Filters








1,124 Hits in 3.4 sec

An Integrated Index for the Identification of Focal Electroencephalogram Signals Using Discrete Wavelet Transform and Entropy Measures

Rajeev Sharma, Ram Pachori, U. Acharya
<span title="2015-07-27">2015</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
classification of focal and non-focal EEG signals using the minimum number of features.  ...  The dynamics of brain area influenced by focal epilepsy can be studied using focal and non-focal electroencephalogram (EEG) signals.  ...  classification of focal and non-focal EEG signals.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e17085218">doi:10.3390/e17085218</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/i7scaoexjvbm7fj7bncywxpoki">fatcat:i7scaoexjvbm7fj7bncywxpoki</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150912023657/http://www.mdpi.com/1099-4300/17/8/5218/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/ac/e9/ace9353b818e116380aa888c4a5c3902823f148c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e17085218"> <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>

Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals

Rajeev Sharma, Ram Pachori, U. Acharya
<span title="2015-02-03">2015</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
In this work, a method for the classification of focal and non-focal EEG signals is presented using entropy measures.  ...  These entropy measures can be useful in assessing the nonlinear interrelation and complexity of focal and non-focal EEG signals.  ...  Andrzejak of Universitat Pompeu Fabra, Barcelona, Spain, for providing permission to use Bern-Barcelona EEG dataset. Author Contributions Ram Bilas Pachori and U.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e17020669">doi:10.3390/e17020669</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/66bgxxsblza7ldckxpptf5cjlu">fatcat:66bgxxsblza7ldckxpptf5cjlu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150927233213/http://www.mdpi.com/1099-4300/17/2/669/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/84/01/8401b8001489514741809c2d9a17b21a57944103.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e17020669"> <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>

Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures [chapter]

Fasil OK, Reghunadhan Rajesh
<span title="2020-09-09">2020</span> <i title="IntechOpen"> Advances in Neural Signal Processing </i> &nbsp;
In this work, the competence of EMD with traditional features to classify the seizure and non-seizure EEG signals is studied.  ...  Empirical mode decomposition (EMD) is a remarkable method for the analysis of nonlinear and non-stationary data.  ...  .89017 Figure 3 . 3 Non-focal EEG signals and six IMFs obtained from non-focal EEG signal.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.89017">doi:10.5772/intechopen.89017</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3tcycjpk3ja23byqn5mbxuogwy">fatcat:3tcycjpk3ja23byqn5mbxuogwy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201106135730/https://api.intechopen.com/chapter/pdf-download/68909.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/83/59/83591950eb66d1bc107e81d68ff734d482a532d0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.89017"> <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>

Feature Extraction and Selection of a Combination of Entropy Features for Real-time Epilepsy Detection

B. Abhinaya, D. Charanya
<span title="2016-04-01">2016</span> <i title="Valley International"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7itxqhdltnewtn4ueymnlhnkea" style="color: black;">International Journal Of Engineering And Computer Science</a> </i> &nbsp;
These two features are given as input to the Least Square Support Vector Machine (LS-SVM) classifier to differentiate normal and focal signal. The classification accuracy of our method is 82%.  ...  This signal is non-linear and chaotic and hence, it is very time-consuming and tedious to analyse them visually.  ...  Acknowledgements None Conflict of Interest None  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18535/ijecs/v5i4.03">doi:10.18535/ijecs/v5i4.03</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rtk5lrhknbhgnl7ek3cqy3ukvu">fatcat:rtk5lrhknbhgnl7ek3cqy3ukvu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602062721/http://ijecs.in/issue/v5-i4/3%20ijecs.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/b5/b1/b5b188552d90152133d2477a7cebfa6aedc2bcd3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18535/ijecs/v5i4.03"> <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>

A Classification Approach for Focal/Non-focal EEG Detection Using Cepstral Analysis

Delal ŞEKER, Mehmet Siraç ÖZERDEM
<span title="2021-09-29">2021</span> <i title="Dicle Universitesi Muhendislik Fakultesi Muhendislik Dergisi"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rxfsrf4lyncqzhmbmegtg727rq" style="color: black;">DÜMF Mühendislik Dergisi</a> </i> &nbsp;
A value of k=10 is used for cross validation. All focal and non-focal EEG pairs are perfectly classified with acc., sen., spe., and F1-score of 100% and AUC with 1 via.  ...  The goal of this paper is to classify the focal (epileptogenic area) and non-focal (non-epileptogenic area) EEG records with cepstral coefficients and machine learning algorithms.  ...  Acknowledgement We special thank to Andrjezak RG, Schindler K, and Rummel C for providing Bern-Barcelona EEG Dataset publicly.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24012/dumf.1002081">doi:10.24012/dumf.1002081</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/btl4lmswljeavge2igxepc57gi">fatcat:btl4lmswljeavge2igxepc57gi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220303111010/https://dergipark.org.tr/en/download/article-file/1999734" 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/8b/63/8b6304817408226b34255033a0716c447401ee0e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24012/dumf.1002081"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Application of Deep Learning and WT-SST in Localization of Epileptogenic Zone Using Epileptic EEG Signals

Sani Saminu, Guizhi Xu, Zhang Shuai, Isselmou Abd El Kader, Adamu Halilu Jabire, Yusuf Kola Ahmed, Ibrahim Abdullahi Karaye, Isah Salim Ahmad
<span title="2022-05-11">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
The detection of the location of focal EEG signals and the time of seizure occurrence are vital information that help doctors treat focal epileptic seizures using a surgical method.  ...  Four detection and classification techniques for focal and non-focal EEG signals were proposed. (1). Combined hybrid features with Support Vector Machine (Hybrid-SVM) (2).  ...  Architecture of 2D-DCNN for classification of focal and non-focal EEG using time-frequency WT-SST features.3.1.5.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app12104879">doi:10.3390/app12104879</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d752224fcbde3l3d3lr6qrhuby">fatcat:d752224fcbde3l3d3lr6qrhuby</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220512230116/https://mdpi-res.com/d_attachment/applsci/applsci-12-04879/article_deploy/applsci-12-04879.pdf?version=1652274688" 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/42/7c/427c1e6ed25139e7561c523de3033e122a371834.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app12104879"> <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>

Classification of Focal and Non-Focal EEG Signal using an Area of Octagon Method

<span title="2019-10-30">2019</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h673cvfolnhl3mnbjxkhtxdtg4" style="color: black;">International Journal of Engineering and Advanced Technology</a> </i> &nbsp;
This article introduces a fresh method known as the Area of Octagon (AOO), used for Focal (F) and Non-Focal (NF) EEG Signal classification.  ...  The proposed method attained an average classification accuracy of 97.9% with Linear, polynomial and an RBF kernel.  ...  Computation of Area of Octagon The Area of octagon of the intrinsic mode functions of EEG signals can give useful diagnostic features for Focal and Non-focal EEG signal classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.a1450.109119">doi:10.35940/ijeat.a1450.109119</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/laeklddolzht7abgrynifnh6zu">fatcat:laeklddolzht7abgrynifnh6zu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209050754/https://www.ijeat.org/wp-content/uploads/papers/v9i1/A1450109119.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/8b/3a/8b3af92ea8f0aca0356e463934c22fa686cdacb5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.a1450.109119"> <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>

Multiscale Permutation Lempel–Ziv Complexity Measure for Biomedical Signal Analysis: Interpretation and Application to Focal EEG Signals

Marta Borowska
<span title="2021-06-29">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
Our experimental results confirmed the usefulness of the MPLZC method for distinguishing focal and non-focal EEG signals with a classification accuracy of 86%.  ...  This paper analyses the complexity of electroencephalogram (EEG) signals in different temporal scales for the analysis and classification of focal and non-focal EEG signals.  ...  We used only one measure, so it can be useful in building a real system supporting identification of a epileptogenic activity in an area of the brain.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e23070832">doi:10.3390/e23070832</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gzlg3zakqzdkphwj7lgowpo7g4">fatcat:gzlg3zakqzdkphwj7lgowpo7g4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717193158/https://res.mdpi.com/d_attachment/entropy/entropy-23-00832/article_deploy/entropy-23-00832-v2.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/3d/a9/3da918baa7f1a06250d4b3163b179063f7b6f1f6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e23070832"> <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>

Interpretation of Entropy Algorithms in the Context of Biomedical Signal Analysis and Their Application to EEG Analysis in Epilepsy

Lampros Chrysovalantis Amarantidis, Daniel Abásolo
<span title="2019-08-27">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
In addition, using results from one entropy algorithm as features and the k-nearest neighbours algorithm, maximum classification accuracies in the first EEG database ranged from 63% to 73.5%, while these  ...  For the second database, maximum classification accuracy reached 62.5% using one entropy algorithm, while using two algorithms as features further increased that by 10%.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e21090840">doi:10.3390/e21090840</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pc3rw6mvc5ei5daaoinhyvaaxq">fatcat:pc3rw6mvc5ei5daaoinhyvaaxq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200306042228/http://epubs.surrey.ac.uk/852524/1/Interpretation%20of%20Entropy%20Algorithms.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/1f/3f/1f3f1d2b126dbd227cd45107377b42fa76fbe986.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e21090840"> <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>

Focal and Non-Focal EEG SignalClassification by Computing Areaof 2D-PSR Obtained for IMF

R. Krishnaprasanna, V. Vijaya Baskar, Research scholar, Department of ECE, Sathyabama University, Chennai, Tamil Nadu-600119, India, Professor, Department of ETCE, Sathyabama University, Chennai, Tamil Nadu-600119, India
<span title="">2018</span> <i title="River Publishers"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ygvakwwlpvfrpb4j6w2wmjbwtm" style="color: black;">Journal of ICT Standardization</a> </i> &nbsp;
The proposed technique namely area of 2D-PSR method has provided promising class accuracy for classification of focal and non-focal EEG signals which gives 98.95% accuracy with polynomial and RBF kernal  ...  The main objective of this work is to classify the focal and non-focal EEG signal for the medical purpose.  ...  The average sample entropy (ASE) of IMFs and average variance of instantaneous frequencies (AVIF) of IMFs for separate EEG signal have been used as functions for classifying type of Focal and non-Focal  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.13052/jicts2245-800x.523">doi:10.13052/jicts2245-800x.523</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/royvvtva2vbgthdyhjhnivfrwy">fatcat:royvvtva2vbgthdyhjhnivfrwy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190429110608/https://www.riverpublishers.com/journal/journal_articles/RP_Journal_2245-800X_523.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/66/08/66084d53844d9267ec40c1d0c9510fa19747a9af.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.13052/jicts2245-800x.523"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Real-Time Localization of Epileptogenic Foci EEG Signals: An FPGA-Based Implementation

Jose V. Frances-Villora, Manuel Bataller-Mompean, Azeddine Mjahad, Alfredo Rosado-Muñoz, Antonio Gutierrez Gutierrez Martin, Vicente Teruel-Marti, Vicente Villanueva, Kevin G. Hampel, Juan F. Guerrero-Martinez
<span title="2020-01-23">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
of focal and non-focal electroencephalographic (EEG) signals.  ...  These works use automatic classification as an analysis tool for helping neurosurgeons to identify focal areas off-line, out of surgery, during the processing of the huge amount of information collected  ...  focal and non-focal EEG signals.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10030827">doi:10.3390/app10030827</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7f67wwi5rvbuxe4dz4coasgfzu">fatcat:7f67wwi5rvbuxe4dz4coasgfzu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200211232313/https://res.mdpi.com/d_attachment/applsci/applsci-10-00827/article_deploy/applsci-10-00827-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/c5/40/c54078dc21ea492b383b06af5b075fb22acda542.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10030827"> <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>

Exploiting Feature Selection and Neural Network Techniques for Identification of Focal and Nonfocal EEG Signals in TQWT Domain

Muhammad Tariq Sadiq, Hesam Akbari, Ateeq Ur Rehman, Zuhaib Nishtar, Bilal Masood, Mahdieh Ghazvini, Jingwei Too, Nastaran Hamedi, Mohammed K. A. Kaabar, Cosimo Ieracitano
<span title="2021-08-27">2021</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cswd2rqrire6lgrsm56kv4adue" style="color: black;">Journal of Healthcare Engineering</a> </i> &nbsp;
of the art used in the public Bern-Barcelona EEG database.  ...  The visual inspection of multiple channels for detecting the focal EEG signal is time-consuming and prone to human error.  ...  Conflicts of Interest e authors declare that they have no conflicts of interest. Authors' Contributions Muhammad Tariq Sadiq and Hesam Akbari contributed equally to this work.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/6283900">doi:10.1155/2021/6283900</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34659691">pmid:34659691</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8418932/">pmcid:PMC8418932</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jehkrqlwoncnro7ub72g624pyq">fatcat:jehkrqlwoncnro7ub72g624pyq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210901174146/https://downloads.hindawi.com/journals/jhe/2021/6283900.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/09/8a/098a958b3ae5a92b04143049e84db4e858577e66.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/6283900"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> hindawi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418932" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Epileptic EEG signal classifications based on DT-CWT and SVM classifier

Deivasigamani S, Faculty of Engineering and Computer Technology, AIMST University, Malaysia-08100., Senthilpari C, Wong Hin Yong, Rajesh P.K., Faculty of Engineering, Multimedia University, Malaysia-63100, Faculty of Engineering, Multimedia University, Malaysia-63100, Faculty of Medicine, AIMST University, Malaysia-08100
<span title="2021-10-13">2021</span> <i title="Journal of Engineering Research"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bwux6bft5bg7nczd66yzc57txe" style="color: black;">Maǧallaẗ al-abḥāṯ al-handasiyyaẗ</a> </i> &nbsp;
Henceforth, the discovery of focal signs from the non-focal signs is a significant for epileptic medical procedure in epilepsy patients.  ...  The exhibition of the proposed EEG signals characterization framework is assessed as far as Sensitivity, Specificity, and Accuracy.  ...  In this paper, we have used 50 focal signals and 50 non-focal signals. The performance of the proposed EEG signal classification system is analyzed in terms of sensitivity, specificity and accuracy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.36909/jer.10523">doi:10.36909/jer.10523</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6hmw25ft6vbatize773fzlc56q">fatcat:6hmw25ft6vbatize773fzlc56q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211016020254/https://kuwaitjournals.org/jer/index.php/JER/article/download/10523/2335" 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/94/b6/94b697cbe3476ba3eb317f78d08fc831355ea9c1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.36909/jer.10523"> <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>

Detection of Focal and Non-Focal Electroencephalogram Signals Using Fast Walsh-Hadamard Transform and Artificial Neural Network

Prasanna J., M. S. P. Subathra, Mazin Abed Mohammed, Mashael S. Maashi, Begonya Garcia-Zapirain, N. J. Sairamya, S. Thomas George
<span title="2020-09-01">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
The discrimination of non-focal class (NFC) and focal class (FC), is vital in localizing the epileptogenic zone (EZ) during neurosurgery.  ...  Hence, in this present work, automated diagnosis of FC EEG signals from NFC EEG signals is developed using the Fast Walsh–Hadamard Transform (FWHT) method, entropies, and artificial neural network (ANN  ...  Acknowledgement: The authors would like to acknowledge the Karunya Institute of Technology and Sciences for providing the facilities.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20174952">doi:10.3390/s20174952</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32883006">pmid:32883006</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l4iszfv3tnhvpkjdg4volvaoim">fatcat:l4iszfv3tnhvpkjdg4volvaoim</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200904002255/https://res.mdpi.com/d_attachment/sensors/sensors-20-04952/article_deploy/sensors-20-04952-v2.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/09/85/09859600bb045ddf82467c156bcf0200387fc3d8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20174952"> <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>

Tunable-Q Wavelet Transform Based Multivariate Sub-Band Fuzzy Entropy with Application to Focal EEG Signal Analysis

Abhijit Bhattacharyya, Ram Pachori, U. Acharya
<span title="2017-03-03">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
This paper analyses the complexity of multivariate electroencephalogram (EEG) signals in different frequency scales for the analysis and classification of focal and non-focal EEG signals.  ...  Our method has achieved the highest classification accuracy of 84.67% in classifying focal and non-focal EEG signals with LS-SVM classifier.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e19030099">doi:10.3390/e19030099</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/grwaczsxkjb5fafk5jj5ie72xi">fatcat:grwaczsxkjb5fafk5jj5ie72xi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180727131130/https://res.mdpi.com/def502001114b91ffbb56ca459001f1dca4662339ce84f1a203ce53551c04320cec4e8180a7d42227a47392b2228aadff3b5b673be53f971bd3c650854b0c226d079fb3fe1945b4cb8e87f4b015b31584eb493133772f8c96f100bcd0ca79890aef1c9b194ef77828c654177ed88a72b021e3432b7a06dedffea5fd570109fc7f795955a2ec62e127cea942905730cf4f2bb6a?filename=&amp;attachment=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/eb/bd/ebbd693706752d4ab431344ad6bfa00d9ae82a60.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e19030099"> <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>
&laquo; Previous Showing results 1 &mdash; 15 out of 1,124 results