affects the quality of life of epilepsy patients.  ...  The application of seizure prediction and localization based on EEG signals in the diagnosis of epilepsy was also introduced.  ...  Hassan and Subasi (2016) proposed a new signal processing scheme for EEG signal segments, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnsys.2021.685387">doi:10.3389/fnsys.2021.685387</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34093143">pmid:34093143</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8173051/">pmcid:PMC8173051</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j5xweg7bcjez5cc53ltm3ttuwe">fatcat:j5xweg7bcjez5cc53ltm3ttuwe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210521070404/https://fjfsdata01prod.blob.core.windows.net/articles/files/685387/pubmed-zip/.versions/1/.package-entries/fnsys-15-685387/fnsys-15-685387.pdf?sv=2018-03-28&amp;sr=b&amp;sig=wVRSq2hKQjC0fsv2H6WUVCSGP96mtRSBCwBv0%2FcMv4g%3D&amp;se=2021-05-21T07%3A04%3A33Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fnsys-15-685387.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/69/10/6910964f1149d752dd8d25eeab946818e8f2d053.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnsys.2021.685387"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173051" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Review on diverse approaches used for epileptic seizure detection using EEG signals

K Baskar, C Karthikeyan
<span title="2018-09-19">2018</span> <i title="Bangladesh Journals Online (JOL)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ugy5izhebje5djfui6dfg774ga" style="color: black;">Bangladesh Journal of Medical Science</a> </i> &nbsp;
Further, this study summarizes various methods used previously to analyze the epilepsy and seizures based on its state of art approach.  ...  This study reviews different approaches, which is been designed to aid the human diagnosis using new avenues that explains the causes of epilepsy and seizures.  ...  function 30 , multi domain wavelet threshold 44 , harmonic wavelet packet transform 36 , Stockwell transform 38 , ensemble empirical mode decomposition 37 , Multivariate Empirical Mode Decomposition 14  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3329/bjms.v17i4.38307">doi:10.3329/bjms.v17i4.38307</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oppbo2aznvfjdmyvxtfarxwer4">fatcat:oppbo2aznvfjdmyvxtfarxwer4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190427155401/https://www.banglajol.info/index.php/BJMS/article/download/38307/26082" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a6/4a/a64a42468865d14616cf7caea0061ad87e8f2a46.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3329/bjms.v17i4.38307"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Epileptic Seizures Detection Based on Empirical Mode Decomposition of EEG Signals [chapter]

Lorena Orosco, Agustina Garces, Eric Laciar
<span title="2011-09-15">2011</span> <i title="InTech"> Management of Epilepsy - Research, Results and Treatment </i> &nbsp;
methods based on the Empirical Mode Decomposition (EMD) of EEG signals has been proposed.On one hand, the use of EMD for seizures detection it is a recent approach.In addition, as a contribution to the  ...  Empirical Mode Decomposition In the last years, a technique called Empirical Mode Decomposition (EMD) has been proposed for the analysis of non-linear and non-stationary series (Huang et al., 1998) .  ...  Epilepsy is one of the most common neurological disorders, with a prevalence of 4-10/1000.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/18302">doi:10.5772/18302</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wy3zw7khivgnfhnbpknwxdldn4">fatcat:wy3zw7khivgnfhnbpknwxdldn4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180729022232/https://api.intechopen.com/chapter/pdf-download/17817" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/12/b3/12b339a1849b956ccdaf6869cae47cb8d9188533.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/18302"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Epileptic EEG Classification by Using Advanced Signal Decomposition Methods [chapter]

Ozlem Karabiber Cura, Aydin Akan
<span title="2020-10-05">2020</span> <i title="IntechOpen"> Epilepsy [Working Title] </i> &nbsp;
In this chapter, advanced signal analysis methods such as Empirical Mode Decomposition (EMD), Ensembe (EMD), Dynamic mode decomposition (DMD), and Synchrosqueezing Transform (SST) are utilized to classify  ...  Electroencephalography (EEG) signals are frequently used for the detection of epileptic seizures.  ...  EMD [7, 8, 22 ] and its derivative approaches such as bivariate empirical mode decomposition (BEMD) [23] , multivariate empirical Mode Decomposition (MEMD) [24] , ensemble Empirical Mode Decomposition  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.93810">doi:10.5772/intechopen.93810</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wbay7jszdbeqron7aqtxpfunee">fatcat:wbay7jszdbeqron7aqtxpfunee</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201018191100/https://api.intechopen.com/chapter/pdf-download/73285.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/68/9d/689dc19b7d9114166f4f766aa61325f7e2c31977.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.93810"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Comparison of empirical mode decomposition and coarse-grained procedure for detecting pre-ictal and ictal condition in electroencephalography signal

Inung Wijayanto, Rudy Hartanto, Hanung Adi Nugroho
<span title="">2020</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vusydvbzgfck3ik2qu2c5h4zea" style="color: black;">Informatics in Medicine Unlocked</a> </i> &nbsp;
The first is to decompose EEG signals by using empirical mode decomposition (EMD) and a coarse-grained (CG) procedure to obtain signal information in multiple scales.  ...  Please cite this article as: Wijayanto I, Hartanto R, Nugroho HA, Comparison of empirical mode decomposition and coarse-grained procedure for detecting pre-ictal and ictal condition in electroencephalography  ...  [63] Weighted Permutation Entropy + Lin SVM A-E 99.5 - - Weighted Permutation Entropy + Non-Lin SVM A-E 99 - - Hassan et al. [64] Complete ensemble EMD with adaptive noise + LPBoost A-E 100  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.imu.2020.100325">doi:10.1016/j.imu.2020.100325</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/m2ia7llo7zemleyxvkm7eolnim">fatcat:m2ia7llo7zemleyxvkm7eolnim</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200415040113/https://pdf.sciencedirectassets.com/312075/AIP/1-s2.0-S2352914820300137/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEGwaCXVzLWVhc3QtMSJHMEUCIQCAyDqNDrkk1%2BI%2BzqTRlFICIdIu8p4oh1nrhs3oPzDs6QIgWvCrn848KSINlY%2FMz29Ebzi9owfLTpGoNPV2CKa3O2oqvQMIhf%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FARADGgwwNTkwMDM1NDY4NjUiDB6BDgOMrxllZ%2BxLfyqRA4vKqWCnEV3%2Bc0ucHbBE7DIoWcWnfmSw2lWzToHcsErBDIbzaebupEMyoJiog1Fg7mBsc0WkrdU0ZxKjymM6j4W4%2B4As86ykxDuveTkjNNEmOLyudT4wq27QLtvWWZX7qhxIxhx4bJ9w5tRgL0ZZEdiNkKMfhHRBSasurQKLGBKW71fStwaqPhRX4%2FE0j%2FDYqs9BqUCuBCTzVP5Dk%2BVoJwVz%2F%2Fad8KcyTk9TayERrdRT%2BKuu2VBUcWWdvBTbBemBVF1eA5UnFiW9urwpVz1yQBp1LsGU1Py2zFx90XD7LxjAYjwkLnSAeAzkXCivhudJWNMQ%2FvECD8sjGP5YFA8rcrmthwB8iHwV8iVOdly2K2B3LrKd%2F6YFehX5d7gtG7XaZmc3kV4SWECVmS6zpjO6NchkMfvyjRk5oKhu9l8AK8zUTDQ0kO0iEVrnk922trpcoRD9ZlCarr3edUMS3mTfIg7L5NgFCbt%2FoRUB3smik%2FKTQsVx8Q%2BoEWEGplj55mtKjQNoMruWKQgW58pduY7hYxGHMK792fQFOusB%2BZZAEp5HlZOfh0ZJZDTrkjPl9His%2F6nSQlc16YvRz%2Bn74eLWWmLoOgS%2BWoNdeNwE5xj9rChclCP98coiB44eZAzcMttsWfYZkcQlxwHIRbsve2UaYAFRtvR%2B7UpxW00aLu1%2FRtI5svG%2FkXw9nO6M5hn6l%2FQxpOrGXiDBCn0HKxDxJsN5nTbaK6AEltACZBjqu2St6m6sO1u7p4xt1FSNlXjRFUKfdxEs6tLalVD5IFs%2BEEq4%2BF9ixKIPMPDKerxSTRvGVw15T%2FLPYlY%2BdTx4uwAXaeh2z7Po%2FUIpAiWHZdiW4KVFj0YrSqekgw%3D%3D&amp;X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20200415T035745Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=300&amp;X-Amz-Credential=ASIAQ3PHCVTY44BYXHJD%2F20200415%2Fus-east-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=41eb0b3a8d74dd0ad1f60c3cff15a1da83e5ebea3f66fb726b760d66769739f6&amp;hash=11d73d8727884429abf8976bad00849b50c28c2f64da9c29fa902226a38f7795&amp;host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&amp;pii=S2352914820300137&amp;tid=spdf-0e5aad07-1145-4e45-8b14-de4d2f096cd4&amp;sid=4860aea455dac64e2b799678c5c7790d42cegxrqa&amp;type=client" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f4/cf/f4cf8bd6bd78e2e82d2fe334ece399a20f6c3143.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.imu.2020.100325"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

Machine learning applications for electroencephalograph signals in epilepsy: a quick review

Yang Si
<span title="2020-04-29">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dc6ns5niezd3fjvm6mouohekhy" style="color: black;">Acta Epileptologica</a> </i> &nbsp;
The present review examines various ML approaches for electroencephalograph (EEG) signal procession in epilepsy research, highlighting applications in the aspect of automated seizure detection, prediction  ...  The present review also presents advantage, challenge and future direction of ML techniques in the analysis of EEG signals in epilepsy.  ...  Hassan and Subasi decomposed single-channel EEG signal by using complete ensemble empirical mode decomposition with adaptive noise, and then implemented an ensemble learning (linear programming boosting  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s42494-020-00014-0">doi:10.1186/s42494-020-00014-0</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xoqhcoppjbfepho7q6ltekbljm">fatcat:xoqhcoppjbfepho7q6ltekbljm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709234521/https://aepi.biomedcentral.com/track/pdf/10.1186/s42494-020-00014-0" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/23/0e/230e7237d7d3ddb28e8286acef8e7b949ebc2ac4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s42494-020-00014-0"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

A Proposal to Automate Seizure Detection based on a Comparative Study of EEG Signal Analysis

Hrishikesh Telang, Shreya More, Yatri Modi, Ruhina Karani
<span title="2017-10-18">2017</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
People with epilepsy suffer from multiple types of seizures and Electroencephalography is an important clinical tool for diagnosing, monitoring and managing neurological disorders related to epilepsy.  ...  Epilepsy is a chronic neurological disorder which is characterized by recurrent and sudden seizures.  ...  The paper has been written with the hope that this methodology helps improve seizure detection and improves the quality of life of epilepsy patients.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/ijca2017915637">doi:10.5120/ijca2017915637</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tfu4m5v2qfaytaud7gi2lfsclq">fatcat:tfu4m5v2qfaytaud7gi2lfsclq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180603012322/https://www.ijcaonline.org/archives/volume176/number7/telang-2017-ijca-915637.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4d/1b/4d1b477f0271373a26f5f4bde51d23000aa0de78.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/ijca2017915637"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Epilepsy EEG classification using morphological component analysis

Arindam Gajendra Mahapatra, Balbir Singh, Hiroaki Wagatsuma, Keiichi Horio
<span title="2018-08-08">2018</span> <i title="Springer Nature America, Inc"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hqblpsydr5emviirtqkkmctpha" style="color: black;">EURASIP Journal on Advances in Signal Processing</a> </i> &nbsp;
forming the over-complete dictionary.  ...  In this paper, we have proposed an application of sparse-based morphological component analysis (MCA) to address the problem of classification of the epileptic seizure using time series electroencephalogram  ...  works on Bonn datasetRDSTFT rational discrete STFT, CEEMDAN complete ensemble empirical mode decomposition with adaptive noise, PSR phase space representation, L.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13634-018-0568-2">doi:10.1186/s13634-018-0568-2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fnbg43jbifc2hlpyfkbvp76cvi">fatcat:fnbg43jbifc2hlpyfkbvp76cvi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428035738/https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-018-0568-2" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a3/c6/a3c6aa24948883033349bbd5359a88daedacd4e6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13634-018-0568-2"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

A Revised Hilbert-Huang Transformation to Track Non-stationary Association of Electroencephalography Signals

Xiaocai Shan, Shoudong Huo, Lichao Yang, Jun Cao, Jiaru Zou, Liangyu Chen, Ptolemaios Georgios Sarrigiannis, Yifan Zhao
<span title="2021-04-28">2021</span> <i title="Institute of Electrical and Electronics Engineers"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kujklva47vealdwew7xiv34ble" style="color: black;">IEEE transactions on neural systems and rehabilitation engineering</a> </i> &nbsp;
A case study on classifying epileptic patients and healthy controls using interictal seizure-free EEG data is also presented.  ...  The time-varying cross-spectrum method has been used to effectively study transient and dynamic brain functional connectivity between non-stationary electroencephalography (EEG) signals.  ...  Recent studies have used WT in signal decomposition and adaptive filtering [3] , EEG source localization [4] , computeraided seizure detection and epilepsy diagnosis [5] , and classification of EEG  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2021.3076311">doi:10.1109/tnsre.2021.3076311</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33909567">pmid:33909567</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qhgkewobrbcadlrxkvqdbfk62q">fatcat:qhgkewobrbcadlrxkvqdbfk62q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210503212541/https://ieeexplore.ieee.org/ielx7/7333/4359219/09417109.pdf?tp=&amp;arnumber=9417109&amp;isnumber=4359219&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e7/2d/e72da8f2cbce54d785b160270fb95eac3bc0bc91.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2021.3076311"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Localization of Active Brain Sources From EEG Signals Using Empirical Mode Decomposition: A Comparative Study

Pablo Andrés Muñoz-Gutiérrez, Eduardo Giraldo, Maximiliano Bueno-López, Marta Molinas
<span title="2018-11-02">2018</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ocihcbhrsvefji6tmqvzm24pfm" style="color: black;">Frontiers in Integrative Neuroscience</a> </i> &nbsp;
mode decomposition (EMD) and wavelet transform (WT).  ...  The spatial resolution obtained using all three EMD variants was substantially better than the use of EMD alone, as the mode-mixing problem was mitigated, particularly with masking EMD and EEMD.  ...  Torres et al. (2011) , proposed a variation of EEMD, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and an improved version of CEEMDAN can be found in Colominas et al. (2014  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnint.2018.00055">doi:10.3389/fnint.2018.00055</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30450041">pmid:30450041</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6224487/">pmcid:PMC6224487</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sjaw3p2wprgfnpialfrdjez6du">fatcat:sjaw3p2wprgfnpialfrdjez6du</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190220155126/http://pdfs.semanticscholar.org/24c1/509a03dbba4d038fa61707a1af6befe18fbb.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/24/c1/24c1509a03dbba4d038fa61707a1af6befe18fbb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnint.2018.00055"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6224487" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Comparison of Empirical Mode Decomposition, Wavelets, and Different Machine Learning Approaches for Patient-Specific Seizure Detection Using Signal-Derived Empirical Dictionary Approach

Muhammad Kaleem, Aziz Guergachi, Sridhar Krishnan
<span title="2021-12-13">2021</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/oahna4ohmbebln5zyufhojnnsy" style="color: black;">Frontiers in Digital Health</a> </i> &nbsp;
The approach presented in this paper falls in the latter category, and is based on a signal-derived empirical dictionary approach, which utilizes empirical mode decomposition (EMD) and discrete wavelet  ...  This is the first time these features have been applied for automatic seizure detection using an empirical dictionary approach.  ...  Epilepsy seizure detection using complete ensemble empirical mode decomposition with adaptive noise. Knowledge-Based Systems. (2020) 191:105333. doi: 10.1016/j.knosys.2019. 105333 11.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fdgth.2021.738996">doi:10.3389/fdgth.2021.738996</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34966902">pmid:34966902</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8710482/">pmcid:PMC8710482</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oz7d5547tveqrad53kk2kd5pey">fatcat:oz7d5547tveqrad53kk2kd5pey</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220201045719/https://fjfsdata01prod.blob.core.windows.net/articles/files/738996/pubmed-zip/.versions/1/.package-entries/fdgth-03-738996/fdgth-03-738996.pdf?sv=2018-03-28&amp;sr=b&amp;sig=Wc%2FqbRL29N8DfHWQPuohs6LSRLMQN3iwIKLdmFJkn1g%3D&amp;se=2022-02-01T04%3A57%3A47Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fdgth-03-738996.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1b/92/1b9278ee979babc6c76ab979d40ecde95dbe27fc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fdgth.2021.738996"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8710482" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A Revised Hilbert-Huang Transformation to Track Non-stationary Association of Electroencephalography Signals

Xiaocai Shan, Shoudong Huo, Lichao Yang, Jun Cao, Jiaru Zou, Liangyu Chen, Ptolemaios Georgios Sarrigiannis, Yifan Zhao
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kujklva47vealdwew7xiv34ble" style="color: black;">IEEE transactions on neural systems and rehabilitation engineering</a> </i> &nbsp;
A case study on classifying epileptic patients and healthy controls using interictal seizure-free EEG data is also presented.  ...  The time-varying cross-spectrum method has been used to effectively study transient and dynamic brain functional connectivity between non-stationary electroencephalography (EEG) signals.  ...  Recent studies have used WT in signal decomposition and adaptive filtering [3] , EEG source localization [4] , computer-aided seizure detection and epilepsy diagnosis [5] , and classification of EEG  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2021.3076311">doi:10.1109/tnsre.2021.3076311</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tpz6o24rune3nmnonnl3q2otc4">fatcat:tpz6o24rune3nmnonnl3q2otc4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717010826/https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/16665/Revised_Hilbert-Huang_transformation_to_track_non-stationary_association-2021.pdf;jsessionid=AE856B5C897AD2799D984FC42D89097D?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9c/21/9c21f8c173459957d59c6f6f3f23039ca9debaf2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2021.3076311"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Epilepsy Detection by Using Scalogram Based Convolutional Neural Network from EEG Signals

Ömer Türk, Mehmet Siraç Özerdem
<span title="2019-05-17">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5hwrtdnkjvclroyxzt4ty5ijb4" style="color: black;">Brain Sciences</a> </i> &nbsp;
The effective use of these signals, especially in disease detection, is very important in terms of both time and cost.  ...  Convolutional Neural Network structure was used to learn the properties of these scalogram images and the classification performance of the structure was compared with the studies in the literature.  ...  Jia et al. (2017) used the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique in their studies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/brainsci9050115">doi:10.3390/brainsci9050115</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31109020">pmid:31109020</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6562774/">pmcid:PMC6562774</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bng3qznz55ab3ijttbsvbptsia">fatcat:bng3qznz55ab3ijttbsvbptsia</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209174746/https://res.mdpi.com/d_attachment/brainsci/brainsci-09-00115/article_deploy/brainsci-09-00115-v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ed/a7/eda768b0b2546e4123a19582113b38cdd7c84f08.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/brainsci9050115"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6562774" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>
&laquo; Previous Showing results 1 &mdash; 15 out of 145 results