Literatura académica sobre el tema "Biopotential detection"
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Artículos de revistas sobre el tema "Biopotential detection"
Mahdi, A. E. y L. Faggion. "Non-contact biopotential sensor for remote human detection". Journal of Physics: Conference Series 307 (17 de agosto de 2011): 012056. http://dx.doi.org/10.1088/1742-6596/307/1/012056.
Texto completoNoguchi, Yuta y Akira Kawai. "Surface Stability of SU-8 Film for Accurate Biopotential Detection". Journal of Photopolymer Science and Technology 25, n.º 6 (2012): 719–22. http://dx.doi.org/10.2494/photopolymer.25.719.
Texto completoNg, E. Y. K., W. K. Ng, L. S. J. Sim y U. Rajendra Acharya. "Numerical modelling of biopotential field for detection of breast tumour". Computers in Biology and Medicine 37, n.º 8 (agosto de 2007): 1121–32. http://dx.doi.org/10.1016/j.compbiomed.2006.10.006.
Texto completoKareem, Ghada. "DETECTION AND CLASSIFICATION OF ABNORMALITIES OF BIO-POTENTIAL ACTIVITY OF HEART". Journal of Southwest Jiaotong University 57, n.º 1 (28 de febrero de 2022): 673–82. http://dx.doi.org/10.35741/issn.0258-2724.57.1.60.
Texto completoAbd-Elbaki, Mohamed K. M., Hanan A. Matar y Naglaa R. E. Ismaeel. "Preparation and Characterization of Silk Fibroin-PANI Nanocomposites and Their Application for Electrophysiological Signals Recording". American Journal of Agricultural Science, Engineering, and Technology 6, n.º 3 (3 de diciembre de 2022): 142–49. http://dx.doi.org/10.54536/ajaset.v6i3.1009.
Texto completoKataoka, Hiroshi, Tsunenori Takatani y Kazuma Sugie. "Two-Channel Portable Biopotential Recording System Can Detect REM Sleep Behavioral Disorder: Validation Study with a Comparison of Polysomnography". Parkinson's Disease 2022 (24 de febrero de 2022): 1–5. http://dx.doi.org/10.1155/2022/1888682.
Texto completoGolparvar, Ata Jedari y Murat Kaya Yapici. "Toward graphene textiles in wearable eye tracking systems for human–machine interaction". Beilstein Journal of Nanotechnology 12 (11 de febrero de 2021): 180–89. http://dx.doi.org/10.3762/bjnano.12.14.
Texto completoDonisi, Leandro, Giuseppe Cesarelli, Noemi Pisani, Alfonso Maria Ponsiglione, Carlo Ricciardi y Edda Capodaglio. "Wearable Sensors and Artificial Intelligence for Physical Ergonomics: A Systematic Review of Literature". Diagnostics 12, n.º 12 (5 de diciembre de 2022): 3048. http://dx.doi.org/10.3390/diagnostics12123048.
Texto completoCao, Tianao, Dan Liu, Qisong Wang, Ou Bai y Jinwei Sun. "Surface Electromyography-Based Action Recognition and Manipulator Control". Applied Sciences 10, n.º 17 (22 de agosto de 2020): 5823. http://dx.doi.org/10.3390/app10175823.
Texto completoVajravelu, Ashok, Muhammad Mahadi Bin Abdul Jamil, Mohd Helmy Bin Abd Wahab, Wan Suhaimizan Bin Wan Zaki, Vibin Mammen Vinod, Karthik Ramasamy Palanisamy y Gousineyah Nageswara Rao. "Nanocomposite-Based Electrode Structures for EEG Signal Acquisition". Crystals 12, n.º 11 (27 de octubre de 2022): 1526. http://dx.doi.org/10.3390/cryst12111526.
Texto completoTesis sobre el tema "Biopotential detection"
Chen, Chang Hao. "Instrumentation amplifier and filter design for biopotential acquisition system". Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2182898.
Texto completoMa, Chon Teng. "Biopotential readout front-end circuits using frequency-translation filtering techniques". Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2182904.
Texto completoZhang, Tan Tan. "Sub-nano-watt subthreshold-biased source-follower-based LPF for biopotential signal acquisition systems". Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2182899.
Texto completoButler, Nickolas Andrew. "Development of a Myoelectric Detection Circuit Platform for Computer Interface Applications". DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/1981.
Texto completoLi, Jin Tao. "A novel readout front-end circuit topology for flexible biopotential signal acquisition system = 一種適用於靈活採集生物電信號的新型前端電路結構". Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2144082.
Texto completoNonclercq, Antoine. "New strategies of acquisition and processing of encephalographic biopotentials". Doctoral thesis, Universite Libre de Bruxelles, 2007. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210711.
Texto completoSince the biopotentials produced by the upper parts of the brain have an amplitude of about one microvolt, the measurements performed by an EEG are exposed to many risks.
Moreover, since the present tendency is measure those signals over periods of several hours, or even several days, human analysis of the recording becomes extremely long and difficult. The use of signal analysis techniques for the help of paroxysm detection with clinical interest within the electroencephalogram becomes therefore almost essential. However the performance of many automatic detection algorithms becomes significantly degraded by the presence of interference: the quality of the recordings is therefore fundamental.
This thesis explores the benefits that electronics and signal processing could bring to electroencephalography, aiming at improving the signal quality and semi-automating the data processing.
These two aspects are interdependent because the performance of any semi-automation of the data processing depends on the quality of the acquired signal. Special attention is focused on the interaction between these two goals and attaining the optimal hardware/software pair.
This thesis offers an overview of the medical electroencephalographic acquisition chain and also of its possible improvements.
The conclusions of this work may be extended to some other cases of biological signal amplification such as the electrocardiogram (ECG) and the electromyogram (EMG). Moreover, such a generalization would be easier, because their signals have a wider amplitude and are therefore more resistant toward interference.
Doctorat en sciences appliquées
info:eu-repo/semantics/nonPublished
Capítulos de libros sobre el tema "Biopotential detection"
Supriya, Supriya, Siuly Siuly, Hua Wang y Yanchun Zhang. "Weighted complex network based framework for epilepsy detection from EEG signals". En Modelling and Analysis of Active Biopotential Signals in Healthcare, Volume 1. IOP Publishing, 2020. http://dx.doi.org/10.1088/978-0-7503-3279-8ch3.
Texto completoKhare, Smith K., Varun Bajaj y G. R. Sinha. "Automatic drowsiness detection based on variational non-linear chirp mode decomposition using electroencephalogram signals". En Modelling and Analysis of Active Biopotential Signals in Healthcare, Volume 1. IOP Publishing, 2020. http://dx.doi.org/10.1088/978-0-7503-3279-8ch5.
Texto completoSubasi, Abdulhamit, Turker Tuncer, Sengul Dogan y Dahiru Tanko. "Local binary pattern based feature extraction and machine learning for epileptic seizure prediction and detection". En Modelling and Analysis of Active Biopotential Signals in Healthcare, Volume 2. IOP Publishing, 2020. http://dx.doi.org/10.1088/978-0-7503-3411-2ch6.
Texto completoActas de conferencias sobre el tema "Biopotential detection"
Lin, Feiyan, Michael McKnight, James Dieffenderfer, Eric Whitmire, Tushar Ghosh y Alper Bozkurt. "Microfabricated impedance sensors for concurrent tactile, biopotential, and wetness detection". En 2014 IEEE Sensors. IEEE, 2014. http://dx.doi.org/10.1109/icsens.2014.6985252.
Texto completoGagnon-Turcotte, G., C. O. Dufresne Camaro y B. Gosselin. "Comparison of low-power biopotential processors for on-the-fly spike detection". En 2015 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2015. http://dx.doi.org/10.1109/iscas.2015.7168755.
Texto completoDiab, Maha S. y Soliman A. Mahmoud. "14:5nW; 30 dB Analog Front-End in 90-nm Technology for Biopotential Signal Detection". En 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. http://dx.doi.org/10.1109/tsp49548.2020.9163572.
Texto completoShokouhmand, Arash, Haoran Wen, Samiha Khan, Joseph A. Puma, Amisha Patel, Philip Green, Farrokh Ayazi y Negar Tavassolian. "Detection of Left Ventricular Ejection Fraction Abnormality Using Fusion of Acoustic and Biopotential Characteristics of Precordium". En 2022 IEEE Sensors. IEEE, 2022. http://dx.doi.org/10.1109/sensors52175.2022.9967355.
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