{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T16:33:56Z","timestamp":1759336436644,"version":"3.37.3"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T00:00:00Z","timestamp":1675123200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T00:00:00Z","timestamp":1675123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1007\/s11517-023-02770-w","type":"journal-article","created":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T14:04:23Z","timestamp":1675173863000},"page":"1225-1238","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Applying correlation analysis to electrode optimization in source domain"],"prefix":"10.1007","volume":"61","author":[{"given":"Yuxin","family":"Dong","sequence":"first","affiliation":[]},{"given":"Linlin","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0718-8555","authenticated-orcid":false,"given":"Mingai","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"2770_CR1","doi-asserted-by":"publisher","first-page":"87","DOI":"10.3389\/fncom.2019.00087","volume":"13","author":"S Saha","year":"2020","unstructured":"Saha S, Baumert M (2020) Intra-and inter-subject variability in EEG-based sensorimotor brain computer interface: a review. Front Comput Neurosci 13:87. https:\/\/doi.org\/10.3389\/fncom.2019.00087","journal-title":"Front Comput Neurosci"},{"key":"2770_CR2","doi-asserted-by":"publisher","first-page":"546656","DOI":"10.3389\/fnins.2020.546656","volume":"14","author":"S Fathima","year":"2021","unstructured":"Fathima S, Kore SK (2021) Formulation of the challenges in brain-computer interfaces as optimization problems-a review. Front Neurosci 14:546656. https:\/\/doi.org\/10.3389\/fnins.2020.546656","journal-title":"Front Neurosci"},{"key":"2770_CR3","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1007\/978-3-030-72254-8_8","volume":"1362","author":"W Fr\u0105cz","year":"2021","unstructured":"Fr\u0105cz W (2021) Techniques, challenges and use in rehabilitation medicine of EEG-based brain-computer interfaces systems. Control, Computer Eng Neurosci 1362:72\u201378. https:\/\/doi.org\/10.1007\/978-3-030-72254-8_8","journal-title":"Control, Computer Eng Neurosci"},{"key":"2770_CR4","doi-asserted-by":"publisher","first-page":"312","DOI":"10.3389\/fnhum.2018.00312","volume":"12","author":"M Tariq","year":"2018","unstructured":"Tariq M, Trivailo PM, Simic M (2018) EEG-based BCI control schemes for lower-limb assistive-robots. Front Hum Neurosci 12:312. https:\/\/doi.org\/10.3389\/fnhum.2018.00312","journal-title":"Front Hum Neurosci"},{"key":"2770_CR5","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.neuroimage.2014.12.026","volume":"108","author":"R Bauer","year":"2015","unstructured":"Bauer R, Fels M, Vukeli\u0107 M, Ziemann U, Gharabaghi A (2015) Bridging the gap between motor imagery and motor execution with a brain-robot interface. Neuroimage 108:319\u2013327. https:\/\/doi.org\/10.1016\/j.neuroimage.2014.12.026","journal-title":"Neuroimage"},{"issue":"18","key":"2770_CR6","doi-asserted-by":"publisher","first-page":"6285","DOI":"10.3390\/s21186285","volume":"21","author":"A Palumbo","year":"2021","unstructured":"Palumbo A, Gramigna V, Calabrese B, Ielpo N (2021) Motor-imagery EEG-based BCIs in wheelchair movement and control: a systematic literature review. Sensors 21(18):6285. https:\/\/doi.org\/10.3390\/s21186285","journal-title":"Sensors"},{"issue":"4","key":"2770_CR7","doi-asserted-by":"publisher","first-page":"40","DOI":"10.3724\/SP.J.1218.2011.00307","volume":"8","author":"B Xu","year":"2011","unstructured":"Xu B, Peng S, Song A, Yang R, Pan L (2011) Robot-aided upper-limb rehabilitation based on motor imagery EEG. Int J Adv Robot Syst 8(4):40. https:\/\/doi.org\/10.3724\/SP.J.1218.2011.00307","journal-title":"Int J Adv Robot Syst"},{"issue":"3","key":"2770_CR8","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1097\/00006534-195205000-00008","volume":"52","author":"GH Klem","year":"1999","unstructured":"Klem GH, L\u00fcders HO, Jasper HH, Elger C (1999) The ten-twenty electrode system of the international federation. The International Federation of Clinical Neurophysiology. Electroencephalogr Clin Neurophysiol 52(3):3\u20136. https:\/\/doi.org\/10.1097\/00006534-195205000-00008","journal-title":"Electroencephalogr Clin Neurophysiol"},{"issue":"6","key":"2770_CR9","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1016\/S0013-4694(98)00004-2","volume":"106","author":"J Le","year":"1998","unstructured":"Le J, Lu M, Pellouchoud E, Gevins A (1998) A rapid method for determining standard 10\/10 electrode positions for high resolution EEG studies. Electroencephalogr Clin Neurophysiol 106(6):554\u2013558. https:\/\/doi.org\/10.1016\/S0013-4694(98)00004-2","journal-title":"Electroencephalogr Clin Neurophysiol"},{"issue":"4","key":"2770_CR10","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1016\/S1388-2457(00)00527-7","volume":"112","author":"R Oostenveld","year":"2001","unstructured":"Oostenveld R, Praamstra P (2001) The five percent electrode system for high-resolution EEG and ERP measurements. Clin Neurophysiol 112(4):713\u2013719. https:\/\/doi.org\/10.1016\/S1388-2457(00)00527-7","journal-title":"Clin Neurophysiol"},{"key":"2770_CR11","doi-asserted-by":"publisher","first-page":"227","DOI":"10.3389\/fnins.2018.00227","volume":"12","author":"J Meng","year":"2018","unstructured":"Meng J, Edelman BJ, Olsoe J, Jacobs G, Zhang S, Beyko A, He B (2018) A study of the effects of electrode number and decoding algorithm on online EEG-based BCI behavioral performance. Front Neurosci 12:227. https:\/\/doi.org\/10.3389\/fnins.2018.00227","journal-title":"Front Neurosci"},{"key":"2770_CR12","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1007\/s10462-019-09694-8","volume":"53","author":"MZ Baig","year":"2020","unstructured":"Baig MZ, Aslam N, Shum HPH (2020) Filtering techniques for channel selection in motor imagery EEG applications: a survey. Artif Intell Rev 53:1207\u20131232. https:\/\/doi.org\/10.1007\/s10462-019-09694-8","journal-title":"Artif Intell Rev"},{"issue":"3","key":"2770_CR13","doi-asserted-by":"publisher","first-page":"035701","DOI":"10.1088\/1361-6501\/abc205","volume":"32","author":"Q Wang","year":"2020","unstructured":"Wang Q, Cao T, Liu D, Zhang M, Lu J, Bai O, Sun J (2020) Motor imagery channel selection method based on SVM-CCA-CS. Meas Sci Technol 32(3):035701. https:\/\/doi.org\/10.1088\/1361-6501\/abc205","journal-title":"Meas Sci Technol"},{"issue":"3","key":"2770_CR14","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1016\/j.clinph.2014.05.038","volume":"126","author":"A Sohrabpour","year":"2015","unstructured":"Sohrabpour A, Lu Y, Kankirawatana P, Blount J, Kim H, He B (2015) Effect of EEG electrode number on epileptic source localization in pediatric patients. Clin Neurophysiol 126(3):472\u2013480. https:\/\/doi.org\/10.1016\/j.clinph.2014.05.038","journal-title":"Clin Neurophysiol"},{"key":"2770_CR15","doi-asserted-by":"publisher","unstructured":"Joadde M A M, Siuly S, Kabir E. A new way of channel selection in the motor imagery classification for BCI applications (2018) In Proceedings of international conference on health information science, HIS 2018, Cairns, QLD, Australia 110\u2013119. https:\/\/doi.org\/10.3389\/fnins.2018.00227","DOI":"10.3389\/fnins.2018.00227"},{"key":"2770_CR16","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1186\/s13634-015-0251-9","volume":"1","author":"T Alotaiby","year":"2015","unstructured":"Alotaiby T, El-Samie FEA, Alshebeili SA (2015) Ahmad I (2015) A review of channel selection algorithms for EEG signal processing. EURASIP J Adv Signal Process 1:66. https:\/\/doi.org\/10.1186\/s13634-015-0251-9","journal-title":"EURASIP J Adv Signal Process"},{"key":"2770_CR17","doi-asserted-by":"publisher","unstructured":"Fauzi H, Shapiai MI, Abdullah SS, Ibrahim Z (2018) Automatic energy extraction methods for EEG channel selection. 2018 international conference on control, electronics, renewable energy and communications (ICCEREC), 70\u201375. https:\/\/doi.org\/10.1109\/ICCEREC.2018.8711995.","DOI":"10.1109\/ICCEREC.2018.8711995"},{"key":"2770_CR18","doi-asserted-by":"publisher","unstructured":"Feng J K, Jin J, Daly I, Zhou J, Niu Y,\u00a0Wang X, Cichocki A (2019) An optimized channel selection method based on multifrequency CSP-rank for motor imagery-based BCI system. Comput Intell Neurosci 2019. https:\/\/doi.org\/10.1155\/2019\/8068357","DOI":"10.1155\/2019\/8068357"},{"key":"2770_CR19","doi-asserted-by":"publisher","first-page":"107393","DOI":"10.1016\/j.patcog.2020.107393","volume":"105","author":"ZAA Alyasseri","year":"2020","unstructured":"Alyasseri ZAA, Khader AT, Al-Betar MA, Alomari OA (2020) Person identification using EEG channel selection with hybrid flower pollination algorithm. Pattern Recognit 105:107393. https:\/\/doi.org\/10.1016\/j.patcog.2020.107393","journal-title":"Pattern Recognit"},{"issue":"2","key":"2770_CR20","doi-asserted-by":"publisher","first-page":"558","DOI":"10.1109\/TCYB.2019.2963709","volume":"51","author":"F Qi","year":"2021","unstructured":"Qi F, Wu W, Yu ZL, Gu Z, Wen Z, Yu T, Li Y (2021) Spatiotemporal-filtering-based channel selection for single-trial EEG classification. IEEE T Cybern 51(2):558\u2013567. https:\/\/doi.org\/10.1109\/TCYB.2019.2963709","journal-title":"IEEE T Cybern"},{"key":"2770_CR21","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.neucom.2016.05.035","volume":"207","author":"Z Qiu","year":"2016","unstructured":"Qiu Z, Jin J, Lam HK, Zhang Y, Wang X, Cichocki A (2016) Improved SFFS method for channel selection in motor imagery based BCI. Neurocomputing 207:519\u2013527. https:\/\/doi.org\/10.1016\/j.neucom.2016.05.035","journal-title":"Neurocomputing"},{"issue":"10","key":"2770_CR22","doi-asserted-by":"publisher","first-page":"2195","DOI":"10.1016\/j.clinph.2004.06.001","volume":"115","author":"CM Michel","year":"2004","unstructured":"Michel CM, Murray MM, Lantz G, Gonzalez S, Spinelli L, Peralta RG (2004) EEG source imaging. Clin Neurophysiol 115(10):2195\u20132222. https:\/\/doi.org\/10.1016\/j.clinph.2004.06.001","journal-title":"Clin Neurophysiol"},{"issue":"2","key":"2770_CR23","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1109\/MSMC.2017.2778458","volume":"4","author":"VS Handiru","year":"2018","unstructured":"Handiru VS, Vinod AP, Guan C (2018) EEG source imaging of movement decoding: the state of the art and future directions. IEEE Trans Neural Syst Rehabil Eng 4(2):14\u201323. https:\/\/doi.org\/10.1109\/MSMC.2017.2778458","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"1","key":"2770_CR24","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1186\/1743-0003-5-25","volume":"5","author":"R Grech","year":"2008","unstructured":"Grech R, Cassar T, Muscat J, Camilleri KP, Fabri SG, Zervakis M, Xanthopoulos P, Sakkalis V, Vanrumste B (2008) Review on solving the inverse problem in EEG source analysis. J NeuroEng Rehabil 5(1):25. https:\/\/doi.org\/10.1186\/1743-0003-5-25","journal-title":"J NeuroEng Rehabil"},{"issue":"2019","key":"2770_CR25","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1016\/j.neucom.2019.02.006","volume":"339","author":"MA Li","year":"2019","unstructured":"Li MA, Wang YF, Jia SM, Sun YJ, Yang JF (2019) Decoding of motor imagery EEG based on brain source estimation. Neurocomputing 339(2019):182\u2013193. https:\/\/doi.org\/10.1016\/j.neucom.2019.02.006","journal-title":"Neurocomputing"},{"key":"2770_CR26","doi-asserted-by":"publisher","unstructured":"Hossain MS, Saha S, Habib MA, Noman AA, Sharfuddin T, Ahmed KI (2016) Application of wavelet-based maximum entropy on the mean in channel optimization for BCI. Presented at 2016 International Conference on Medical Engineering, Health Informatics and Technology, Dhaka, Bangladesh 1\u20135. https:\/\/doi.org\/10.1109\/MEDITEC.2016.7835394","DOI":"10.1109\/MEDITEC.2016.7835394"},{"key":"2770_CR27","doi-asserted-by":"publisher","unstructured":"Li M A, Zhang C, Sun Y J (2017) Channel selection with EEG source imaging. 2017 2nd international conference on computational modeling, simulation and applied mathematics (CMSAM2017), Beijing, China 540\u2013545. https:\/\/doi.org\/10.12783\/dtcse\/cmsam2017\/16430","DOI":"10.12783\/dtcse\/cmsam2017\/16430"},{"issue":"4","key":"2770_CR28","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/S0074-7742(08)60008-2","volume":"3","author":"H Nakahama","year":"1961","unstructured":"Nakahama H (1961) Functional organization of somatic areas of the cerebral cortex. Int Rev Neurobiol 3(4):187\u2013250. https:\/\/doi.org\/10.1016\/S0074-7742(08)60008-2","journal-title":"Int Rev Neurobiol"},{"key":"2770_CR29","doi-asserted-by":"publisher","unstructured":"Jacobs K M (2011) Brodmann\u2019s areas of the cortex.\u00a0Encyclopedia of clinical neuropsychology. Springer New York, New York 459. https:\/\/doi.org\/10.1007\/978-3-319-57111-9_301","DOI":"10.1007\/978-3-319-57111-9_301"},{"key":"2770_CR30","doi-asserted-by":"publisher","unstructured":"Blankertz B, M\u00fcller K R, Krusienski D, Schalk G, Wolpaw J R, Schlogl A, Pfurtscheller G, Millan J R, Schroder M, Birbaumer N (2005) Bci competition iii. Fraunhofer FIRST. IDA, http:\/\/ida.first.fraunhofer.de\/projects\/bci\/competition_iii. https:\/\/doi.org\/10.1109\/tnsre.2006.875642","DOI":"10.1109\/tnsre.2006.875642"},{"key":"2770_CR31","doi-asserted-by":"publisher","first-page":"55","DOI":"10.3389\/fnins.2012.00055","volume":"6","author":"M Tangermann","year":"2012","unstructured":"Tangermann M, M\u00fcller KR, Aertsen A, Birbaumer N, Braun C, Brunner C, Leeb R, Mehring C, Miller KJ, M\u00fcller-Putz GR, Nolte G, Pfurtscheller G, Preissl H, Schalk G, Schl\u00f6gl A, Vidaurre C, Stephan S, Blankertz B (2012) Review of the BCI competition IV. Front Neurosci 6:55. https:\/\/doi.org\/10.3389\/fnins.2012.00055","journal-title":"Front Neurosci"},{"key":"2770_CR32","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1016\/j.clinph.2008.11.015","volume":"120","author":"C Neuper","year":"2009","unstructured":"Neuper C, Scherer R, Wriessnegger S, Pfurtscheller G (2009) Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain-computer interface. Clin Neurophysiol 120:239\u2013247. https:\/\/doi.org\/10.1016\/j.clinph.2008.11.015","journal-title":"Clin Neurophysiol"},{"key":"2770_CR33","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.jneumeth.2015.08.015","volume":"256","author":"J Song","year":"2015","unstructured":"Song J, Davey C, Poulsen C, Luu P, Turovets S, Anderson E, Li K, Tucker D (2015) EEG source localization: sensor density and head surface coverage. J Neurosci Methods 256:9\u201321. https:\/\/doi.org\/10.1016\/j.jneumeth.2015.08.015","journal-title":"J Neurosci Methods"},{"issue":"8","key":"2770_CR34","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1109\/10.704867","volume":"45","author":"M Fuchs","year":"1998","unstructured":"Fuchs M, Drenckhahn R, Wischmann H, Wagner M (1998) An improved boundary element method for realistic volume-conductor modeling. IEEE Trans Biomed Eng 45(8):980\u2013997. https:\/\/doi.org\/10.1109\/10.704867","journal-title":"IEEE Trans Biomed Eng"},{"key":"2770_CR35","doi-asserted-by":"publisher","unstructured":"Jatoi M A, Kamel N, Faye I, Malik A S, Bornot J M, Begum T (2019) BEM based solution of forward problem for brain source estimation.\u00a02015 IEEE international conference on signal and image processing applications (ICSIPA), Kuala Lumpur 180\u2013185. https:\/\/doi.org\/10.1109\/ICSIPA.2015.7412186","DOI":"10.1109\/ICSIPA.2015.7412186"},{"issue":"1","key":"2770_CR36","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1186\/1475-925X-9-45","volume":"9","author":"A Gramfort","year":"2010","unstructured":"Gramfort A, Papadopoulo T, Olivi E, Clerc M (2010) OpenMEEG: opensource software for quasistatic bioelectromagnetics. Biomed Eng Online 9(1):45. https:\/\/doi.org\/10.1186\/1475-925X-9-45","journal-title":"Biomed Eng Online"},{"issue":"11","key":"2770_CR37","doi-asserted-by":"publisher","first-page":"1194","DOI":"10.1002\/hbm.20345","volume":"28","author":"JL Lancaster","year":"2007","unstructured":"Lancaster JL, Tordesillas-Guti\u00e9rrez D, Martinez M, Evans A, Zilles K, Mazziotta JC, Fox PT (2007) Bias between MNI and talairach coordinates analyzed using the ICBM-152 brain template. Hum Brain Mapp 28(11):1194\u20131205. https:\/\/doi.org\/10.1002\/hbm.20345","journal-title":"Hum Brain Mapp"},{"key":"2770_CR38","first-page":"5","volume":"24","author":"RD Pascual-Marqui","year":"2002","unstructured":"Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 24:5\u201312","journal-title":"Methods Find Exp Clin Pharmacol"},{"key":"2770_CR39","doi-asserted-by":"publisher","unstructured":"Grossmann A, Kronland-Martinet R, Morlet J (1990) Reading and understanding continuous wavelet transforms. Wavelets. Springer, Berlin, Heidelberg 2\u201320. https:\/\/doi.org\/10.1007\/978-3-642-75988-8_1","DOI":"10.1007\/978-3-642-75988-8_1"},{"key":"2770_CR40","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.neucom.2020.03.055","volume":"402","author":"MA Li","year":"2020","unstructured":"Li MA, Dong YX, Sun YJ, Yang JF, Duan LJ (2020) Subject-based dipole selection for decoding motor imagery tasks. Neurocomputing 402:195\u2013208. https:\/\/doi.org\/10.1016\/j.neucom.2020.03.055","journal-title":"Neurocomputing"},{"issue":"5","key":"2770_CR41","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1016\/S1388-2457(98)00038-8","volume":"110","author":"J M\u00fcller-Gerking","year":"1999","unstructured":"M\u00fcller-Gerking J, Pfurtscheller G, Flyvbjerg H (1999) Designing optimal spatial filters for single-trial EEG classification in a movement task. Clin Neurophysiol 110(5):787\u2013798. https:\/\/doi.org\/10.1016\/S1388-2457(98)00038-8","journal-title":"Clin Neurophysiol"},{"issue":"12","key":"2770_CR42","doi-asserted-by":"publisher","first-page":"1356","DOI":"10.3390\/e22121356","volume":"22","author":"M Li","year":"2020","unstructured":"Li M, Wang R, Xu D (2020) An improved composite multiscale fuzzy entropy for feature extraction of MI-EEG. Entropy (Basel) 22(12):1356. https:\/\/doi.org\/10.3390\/e22121356","journal-title":"Entropy (Basel)"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-023-02770-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-023-02770-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-023-02770-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T01:13:24Z","timestamp":1681089204000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-023-02770-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,31]]},"references-count":42,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["2770"],"URL":"https:\/\/doi.org\/10.1007\/s11517-023-02770-w","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"type":"print","value":"0140-0118"},{"type":"electronic","value":"1741-0444"}],"subject":[],"published":{"date-parts":[[2023,1,31]]},"assertion":[{"value":"26 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 December 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 January 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}