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Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

R. Yuvaraj, M. Murugappan, Norlinah Mohamed Ibrahim, Kenneth Sundaraj, Mohd Iqbal Omar, Khairiyah Mohamad, R. Palaniappan
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/efcewkjpgrbuvptv4j3naansru" style="color: black;">International Journal of Psychophysiology</a> </i> &nbsp;
From the experimental results using our EEG data set, we found that (a) bispectrum feature is superior to other three kinds of features, namely power spectrum, wavelet packet and nonlinear dynamical analysis  ...  This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated  ...  Emotional state classification in PD  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ijpsycho.2014.07.014">doi:10.1016/j.ijpsycho.2014.07.014</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/25109433">pmid:25109433</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ofzmzx5cdfbuxgbh5oconsrj2e">fatcat:ofzmzx5cdfbuxgbh5oconsrj2e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722104609/https://kar.kent.ac.uk/48277/1/Optimal%20set%20of%20EEG%20features%20for%20emotional%20state%20classification%20and%20trajectory%20visualization%20in%20Parkinson%20disease.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/48/ee/48eec94e282e94eecac17cf54de449da0be73723.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ijpsycho.2014.07.014"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

A Survey on Brain-Computer Interface and Related Applications [article]

Krishna Pai, Rakhee Kallimani, Sridhar Iyer, B.Uma Maheswari, Rajashri Khanai, Dattaprasad Torse
<span title="2022-03-17">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
For BCI systems to be widely used by people with severe disabilities, long-term studies of their real-world use are needed, along with effective and feasible dissemination models.  ...  BCI systems are able to communicate directly between the brain and computer using neural activity measurements without the involvement of muscle movements.  ...  Specifically, • The Non-Linearity characteristics of the brain signal, with the non-stationarity behaviour of the signal, presents a key challenge.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2203.09164v1">arXiv:2203.09164v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/evyespeyujadnayn7c62ba5eoa">fatcat:evyespeyujadnayn7c62ba5eoa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220326173552/https://arxiv.org/ftp/arxiv/papers/2203/2203.09164.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/76/75/76753c02805bc484b9567b1a33e658066f5962a1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2203.09164v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

An Emotion Assessment of Stroke Patients by Using Bispectrum Features of EEG Signals

Choong Wen Yean, Wan Khairunizam Wan Wan Ahmad, Wan Azani Mustafa, Murugappan Murugappan, Yuvaraj Rajamanickam, Abdul Hamid Adom, Mohammad Iqbal Omar, Bong Siao Zheng, Ahmad Kadri Junoh, Zuradzman Mohamad Razlan, Shahriman Abu Bakar
<span title="2020-09-25">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5hwrtdnkjvclroyxzt4ty5ijb4" style="color: black;">Brain Sciences</a> </i> &nbsp;
EEG signals from three groups of subjects, namely stroke patients with left brain damage (LBD), right brain damage (RBD), and normal control (NC), were analyzed for six different emotional states.  ...  This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals.  ...  In addition, the authors' dominant frequency band was the beta band by using wavelet packet transform (WPT) with Hurst exponent feature.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/brainsci10100672">doi:10.3390/brainsci10100672</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32992930">pmid:32992930</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7601112/">pmcid:PMC7601112</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qegnstjksbb6bp2zimu5rfogmm">fatcat:qegnstjksbb6bp2zimu5rfogmm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200926094322/https://res.mdpi.com/d_attachment/brainsci/brainsci-10-00672/article_deploy/brainsci-10-00672.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/c8/36/c836c44f09ea69547cc5ebc347a25825daa342c1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/brainsci10100672"> <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/PMC7601112" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges

Natasha Padfield, Jaime Zabalza, Huimin Zhao, Valentin Masero, Jinchang Ren
<span title="2019-03-22">2019</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 reviews state-of-the-art signal processing techniques for MI EEG-based BCIs, with a particular focus on the feature extraction, feature selection and classification techniques used.  ...  Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and entertainment  ...  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/s19061423">doi:10.3390/s19061423</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/msk42smb7bd6ljqk4pxv6jy3ce">fatcat:msk42smb7bd6ljqk4pxv6jy3ce</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190506000924/https://res.mdpi.com/sensors/sensors-19-01423/article_deploy/sensors-19-01423.pdf?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/1f/3d/1f3d0722f9b4011a0022bc6de06fb3f7de89f890.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19061423"> <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>

EEG Classification by factoring in Sensor Configuration [article]

Lubna Shibly Mokatren, Rashid Ansari, Ahmet Enis Cetin, Alex D Leow, Heide Klumpp, Olusola Ajilore, Fatos Yarman Vural
<span title="2020-02-08">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Performance of these models is examined on two tasks, social anxiety disorder (SAD) detection, and emotion recognition using a dataset for emotion analysis using physiological signals (DEAP).  ...  Enhanced analysis and classification of EEG signals can help improve detection performance.  ...  However, wavelet transforms can capture the local behavior of the signal, and can obtain both frequency and time information of transient non-stationary signals.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.09472v2">arXiv:1905.09472v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4tya2ttmrjdq3oxq72ryosmyae">fatcat:4tya2ttmrjdq3oxq72ryosmyae</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321065049/https://arxiv.org/pdf/1905.09472v2.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.09472v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders

U. Raghavendra, U. Rajendra Acharya, Hojjat Adeli
<span title="2019-11-19">2019</span> <i title="S. Karger AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/waqch6lx5raqbkrcmbicg62sdi" style="color: black;">European Neurology</a> </i> &nbsp;
, multiple sclerosis, and ischemic brain stroke using physiological signals and images.  ...  Authors have been advocating the research ideology that a computer-aided diagnosis (CAD) system trained using lots of patient data and physiological signals and images based on adroit integration of advanced  ...  Analysis of EEG records in an epileptic patient using wavelet transform. J Neurosci Methods. 2003 Feb; 123(1): 69-87. 36 Yuan Q, Zhou W, Xu F, Leng Y, Wei D.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1159/000504292">doi:10.1159/000504292</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31743905">pmid:31743905</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/frg5lwwt7vauxm6rjgc7sepy6y">fatcat:frg5lwwt7vauxm6rjgc7sepy6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200305143845/https://www.karger.com/Article/Pdf/504292" 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/ef/d3/efd3ccf5c4ab7cda6915045bc70f618ee26cb6dc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1159/000504292"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

EEG Classification by factoring in Sensor Spatial Configuration

Lubna Shibly Mokatren, Rashid Ansari, Ahmet Enis Cetin, Alex D. Leow, Olusola Ajilore, Heide Klumpp, Fatos T. Yarman Vural
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Performance of these models is examined on two tasks: social anxiety disorder classification, and emotion recognition using a dataset, DEAP, for emotion analysis using physiological signals.  ...  Enhanced analysis and classification of EEG signals can help improve performance in classifying the disorders and abnormalities.  ...  However, wavelet transforms can capture the local behavior of the signal and can adequately capture both frequency and time information of transient non-stationary signals.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3054670">doi:10.1109/access.2021.3054670</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vgfesjrw7va5pktaiiy5qn3i6a">fatcat:vgfesjrw7va5pktaiiy5qn3i6a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717112743/https://ieeexplore.ieee.org/ielx7/6287639/9312710/09336002.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/10/48/1048b35471cd41b27e93f536b203d4069f210145.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3054670"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

Mamunur Rashid, Norizam Sulaiman, Anwar P. P. Abdul Majeed, Rabiu Muazu Musa, Ahmad Fakhri Ab. Nasir, Bifta Sama Bari, Sabira Khatun
<span title="2020-06-03">2020</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/el4ui6zhlfcjjbeubbsd7m4x6i" style="color: black;">Frontiers in Neurorobotics</a> </i> &nbsp;
Secondly, a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics  ...  Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves.  ...  ACKNOWLEDGMENTS The authors would like to acknowledge support from the Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang, Malaysia.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnbot.2020.00025">doi:10.3389/fnbot.2020.00025</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32581758">pmid:32581758</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7283463/">pmcid:PMC7283463</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jhpwp2b3hffz5mazb7y6oj3saq">fatcat:jhpwp2b3hffz5mazb7y6oj3saq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200604194734/https://fjfsdata01prod.blob.core.windows.net/articles/files/515104/pubmed-zip/.versions/1/.package-entries/fnbot-14-00025/fnbot-14-00025.pdf?sv=2015-12-11&amp;sr=b&amp;sig=%2FUnO2mMUyLG7hGkTMZ94mnH0fyraHXusV6om2vwmLKc%3D&amp;se=2020-06-04T19%3A48%3A03Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fnbot-14-00025.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/57/ed57cb2e56c4aef06279f2edf2525ab05ccb10d7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnbot.2020.00025"> <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/PMC7283463" 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 of Brain Lesion Detection and Classification using Neuroimaging Analysis Techniques

Norhashimah Mohd Saad, Syed Abdul Rahman Syed Abu Bakar, Ahmad Sobri Muda, Musa Mohd Mokji
<span title="2015-05-28">2015</span> <i title="Penerbit UTM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xgym76lve5dw7bbeqkndyfil2u" style="color: black;">Jurnal Teknologi</a> </i> &nbsp;
The review covers neuroimaging modalities, magnetic resonance imaging, DWI and analysis techniques for CAD in detecting and classifying of brain lesion.  ...  Neuroimaging plays an important role in the diagnosis brain lesions such as tumors, strokes and infections.  ...  Acknowledgement The author would like to thank Malaysia Ministry of Higher Education (MOHE) for financial assistance while conducting this research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11113/jt.v74.4670">doi:10.11113/jt.v74.4670</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fd4lbfofbbcxdahweew5aj6txe">fatcat:fd4lbfofbbcxdahweew5aj6txe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720070636/https://jurnalteknologi.utm.my/index.php/jurnalteknologi/article/download/4670/3255" 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/f8/a3/f8a342932ade5cc76d2992b69dbfdfc538a8a3dc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11113/jt.v74.4670"> <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>

Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part II: Brain Signals

Radek Martinek, Martina Ladrova, Michaela Sidikova, Rene Jaros, Khosrow Behbehani, Radana Kahankova, Aleksandra Kawala-Sterniuk
<span title="2021-09-23">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
In this paper, which is a Part II work—various innovative methods for the analysis of brain bioelectrical signals were presented and compared.  ...  source separation, and wavelet transform.  ...  On the other hand, in [164] , various mathematical methods for functional and effective connectivity calculation in both EEG and MEG signals were presented, in particular endeavor, linear, and non-linear  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21196343">doi:10.3390/s21196343</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34640663">pmid:34640663</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mfe4taom5rhfpcp7m744msmgry">fatcat:mfe4taom5rhfpcp7m744msmgry</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210929130816/https://mdpi-res.com/d_attachment/sensors/sensors-21-06343/article_deploy/sensors-21-06343.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/0c/7a/0c7a13cf1eaa7bac480ea157fa65c03fdd478a0b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21196343"> <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>

Past, Present, and Future of EEG-Based BCI Applications

Kaido Värbu, Naveed Muhammad, Yar Muhammad
<span title="2022-04-26">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
In this review, the equipment used for gathering EEG data and signal processing methods have also been reviewed.  ...  EEG-based BCI applications have initially been developed for medical purposes, with the aim of facilitating the return of patients to normal life.  ...  mother wavelet selection for eeg signal application to motor imagery-based brain-computer interface Combination of discrete wavelet packet transform with detrended fluctuation Hekmatmanesh et al. 2019  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s22093331">doi:10.3390/s22093331</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35591021">pmid:35591021</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC9101004/">pmcid:PMC9101004</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gn6bt4uqavenzbu3nkt32de42m">fatcat:gn6bt4uqavenzbu3nkt32de42m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220428223234/https://mdpi-res.com/d_attachment/sensors/sensors-22-03331/article_deploy/sensors-22-03331-v3.pdf?version=1651135666" 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/8a/5d/8a5d443da6e12385611628772e6f92058f5704ef.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s22093331"> <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/PMC9101004" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Bio-Signals in Medical Applications and Challenges Using Artificial Intelligence

Mudrakola Swapna, Uma Maheswari Viswanadhula, Rajanikanth Aluvalu, Vijayakumar Vardharajan, Ketan Kotecha
<span title="2022-02-25">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bajb2sq2z5a3beaybwby4ac4w4" style="color: black;">Journal of Sensor and Actuator Networks</a> </i> &nbsp;
Different types of bio-signal can be used to monitor a patient's condition and in decision making. Medical equipment uses signals to communicate information to care staff.  ...  The early prediction and detection of health conditions will guide people to stay healthy. This paper represents the scope of bio-signals using AI in the medical area.  ...  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/jsan11010017">doi:10.3390/jsan11010017</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/67eo5uer3rgxrk3cpmggmxxfpu">fatcat:67eo5uer3rgxrk3cpmggmxxfpu</a> </span>
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A Review On Automatic Detection of Brain Tumor Using Computer Aided Diagnosis System Through MRI

Meera R, Dr. Anandhan, P
<span title="2018-09-12">2018</span> <i title="European Alliance for Innovation n.o."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gdjl73a6dbeozbpeysr4hhjjk4" style="color: black;">EAI Endorsed Transactions on Energy Web</a> </i> &nbsp;
The various Preprocessing Techniques are classified as: (i) Content Based Model, (ii) Fiber Tracking Method, (iii) Wavelets and Wavelet Packets and Fourier Transform Technique.  ...  Wavelets and Wavelet Packets, Stein's Unbiased Risk Estimate(SURE) By using thresholding the noise coefficients are vanished with detailed components.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4108/eai.12-9-2018.155747">doi:10.4108/eai.12-9-2018.155747</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4xnmrtl4mjdljo67v3arbdnfrm">fatcat:4xnmrtl4mjdljo67v3arbdnfrm</a> </span>
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Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review

L R Quitadamo, F Cavrini, L Sbernini, F Riillo, L Bianchi, S Seri, G Saggio
<span title="2017-01-09">2017</span> <i title="IOP Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tpqlgxji7rezlnmgkbv4hfla3a" style="color: black;">Journal of Neural Engineering</a> </i> &nbsp;
The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques  ...  Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results.  ...  Features based on dual-tree complex wavelet transform and a linear SVM were used for classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1741-2552/14/1/011001">doi:10.1088/1741-2552/14/1/011001</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28068295">pmid:28068295</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eew3npim2vanldy5vpjcsvw4da">fatcat:eew3npim2vanldy5vpjcsvw4da</a> </span>
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The Effectiveness Assessment of Massage Therapy Using Entropy-based EEG Features among Lumbar Disc Herniation Patients Comparing with Healthy Controls

Huihui Li, Wenjing Du, Kai Fan, Junsong Ma, Kamen Ivanov, Lei Wang
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
It indicated that the entropy-based features and permutation disalignment index (PDI) of EEG rhythms could be promising indices of the massage effectiveness for LDH patients and control group.  ...  However, few studies revealed the quantitative entropy-based features of electroencephalography (EEG) for the MT effectiveness for the LDH patients.  ...  They also thanked Fang Zhou, Xiangjun Sun, Cuifeng Zheng, and Wenmin Chen for data collection.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.2964050">doi:10.1109/access.2020.2964050</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/isriwegbqff55lkgkhbp363oem">fatcat:isriwegbqff55lkgkhbp363oem</a> </span>
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