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Artykuły w czasopismach na temat "EOG"
Reilly, Richard B., i T. Clive Lee. "Electrograms (ECG, EEG, EMG, EOG)". Technology and Health Care 18, nr 6 (19.11.2010): 443–58. http://dx.doi.org/10.3233/thc-2010-0604.
Pełny tekst źródłaWebster, John G. "Biomedical Instrumentation". International Journal of Systems Biology and Biomedical Technologies 3, nr 1 (styczeń 2015): 20–38. http://dx.doi.org/10.4018/ijsbbt.2015010102.
Pełny tekst źródłaSiting, Zhao, Kishan Kishan i Amiya Patanaik. "271 Sleep staging performance of a signal-agnostic cloud-based real-time sleep analytics platform". Sleep 44, Supplement_2 (1.05.2021): A108—A109. http://dx.doi.org/10.1093/sleep/zsab072.270.
Pełny tekst źródłaHossain, Md Shafayet, Sakib Mahmud, Amith Khandakar, Nasser Al-Emadi, Farhana Ahmed Chowdhury, Zaid Bin Mahbub, Mamun Bin Ibne Reaz i Muhammad E. H. Chowdhury. "MultiResUNet3+: A Full-Scale Connected Multi-Residual UNet Model to Denoise Electrooculogram and Electromyogram Artifacts from Corrupted Electroencephalogram Signals". Bioengineering 10, nr 5 (10.05.2023): 579. http://dx.doi.org/10.3390/bioengineering10050579.
Pełny tekst źródłaMartinek, Radek, Martina Ladrova, Michaela Sidikova, Rene Jaros, Khosrow Behbehani, Radana Kahankova i Aleksandra Kawala-Sterniuk. "Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach—Part III: Other Biosignals". Sensors 21, nr 18 (10.09.2021): 6064. http://dx.doi.org/10.3390/s21186064.
Pełny tekst źródłaD'Souza, Sandra, i N. Sriraam. "Design of EOG Signal Acquisition System Using Virtual Instrumentation". International Journal of Measurement Technologies and Instrumentation Engineering 4, nr 1 (styczeń 2014): 1–16. http://dx.doi.org/10.4018/ijmtie.2014010101.
Pełny tekst źródłaZhu, Hangyu, Cong Fu, Feng Shu, Huan Yu, Chen Chen i Wei Chen. "The Effect of Coupled Electroencephalography Signals in Electrooculography Signals on Sleep Staging Based on Deep Learning Methods". Bioengineering 10, nr 5 (10.05.2023): 573. http://dx.doi.org/10.3390/bioengineering10050573.
Pełny tekst źródłaAntony, Mary Judith, Baghavathi Priya Sankaralingam, Shakir Khan, Abrar Almjally, Nouf Abdullah Almujally i Rakesh Kumar Mahendran. "Brain–Computer Interface: The HOL–SSA Decomposition and Two-Phase Classification on the HGD EEG Data". Diagnostics 13, nr 17 (3.09.2023): 2852. http://dx.doi.org/10.3390/diagnostics13172852.
Pełny tekst źródłaTejedor, Javier, Constantino A. García, David G. Márquez, Rafael Raya i Abraham Otero. "Multiple Physiological Signals Fusion Techniques for Improving Heartbeat Detection: A Review". Sensors 19, nr 21 (29.10.2019): 4708. http://dx.doi.org/10.3390/s19214708.
Pełny tekst źródłaISHII, Chiharu. "Control of an Electric Wheelchair Based on EMG, EOG and EEG". Journal of the Japan Society for Precision Engineering 83, nr 11 (2017): 1006–9. http://dx.doi.org/10.2493/jjspe.83.1006.
Pełny tekst źródłaRozprawy doktorskie na temat "EOG"
Yue, Chongshi. "EOG Signals in Drowsiness Research". Thesis, Linköpings universitet, Biomedicinsk instrumentteknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81761.
Pełny tekst źródłaKelly, Graham. "Development of a compact, low-cost wireless device for biopotential acquisition". VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3559.
Pełny tekst źródłaNoureddin, Borna. "Online removal of eye movement and blink artifacts from EEG signals without EOG". Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27818.
Pełny tekst źródłaChocos, Ruiz Miguel Edgardo. "Estudo de filtros adaptativos para a remoção de artefatos de EOG em sinais de EEG". Florianópolis, SC, 1999. http://repositorio.ufsc.br/xmlui/handle/123456789/81217.
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Hapuarachchi, Pasan. "Feature selection and artifact removal in sleep stage classification". Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2879.
Pełny tekst źródłaHowever, if some of these artifacts are removed prior to analysis, their job will be become easier. Furthermore, one of the biggest motivations, of our team's research is the construction of a portable device that can analyze the sleep data as they are being collected. For this task, the sleep data must be analyzed completely automatically in order to make the classifications.
The research presented in this thesis concerns itself with the denoising and the feature selection aspects of the teams' goals. Since humans are able to process artifacts and ignore them prior to classification, an automated system should have the same capabilities or close to them. As such, the denoising step is performed to condition the data prior to any other stages of the sleep stage neoclassicisms. As mentioned before, the denoising step, by itself, is useful to human EEG technicians as well.
The denoising step in this research mainly looks at EOG artifacts and artifacts isolated to a single EEG channel, such as electrode pop artifacts. The first two algorithms uses Wavelets exclusively (BWDA and WDA), while the third algorithm is a mixture of Wavelets and In- dependent Component Analysis (IDA). With the BWDA algorithm, determining consistent thresholds proved to be a difficult task. With the WDA algorithm, the performance was better, since the selection of the thresholds was more straight-forward and since there was more control over defining the duration of the artifacts. The IDA algorithm performed inferior to the WDA algorithm. This could have been due to the small number of measurement channels or the automated sub-classifier used to select the denoised EEG signal from the set of ICA demixed signals.
The feature selection stage is extremely important as it selects the most pertinent features to make a particular classification. Without such a step, the classifier will have to process useless data, which might result in a poorer classification. Furthermore, unnecessary features will take up valuable computer cycles as well. In a portable device, due to battery consumption, wasting computer cycles is not an option. The research presented in this thesis shows the importance of a systematic feature selection step in EEG classification. The feature selection step produced excellent results with a maximum use of just 5 features. During automated classification, this is extremely important as the automated classifier will only have to calculate 5 features for each given epoch.
Karlsson, Johanna. "Identifying patterns in physiological parameters of expert and novice marksmen in simulation environment related to performance outcomes". Thesis, Linköpings universitet, Avdelningen för medicinsk teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139589.
Pełny tekst źródłaPeiris, Malik Tivanka Rajiv. "Lapses in Responsiveness: Characteristics and Detection from the EEG". Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/1261.
Pełny tekst źródłaMathew, Blesy Anu. "ENTROPY OF ELECTROENCEPHALOGRAM (EEG) SIGNALS CHANGES WITH SLEEP STATE". UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_theses/203.
Pełny tekst źródłaHartmann, Daniel Michael. "Einsatz eines superfundierten Retina-RPE-Choroidea Präparats vom Haushuhn (Gallus domesticus) zur Untersuchung pharmakologischer Wirkungen mittels in vitro elektroretinographischer Erfassung (ERG und EOG) von okulären Funktionen". [S.l. : s.n.], 2004. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB11679860.
Pełny tekst źródłaEscola, Henri. "Analyse et traitement de signaux physiologiques pour la mesure de l'action de substances pharmacologiques". Compiègne, 1993. http://www.theses.fr/1993COMPD593.
Pełny tekst źródłaKsiążki na temat "EOG"
Hereford, Jane. The competitive edge: Passing the North Carolina Eighth Grade EOG Test in Reading. Raleigh, NC: Contemporary Pub. Co. of Raleigh, 1997.
Znajdź pełny tekst źródłaHereford, Jane. The competitive edge: Passing the North Carolina eighth grade EOG test in mathematics. Raleigh, NC: Contemporary Pub. Co. of Raleigh, 1997.
Znajdź pełny tekst źródłaSlack, J. M. W. Egg & Ego. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-1420-5.
Pełny tekst źródłaGenquan, Feng. EKG and EEG multiphase information analysis. [New York]: American Medical Publishers, 1992.
Znajdź pełny tekst źródłaEgg & ego: An almost true story of life in the biology lab. New York: Springer, 1999.
Znajdź pełny tekst źródłaBudiman, Fajar. Eng ing eng. [Jakarta]: Jayakarta, 1990.
Znajdź pełny tekst źródłaGraeve, Laurent de. Ego, ego: Roman. Monaco: Editions du Rocher, 1999.
Znajdź pełny tekst źródłaLandt, Artur. Canon EOS Rebel T2: Includes, EOS Rebel K2, EOS Rebel TI, EOS 300X, EOS 3000V, EOS 300V. New York: Lark Books, 2005.
Znajdź pełny tekst źródłaZoehfeld, Kathleen Weidner. Disney's big egg, little egg. New York: Mouse Works, 1998.
Znajdź pełny tekst źródłaWeiss, Nicki. An egg is an egg. New York, N.Y: Trumpet Club, 1992.
Znajdź pełny tekst źródłaCzęści książek na temat "EOG"
Geller, Andrew M., Catherine M. Osborne i Robert L. Peiffer. "The ERG, EOG, and VEP in Rats". W Ocular Toxicology, 7–25. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1887-7_2.
Pełny tekst źródłaMishra, Ayushi, Vikrant Bhateja, Aparna Gupta, Apoorva Mishra i Suresh Chandra Satapathy. "Feature Fusion and Classification of EEG/EOG Signals". W Advances in Intelligent Systems and Computing, 793–99. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3600-3_76.
Pełny tekst źródłaChampaty, Biswajeet, D. N. Tibarewala, Biswajit Mohapatra i Kunal Pal. "Development of EOG and EMG-Based Multimodal Assistive Systems". W Medical Imaging in Clinical Applications, 285–310. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33793-7_13.
Pełny tekst źródłaGupta, Aparna, Vikrant Bhateja, Apoorva Mishra i Ayushi Mishra. "Autoregressive Modeling-Based Feature Extraction of EEG/EOG Signals". W Information and Communication Technology for Intelligent Systems, 731–39. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1747-7_72.
Pełny tekst źródłaGarcés Correa, Agustina, Lorena L. Orosco i Eric Laciar Leber. "Analysis of Parameters that Characterize Drowsiness Based on EEG, ECG and EOG Records". W IFMBE Proceedings, 461–67. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51723-5_57.
Pełny tekst źródłaKosmyna, Nataliya, Arnav Balyan i Eugene Hauptmann. "Decoding Visual Imagery Using EEG/EOG Glasses: A Pilot Study". W Proceedings of the Future Technologies Conference (FTC) 2022, Volume 2, 415–32. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18458-1_29.
Pełny tekst źródłaKosmyna, Nataliya, Arnav Balyan i Eugene Hauptmann. "Target Speaker Detection with EEG/EOG Glasses: A Pilot Study". W Proceedings of the Future Technologies Conference (FTC) 2022, Volume 2, 433–46. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18458-1_30.
Pełny tekst źródłaAbbas, Sherif N., i M. Abo-Zahhad. "Eye Blinking EOG Signals as Biometrics". W Signal Processing for Security Technologies, 121–40. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47301-7_5.
Pełny tekst źródłaEdlinger, Guenter, Christoph Kapeller, Arnau Espinosa, Sergi Torrellas, Felip Miralles i Christoph Guger. "Multi-modal Computer Interaction for Communication and Control Using EEG, EMG, EOG and Motion Sensors". W Universal Access in Human-Computer Interaction. Design Methods, Tools, and Interaction Techniques for eInclusion, 633–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39188-0_68.
Pełny tekst źródłaBhateja, Vikrant, Aparna Gupta, Apoorva Mishra i Ayushi Mishra. "Artificial Neural Networks Based Fusion and Classification of EEG/EOG Signals". W Advances in Intelligent Systems and Computing, 141–48. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3338-5_14.
Pełny tekst źródłaStreszczenia konferencji na temat "EOG"
Hirayama, Yoshikazu, Tomomi Takashina, Yuichi Watanabe, Kensaku Fukumoto, Miyuki Yanagi, Ryota Horie i Michiko Ohkura. "Physiological Signal- Driven Camera Using EOG, EEG, and ECG". W 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). IEEE, 2019. http://dx.doi.org/10.1109/aciiw.2019.8925063.
Pełny tekst źródłaChernyshov, George, Kirill Ragozin, Benjamin Tag i Kai Kunze. "EOG Glasses". W MobileHCI '19: 21st International Conference on Human-Computer Interaction with Mobile Devices and Services. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3338286.3344418.
Pełny tekst źródłaKim, Yun Seong, Haet Bit Lee, Jung Soo Kim, Hyun Jae Baek, Myung Suk Ryu i Kwang Suk Park. "ECG, EOG detection from helmet based system". W 6th International Special Topic Conference on Information Technology Applications in Biomedicine, 2007. IEEE, 2007. http://dx.doi.org/10.1109/itab.2007.4407378.
Pełny tekst źródłaAnh-Dao, Nguyen Thi, Tran Duc-Nghia, Nguyen Thi-Hao, Tran Duc-Tan i Nguyen Linh-Trung. "An effective procedure for reducing EOG and EMG artefacts from EEG signals". W 2013 International Conference on Advanced Technologies for Communications (ATC 2013). IEEE, 2013. http://dx.doi.org/10.1109/atc.2013.6698131.
Pełny tekst źródłaAhamed, Md Asif, Md Asraf-Ul Ahad, Md Hanif Ali Sohag i Mohiuddin Ahmad. "Development of low cost wireless biosignal acquisition system for ECG EMG and EOG". W 2015 2nd International Conference on Electrical Information and Communication Technologies (EICT). IEEE, 2015. http://dx.doi.org/10.1109/eict.2015.7391945.
Pełny tekst źródłaBulling, Andreas, Daniel Roggen i Gerhard Tröster. "Wearable EOG goggles". W the 27th international conference extended abstracts. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1520340.1520468.
Pełny tekst źródłaP L, Lekshmylal, Shiny G i Ashalatha Radhakrishnan. "Removal of EOG and EMG artifacts from EEG signals using blind source separation methods". W 2023 International Conference on Control, Communication and Computing (ICCC). IEEE, 2023. http://dx.doi.org/10.1109/iccc57789.2023.10165575.
Pełny tekst źródłaOlesen, Simon Dahl Thorsager, Rig Das, Mathias Dizon Olsson, Muhammad Ahmed Khan i Sadasivan Puthusserypady. "Hybrid EEG-EOG-based BCI system for Vehicle Control". W 2021 9th International Winter Conference on Brain-Computer Interface (BCI). IEEE, 2021. http://dx.doi.org/10.1109/bci51272.2021.9385300.
Pełny tekst źródłaVehkaoja, A. T., J. A. Verho, M. M. Puurtinen, N. M. Nojd, J. O. Lekkala i J. A. Hyttinen. "Wireless Head Cap for EOG and Facial EMG Measurements". W 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1615824.
Pełny tekst źródłaKalaganis, Fotis P., Manuel Seet, Kostas Georgiadis, Vangelis P. Oikonomou, Nikos A. Laskaris, Spiros Nikolopoulos, Ioannis Kompatsiaris, Maria Panou, Andrei Dragomir i Anastasios Bezerianos. "Reconstructing EOG From EEG Timeseries: A Spatial Filtering Approach". W 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2021. http://dx.doi.org/10.1109/embc46164.2021.9630320.
Pełny tekst źródłaRaporty organizacyjne na temat "EOG"
La Haye, Robert. National Spherical Torus Experiment Upgrade Collaborative Research on Configuration Optimization of Advanced Operating Scenarios and Control Including Macroscopy Stability EOG for Period 3/1/14 through 2/28/18. Office of Scientific and Technical Information (OSTI), marzec 2018. http://dx.doi.org/10.2172/1439061.
Pełny tekst źródłaHyde, Peter Alden. EOC Photos. Office of Scientific and Technical Information (OSTI), wrzesień 2019. http://dx.doi.org/10.2172/1565815.
Pełny tekst źródłaLi, Shangchen, Hongxun Ruan, Sheridan Titman i Haotian Xiang. ESG Spillovers. Cambridge, MA: National Bureau of Economic Research, maj 2023. http://dx.doi.org/10.3386/w31248.
Pełny tekst źródłaJensen, Melanie, Steven Schlasner, Kerryanne Leroux, Charles Gorecki i Nicholas Azzolina. Comparison of Non-EOR and EOR Life Cycle Assessments. Office of Scientific and Technical Information (OSTI), październik 2019. http://dx.doi.org/10.2172/1874451.
Pełny tekst źródłaBright, Ashleigh Bright. Egg producer and egg buyer disconnect: Exploring barriers and levers to increase cage-free egg production in China. Tiny Beam Fund, grudzień 2022. http://dx.doi.org/10.15868/socialsector.41288.
Pełny tekst źródłaScofield, Thomas C., Elizabeth Walter i Samuel J. Livingstone. Epidemic Outbreak Surveillance (EOS). Fort Belvoir, VA: Defense Technical Information Center, lipiec 2006. http://dx.doi.org/10.21236/ada483621.
Pełny tekst źródłaZhao, Jeffrey. ENG 572 Final Report. Office of Scientific and Technical Information (OSTI), lipiec 2020. http://dx.doi.org/10.2172/1645179.
Pełny tekst źródłaMorton, Paul E., i Glenn F. Wilson. Backpropagation and EEG Data. Fort Belvoir, VA: Defense Technical Information Center, październik 1988. http://dx.doi.org/10.21236/ada279073.
Pełny tekst źródłaGlickman, Matthew R., i Akaysha Tang. EEG analyses with SOBI. Office of Scientific and Technical Information (OSTI), luty 2009. http://dx.doi.org/10.2172/978914.
Pełny tekst źródłaZhao, Jeffrey. ENG 572 Interim Report. Office of Scientific and Technical Information (OSTI), kwiecień 2022. http://dx.doi.org/10.2172/1863849.
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