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dc.contributor.authorZhao, Wenshan
dc.contributor.authorMa, Lina
dc.contributor.authorZhang, Yuzhen
dc.contributor.authorHe, Yigang
dc.contributor.authorSun, Yichuang
dc.date.accessioned2020-05-19T00:10:16Z
dc.date.available2020-05-19T00:10:16Z
dc.date.issued2020-02-13
dc.identifier.citationZhao , W , Ma , L , Zhang , Y , He , Y & Sun , Y 2020 , ' Realization of Analog Wavelet Filter using Hybrid Genetic Algorithm for On-line Epileptic Event Detection ' , IEEE Access , vol. 8 , 8998264 , pp. 33137-33150 . https://doi.org/10.1109/ACCESS.2020.2973892
dc.identifier.issn2169-3536
dc.identifier.otherPURE: 19587768
dc.identifier.otherPURE UUID: 63db1000-5f9c-466e-96a9-991e77790073
dc.identifier.otherScopus: 85080886565
dc.identifier.urihttp://hdl.handle.net/2299/22718
dc.description© 2020 The Author(s). This open access work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.
dc.description.abstractAs the evolution of traditional electroencephalogram (EEG) monitoring unit for epilepsy diagnosis, wearable ambulatory EEG (WAEEG) system transmits EEG data wirelessly, and can be made miniaturized, discrete and social acceptable. To prolong the battery lifetime, analog wavelet filter is used for epileptic event detection in WAEEG system to achieve on-line data reduction. For mapping continuous wavelet transform to analog filter implementation with low-power consumption and high approximation accuracy, this paper proposes a novel approximation method to construct the wavelet base in analog domain, in which the approximation process in frequency domain is considered as an optimization problem by building a mathematical model with only one term in the numerator. The hybrid genetic algorithm consisting of genetic algorithm and quasi-Newton method is employed to find the globally optimum solution, taking required stability into account. Experiment results show that the proposed method can give a stable analog wavelet base with simple structure and higher approximation accuracy compared with existing method, leading to a better spike detection accuracy. The fourth-order Marr wavelet filter is designed as an example using Gm-C filter structure based on LC ladder simulation, whose power consumption is only 33.4 pW at 2.1Hz. Simulation results show that the design method can be used to facilitate low power and small volume implementation of on-line epileptic event detector.en
dc.format.extent14
dc.language.isoeng
dc.relation.ispartofIEEE Access
dc.subjectWavelet transform
dc.subjectanalog filter
dc.subjectepileptic event detection
dc.subjecthybrid genetic algorithm
dc.subjectrational approximation
dc.subjectwireless ambulatory electroencephalogram
dc.subjectComputer Science(all)
dc.subjectMaterials Science(all)
dc.subjectEngineering(all)
dc.titleRealization of Analog Wavelet Filter using Hybrid Genetic Algorithm for On-line Epileptic Event Detectionen
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionCommunications and Intelligent Systems
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85080886565&partnerID=8YFLogxK
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1109/ACCESS.2020.2973892
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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