{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T15:27:33Z","timestamp":1767972453626,"version":"3.49.0"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876066"],"award-info":[{"award-number":["61876066"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tmm.2022.3217392","type":"journal-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:21:28Z","timestamp":1667517688000},"page":"7076-7088","source":"Crossref","is-referenced-by-count":8,"title":["A Robust Frequency-Domain-Based Graph Adaptive Network for Parkinson's Disease Detection From Gait Data"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4271-6483","authenticated-orcid":false,"given":"Cankun","family":"Zhong","sequence":"first","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0783-3585","authenticated-orcid":false,"given":"Wing W. Y.","family":"Ng","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-02182-5"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2019.2946194"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403118"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR56361.2022.9956330"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.03.032"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.113075"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2974323"},{"key":"ref16","article-title":"Discrete graph structure learning for forecasting multiple time series","author":"shang","year":"2021","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.02.009"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3068609"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3081930"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1111\/j.1460-9568.2005.04298.x"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0254841"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1002\/mds.20507"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1111\/j.1460-9568.2007.05810.x"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2007.894058"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16514"},{"key":"ref44","first-page":"30284","article-title":"Generalized jensen-shannon divergence loss for learning with noisy labels","volume":"34","author":"englesson","year":"2021","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3070127"},{"key":"ref49","article-title":"Deep graph structure learning for robust representations: A survey","author":"zhu","year":"2021"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11081395"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2020.09.011"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2011.09.106"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.11138\/FNeur\/2017.32.1.028"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.arr.2014.01.004"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1016\/j.bbe.2018.06.002","article-title":"Parkinson's disease monitoring from gait analysis via foot-worn sensors","volume":"38","author":"asuroglu","year":"2018","journal-title":"Journal of Biocybernetics and Biomedical Engineering"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.medengphy.2021.03.005","article-title":"Data-driven gait analysis for diagnosis and severity rating of Parkinson's disease","volume":"91","author":"balaji","year":"2021","journal-title":"Med Eng Phys"},{"key":"ref40","first-page":"1263","article-title":"Neural message passing for quantum chemistry","author":"gilmer","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2022.10.001"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01066"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3072345"},{"key":"ref36","first-page":"11458","article-title":"Robust graph representation learning via neural sparsification","author":"zheng","year":"2020","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1049\/sil2.12018"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2018.07.015"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3060280"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jddst.2020.101790"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2018.08.007"},{"key":"ref39","article-title":"Dropedge: Towards deep graph convolutional networks on node classification","author":"rong","year":"2020","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref38","article-title":"Categorical reparameterization with gumbel-softmax","author":"jang","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref24","article-title":"Supervised machine learning based gait classification system for early detection and stage classification of Parkinson's disease","volume":"94","author":"balaji","year":"2020","journal-title":"Appl Soft Comput"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1186\/s12984-020-00756-5"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jestch.2020.12.005"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2021.109249"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.icte.2016.10.005"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/OJEMB.2020.2966295"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.03.018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3056104"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2016.01.014"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441701"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/10016790\/09930650.pdf?arnumber=9930650","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T20:17:25Z","timestamp":1702325845000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9930650\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/tmm.2022.3217392","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}