Radar-Based Human Motion Recognition by Using Vital Signs with ECA-CNN

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dc.contributor.authorChen, K.
dc.contributor.authorGu, M.
dc.contributor.authorChen, Z.
dc.coverage.issue2cs
dc.coverage.volume32cs
dc.date.accessioned2023-10-11T07:43:39Z
dc.date.available2023-10-11T07:43:39Z
dc.date.issued2023-06cs
dc.description.abstractRadar technologies reserve a large latent capacity in dealing with human motion recognition (HMR). For the problem that it is challenging to quickly and accurately classify various complex motions, an HMR algorithm combing the attention mechanism and convolution neural network (ECA-CNN) using vital signs is proposed. Firstly, the original radar signal is obtained from human chest wall displacement. Chirp-Z Transform (CZT) algorithm is adopted to refine and amplify the narrow band spectrum region of interest in the global spectrum of the signal, and accurate information on the specific band is extracted. Secondly, six time-domain features were extracted for the neural network. Finally, an ECA-CNN is designed to improve classification accuracy, with a small size, fast speed, and high accuracy of 98%. This method can improve the classification accuracy and efficiency of the network to a large extent. Besides, the size of this network is 100 kb, which is convenient to integrate into the embedded devices.en
dc.formattextcs
dc.format.extent248-255cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2023 vol. 32, č. 2, s. 248-255. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2023.0248en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/214327
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2023/23_02_0248_0255.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectHuman motion recognitionen
dc.subjectvital signsen
dc.subjectEfficient Channel Attention enabled Convolutional Neural Network (ECA-CNN)en
dc.subjectradaren
dc.titleRadar-Based Human Motion Recognition by Using Vital Signs with ECA-CNNen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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