Filters








2,327 Hits in 4.7 sec

DALGACIK DÖNÜŞÜMÜ İLE YAPAY SİNİR AĞLARI KULLANILARAK UYKU EVRELERİNİN OTOMATİK SINIFLANDIRILMASI

Ali ÖTER, Osman AYDOĞAN, Deniz TUNCEL
<span title="2019-01-27">2019</span> <i title="Omer Halisdemir Universitesi Muhendislik Bilimleri Dergisi"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/eogd2y4kefav5dde5gcnwspfsm" style="color: black;">Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi</a> </i> &nbsp;
The signals for automatic sleep stages classification were selected in accordance with American Academy of Sleep Medicine criteria.  ...  The findings suggest that training and test success of automatic sleep stage classification are better compared to the other studies in the literature.  ...  . • Unlike other studies, sleep stages were determined by using the sleep stages belonging to subjects with OSA. • EMG, EOG 2 and 3 EEG signals were used in the automatic sleep stage classification. •  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.28948/ngumuh.516809">doi:10.28948/ngumuh.516809</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qflqaz2t3zadfjafxx2mle5gpm">fatcat:qflqaz2t3zadfjafxx2mle5gpm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200214075038/https://dergipark.org.tr/tr/download/article-file/632707" 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/11/bb/11bb1d3166e89a8ddb1a5ae2a8bea6ab5a92075d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.28948/ngumuh.516809"> <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>

Automatic EOG and EMG Artifact Removal Method for Sleep Stage Classification [chapter]

Ali Abdollahi Gharbali, José Manuel Fonseca, Shirin Najdi, Tohid Yousefi Rezaii
<span title="">2016</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kss7mrolvja63k4rmix3iynkzi" style="color: black;">IFIP Advances in Information and Communication Technology</a> </i> &nbsp;
EEG is widely adopted for the automatic detection of sleep stages and neuronal activity evaluation during sleep.  ...  Classification In this study ANN were used for the classification of sleep stages.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-31165-4_15">doi:10.1007/978-3-319-31165-4_15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p35wjn62qzatvoepyqotb3scii">fatcat:p35wjn62qzatvoepyqotb3scii</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190501112155/https://hal.inria.fr/hal-01438238/file/419233_1_En_15_Chapter.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/1c/78/1c7820444c04ea619090ee63db9dfa7ac1b9a073.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-31165-4_15"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Light Sleep Detection based on Surface Electromyography Signals for Nap Monitoring

Wachiraporn Aiamklin, Yutana Jewajinda, Yunyong Punsawad
<span title="2022-01-10">2022</span> <i title="North Atlantic University Union (NAUN)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/huvvatmx4relzg7dmrwkrnyfsy" style="color: black;">International Journal of Biology and Biomedical Engineering</a> </i> &nbsp;
This paper proposes the development of automatic sleep stage detection by using physiological signals.  ...  A combination of EMG and electroencephalogram (EEG) signals might be yield a high system performance for nap monitoring and alarm system.  ...  This work involved a sleep study device and experimental setting provided by the Brain-Computer Interface Laboratory, Mahidol University, Thailand.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.46300/91011.2022.16.18">doi:10.46300/91011.2022.16.18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fddaepfoqbc47nhmowoaskhrte">fatcat:fddaepfoqbc47nhmowoaskhrte</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220117164101/https://npublications.com/journals/bio/2022/a362010-018(2022).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/c4/a8/c4a88f3934789ec640b8f8eb76d8fd45c2b43803.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.46300/91011.2022.16.18"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Self-evaluated automatic classifier as a decision-support tool for sleep/wake staging

S. Charbonnier, L. Zoubek, S. Lesecq, F. Chapotot
<span title="">2011</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdwg5aetkjbgpga7kn2jevifmi" style="color: black;">Computers in Biology and Medicine</a> </i> &nbsp;
The decision system is composed of two stages: the first stage checks the 20 s epoch of polysomnographic signals (EEG, EOG and EMG) for the presence of artifacts and selects the artifact-free signals.  ...  An automatic sleep/wake stages classifier that deals with the presence of artifacts and that provides a confidence index with each decision is proposed.  ...  Acknowledgement The authors are grateful to Alain Buguet and Emilia Sforza for providing and scoring the data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2011.04.001">doi:10.1016/j.compbiomed.2011.04.001</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/21497802">pmid:21497802</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fls2hxihh5fzlkwjkcifwkxvi4">fatcat:fls2hxihh5fzlkwjkcifwkxvi4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321143427/http://www.phitools.com/pdf/charbonnier_cbm_2011.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/26/95/26957a05301f4392a5cc124ecf8ceebc85da5c01.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2011.04.001"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Effect of EEG Time Domain Features on the Classification of Sleep Stages

Sule Yucelbas, Seral Ozsen, Cuneyt Yucelbas, Gulay Tezel, Serkan Kuccukturk, Sebnem Yosunkaya
<span title="2016-07-15">2016</span> <i title="Indian Society for Education and Environment"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wffwpj3q45g5zfjzfeyagk5uea" style="color: black;">Indian Journal of Science and Technology</a> </i> &nbsp;
Five different classifiers were designed especially for transitions between stages using time domain features of EEG, EOG and EMG signals and evaluated these features for each classifier.  ...  Background/Objectives: Studies on the field of automatic sleep stage classification have been taking more attention of researchers day by day.  ...  For example, while Keywords: ANN, Automatic Sleep Stage Classification, EEG, EMG, EOG, Feature Selection one sleep expert can label a signal pattern as sleep spindle in EEG signal, other expert may not  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17485/ijst/2016/v9i25/96630">doi:10.17485/ijst/2016/v9i25/96630</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4tnqzlosojgmdfpj53couimymu">fatcat:4tnqzlosojgmdfpj53couimymu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720040030/http://www.indjst.org/index.php/indjst/article/download/96630/71211" 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 noreferrer" href="https://doi.org/10.17485/ijst/2016/v9i25/96630"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

PSG Kayıt Sinyalleri Kullanılarak Uyku Evrelerinin Sınıflandırılması

Yasin KOCA, Seral ÖZŞEN, Fatma Zehra GÖĞÜŞ, Gülay TEZEL, Serkan KÜÇÜKTÜRK, Hülya VATANSEV
<span title="2020-10-05">2020</span> <i title="European Journal of Science and Technology"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zn2laggqzbe7hekqkjyz4cj2p4" style="color: black;">European Journal of Science and Technology</a> </i> &nbsp;
Automatic sleep staging is aimed within the scope of this paper. Sleep staging is a study by a sleep specialist.  ...  For this, an automatic sleep staging method has been introduced.  ...  In spite of fact that EEG, EOG and EMG tracings are used basically in sleep staging, especially the density of EEG signal in staging process and the power in detecting stages higher than the other signals  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31590/ejosat.804709">doi:10.31590/ejosat.804709</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j7mzg6djbfcw5lizfopsxy6xri">fatcat:j7mzg6djbfcw5lizfopsxy6xri</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201013014146/https://dergipark.org.tr/tr/download/article-file/1325886" 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/7d/1c/7d1c1a4c6d14c6aec01b0139a158b0e069510401.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31590/ejosat.804709"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Multi-modality of polysomnography signals' fusion for automatic sleep scoring

Rui Yan, Chi Zhang, Karen Spruyt, Lai Wei, Zhiqiang Wang, Lili Tian, Xueqiao Li, Tapani Ristaniemi, Jihui Zhang, Fengyu Cong
<span title="">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jk3pblxy6rgufncpryy2osctie" style="color: black;">Biomedical Signal Processing and Control</a> </i> &nbsp;
At the classification stage, five different classifiers were employed to evaluate the validity of the features and to classify sleep stages.  ...  Objective: The study aims to develop an automatic sleep scoring method by fusing different polysomnography (PSG) signals and further to investigate PSG signals' contribution to the scoring result.  ...  To our knowledge, very limited articles explored it together with EEG, EOG and EMG in automatic sleep scoring algorithms.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.bspc.2018.10.001">doi:10.1016/j.bspc.2018.10.001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nnzopkob25ecdbwymbx3e2jcqu">fatcat:nnzopkob25ecdbwymbx3e2jcqu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428162344/https://jyx.jyu.fi/bitstream/handle/123456789/62551/1s2.0s1746809418302647main.pdf;jsessionid=A234D3FD49A04867CDF525FE26CBF5D5?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/28/f7/28f7e220fb95baf5444f263106d22765cdbb876a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.bspc.2018.10.001"> <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>

Automatic Sleep Scoring Stages using Real-Time EMG Signals

Hemu Farooq, Anuj Jain, V. K. Sharma
<span title="2021-01-18">2021</span> <i title="Sroha Publishing Pvt. Ltd"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5ygxxvpqbvgkroshko2uitm5om" style="color: black;">International Journal of Research in Engineering, Science and Management</a> </i> &nbsp;
The proposed work provides an insight to use the automatic scheme which is based on real time EMG signals.  ...  Besides, mistakes and irregularities in between classification of same data can be recurrent. Therefore, there is a great use of automatic scoring system to support reliable classification.  ...  However, in proposed work the motive is to classify the sleep stages using EEG, EMG, EOG simultaneously when recorded.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.47607/ijresm.2021.465">doi:10.47607/ijresm.2021.465</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sgxajx4jwbb5lbxrwnzis6vcta">fatcat:sgxajx4jwbb5lbxrwnzis6vcta</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210127164842/https://www.journals.resaim.com/ijresm/article/download/465/439" 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/a6/97/a697eadad934279c700618ee54a7d12443bb04d5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.47607/ijresm.2021.465"> <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 machine learning approach to classify vigilance states in rats

Zong-En Yu, Chung-Chih Kuo, Chien-Hsing Chou, Chen-Tung Yen, Fu Chang
<span title="">2011</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ekjwtd7zwfeipf5aknu4733lzy" style="color: black;">Expert systems with applications</a> </i> &nbsp;
In this paper, we proposed an automatic sleep stages classification system by analyzing rat's EEG signal. The rat's EEG signal is transferred by FFT and then extracted features.  ...  By experimenting on 810 periods of EEG signal, the proposed classification system achieves satisfactory classification accuracy of sleep stages.  ...  This motivates us to classify sleep stages with EEG signal only.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.eswa.2011.02.076">doi:10.1016/j.eswa.2011.02.076</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7kztuoucuffjtcb4lptnpyxmu4">fatcat:7kztuoucuffjtcb4lptnpyxmu4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170816104558/http://www.wseas.us/e-library/conferences/2009/budapest/MIV-SSIP/MIV-SSIP20.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/92/be/92be93502b485cc26f16f7b96adc5dba0b1e2875.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.eswa.2011.02.076"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Save Muscle Information–Unfiltered EEG Signal Helps Distinguish Sleep Stages

Gi-Ren Liu, Caroline Lustenberger, Yu-Lun Lo, Wen-Te Liu, Yuan-Chung Sheu, Hau-Tieng Wu
<span title="2020-04-03">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
We show that an existing automatic sleep stage annotation algorithm can be improved by taking this information into account.  ...  This result suggests that if possible, we should sample the EEG signal with a high sampling rate, and preserve as much spectral information as possible.  ...  EEG signals are used for classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20072024">doi:10.3390/s20072024</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32260314">pmid:32260314</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7180982/">pmcid:PMC7180982</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zibgyx6fsnep3jllfdo7mxg4ce">fatcat:zibgyx6fsnep3jllfdo7mxg4ce</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200508202702/https://res.mdpi.com/d_attachment/sensors/sensors-20-02024/article_deploy/sensors-20-02024-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/4e/1c/4e1c880a20b5ac6f677fd31dd04c977310bd67dd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20072024"> <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/PMC7180982" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis [article]

Navin Cooray, Mkael Symmonds University of Oxford, Institute of Biomedical Engineering, Dept. Engineering Sciences, Oxford, UK, Nuffield Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre Department of Clinical Neurophysiology, Oxford University Hospitals, John Radcliffe Hospital, University of Oxford, UK)
<span title="2018-11-12">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Sleep stage classification was achieved using a Random Forest (RF) classifier and 156 features extracted from electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) channels.  ...  Accuracy remained high (92%) when using automated sleep staging.  ...  For this study the pre-processed EEG, EOG, and EMG signals were segmented into 10 second mini-epochs in order to calculate features for each 30-second epoch, a technique often used for sleep stage classification  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1811.04662v1">arXiv:1811.04662v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v5zvejgmxfefxep4jtivtiaghy">fatcat:v5zvejgmxfefxep4jtivtiaghy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200824061421/https://arxiv.org/ftp/arxiv/papers/1811/1811.04662.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/73/ff/73ffabf3414ae3a848cd7ae11d881e46c737176b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1811.04662v1" 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>

Feature selection for sleep/wake stages classification using data driven methods

Lukáš Zoubek, Sylvie Charbonnier, Suzanne Lesecq, Alain Buguet, Florian Chapotot
<span title="">2007</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jk3pblxy6rgufncpryy2osctie" style="color: black;">Biomedical Signal Processing and Control</a> </i> &nbsp;
The most significant improvement on classification accuracy is obtained on NREM sleep stage I, a stage of transition between sleep and wakefulness. #  ...  Extraction of various features from the electroencephalogram (EEG), the electro-oculogram (EOG) and the electromyogram (EMG) processed in the frequency and time domains was achieved using a database of  ...  Acknowledgements Special thanks are expressed to PhiTools (Strasbourg, France) for lending the PRANA software and the sleep recording database.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.bspc.2007.05.005">doi:10.1016/j.bspc.2007.05.005</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/or5w6patrnevrliwlrn7xolqha">fatcat:or5w6patrnevrliwlrn7xolqha</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170705124810/http://www.phitools.com/pdf/zoubek_bspc_2007.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/f6/5b/f65bab31d57a17565e52cdca95bbd967e0c0676a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.bspc.2007.05.005"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

A Self-adaptive Threshold Method for Automatic Sleep Stage Classification Using EOG and EMG

Jie Li, Hang Chen, Shuming Ye, J.Y. Li, T.Y. Liu, T. Deng, M. Tian
<span title="">2015</span> <i title="EDP Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4vlgvitw6fcmbay5hkyo2s2ime" style="color: black;">MATEC Web of Conferences</a> </i> &nbsp;
In this study, we developed a new method to classify sleep stage using electrooculogram (EOG) and electromyography (EMG) automatically.  ...  Combination of the time features of EOG and EMG signals, we classified sleep stages into Wake, REM and NREM stages.  ...  using EEG, EOG, and EMG [9] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/matecconf/20152205023">doi:10.1051/matecconf/20152205023</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oq2422pxc5ecdaa6522uvrzphi">fatcat:oq2422pxc5ecdaa6522uvrzphi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808092619/https://www.matec-conferences.org/articles/matecconf/pdf/2015/03/matecconf_iceta2015_05023.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/5e/d0/5ed0be5ea62991694cc7eef658bea4a46635bb4a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/matecconf/20152205023"> <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 Novel Hybrid Machine Learning Classification for the Detection of Bruxism Patients Using Physiological Signals

Md Belal Bin Heyat, Faijan Akhtar, Asif Khan, Alam Noor, Bilel Benjdira, Yumna, Syed Jafar Abbas, Dakun Lai
<span title="2020-10-22">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;
Besides, the classification of the sleep stages such as the wake (w) stage and rapid eye movement (REM) stage from the electrocardiogram channel (ECG1-ECG2) obtained a maximum specificity of 86% and an  ...  The combined bruxism classification and the sleep stages classification from the electroencephalogram channel (C4-P4) obtained a maximum specificity of 90% and an accuracy of 97%.  ...  [60] designed an automatic system for diagnosing sleep stages using time-frequency images of the EEG signals. Matsuura et al.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10217410">doi:10.3390/app10217410</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hinvcbjxivgnffnfqlvititiae">fatcat:hinvcbjxivgnffnfqlvititiae</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201024084550/https://res.mdpi.com/d_attachment/applsci/applsci-10-07410/article_deploy/applsci-10-07410-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/79/f5/79f5c115ad6b9a8e5f71b2a88b71b9176b9d2692.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10217410"> <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 Lightweight and Inexpensive In-ear Sensing System For Automatic Whole-night Sleep Stage Monitoring

Anh Nguyen, Raghda Alqurashi, Zohreh Raghebi, Farnoush Banaei-kashani, Ann C. Halbower, Tam Vu
<span title="">2016</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5j2fcrioqzharcoeonnjm7exwq" style="color: black;">Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM - SenSys &#39;16</a> </i> &nbsp;
Our evaluation results show that LIBS can monitor biosignals representing brain activities, eye movements, and muscle contractions with excellent fidelity such that it can be used for sleep stage classification  ...  We constructed a hardware prototype from off-the-shelf electronic components and used it to conduct 38 hours of sleep studies on 8 participants over a period of 30 days.  ...  The relationship between the sleep stages and EEG, EOG, and EMG signals is illustrated in Figure 2 .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2994551.2994562">doi:10.1145/2994551.2994562</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sensys/NguyenARKHV16.html">dblp:conf/sensys/NguyenARKHV16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qco7iaeuonayzkpx54nha7r63u">fatcat:qco7iaeuonayzkpx54nha7r63u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180404041825/http://mnslab.org:80/tamvu/paper/2016%20Inear%20Lan%20Anh.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/9d/78/9d780c997a56931629cc4b342c3664c0eb5f58d2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2994551.2994562"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>
&laquo; Previous Showing results 1 &mdash; 15 out of 2,327 results