{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T22:54:58Z","timestamp":1780959298884,"version":"3.54.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2024,5,4]],"date-time":"2024-05-04T00:00:00Z","timestamp":1714780800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,4]],"date-time":"2024-05-04T00:00:00Z","timestamp":1714780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Young Teacher Foundation of Henan Province","award":["No.2021GGJS093"],"award-info":[{"award-number":["No.2021GGJS093"]}]},{"name":"Key Science and Technology Program of Henan Province","award":["No.242102211058"],"award-info":[{"award-number":["No.242102211058"]}]},{"name":"Key Science and Technology Program of Henan Province","award":["No.232102211003"],"award-info":[{"award-number":["No.232102211003"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["No.62303427"],"award-info":[{"award-number":["No.62303427"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Doctor Natural Science Foundation of Zhengzhou University of Light Industry","award":["No.2022BSJJZK13"],"award-info":[{"award-number":["No.2022BSJJZK13"]}]},{"name":"Key Science Research Project of Colleges and Universities in Henan Province of China","award":["No.22A520046"],"award-info":[{"award-number":["No.22A520046"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1007\/s10586-024-04492-6","type":"journal-article","created":{"date-parts":[[2024,5,4]],"date-time":"2024-05-04T17:01:35Z","timestamp":1714842095000},"page":"10125-10139","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Innovative combination of covariance analysis-based sliding time window and task-related component analysis for steady-state visual evoked potential recognition"],"prefix":"10.1007","volume":"27","author":[{"given":"Jiaofen","family":"Nan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaifan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuang","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinghui","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanxin","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,4]]},"reference":[{"issue":"11","key":"4492_CR1","doi-asserted-by":"publisher","first-page":"4814","DOI":"10.1109\/TNNLS.2020.3015505","volume":"32","author":"J Jin","year":"2021","unstructured":"Jin, J., Xiao, R., Daly, I., Miao, Y., Wang, X., Cichocki, A.: Internal feature selection method of CSP based on L1-norm and Dempster-Shafer theory. IEEE Trans. Neural Netw. Learn. Syst. 32(11), 4814\u201325 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"10","key":"4492_CR2","doi-asserted-by":"publisher","first-page":"2153","DOI":"10.1109\/TNSRE.2020.3020975","volume":"28","author":"J Jin","year":"2020","unstructured":"Jin, J., Liu, C., Daly, I., Miao, Y., Li, S., Wang, X., et al.: Bispectrum-based channel selection for motor imagery based brain-computer interfacing. IEEE Trans. Neural Syst. Rehabil. Eng. 28(10), 2153\u201363 (2020)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"4492_CR3","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.neunet.2019.07.008","volume":"118","author":"J Jin","year":"2019","unstructured":"Jin, J., Miao, Y., Daly, I., Zuo, C., Hu, D., Cichocki, A.: Correlation-based channel selection and regularized feature optimization for MI-based BCI. Neural Netw. 118, 262\u201370 (2019)","journal-title":"Neural Netw."},{"issue":"6","key":"4492_CR4","doi-asserted-by":"publisher","first-page":"1292","DOI":"10.1109\/TNSRE.2019.2914916","volume":"27","author":"Y Yu","year":"2019","unstructured":"Yu, Y., Liu, Y., Yin, E., Jiang, J., Zhou, Z., Hu, D.: An asynchronous hybrid spelling approach based on EEG-EOG signals for Chinese character input. IEEE Trans. Neural Syst. Rehabil. Eng. 27(6), 1292\u2013302 (2019)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"8","key":"4492_CR5","doi-asserted-by":"publisher","first-page":"2266","DOI":"10.1109\/TBME.2019.2958641","volume":"67","author":"X Xiao","year":"2020","unstructured":"Xiao, X., Xu, M., Jin, J., Wang, Y., Jung, T.-P., Ming, D.: Discriminative canonical pattern matching for single-trial classification of ERP components. IEEE Trans. Biomed. Eng. 67(8), 2266\u201375 (2020)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"1","key":"4492_CR6","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1109\/TNSRE.2019.2956488","volume":"28","author":"J Jin","year":"2020","unstructured":"Jin, J., Li, S., Daly, I., Miao, Y., Liu, C., Wang, X., et al.: The study of generic model set for reducing calibration time in P300-based brain-computer interface. IEEE Trans. Neural Syst. Rehabil. Eng. 28(1), 3\u201312 (2020)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"6","key":"4492_CR7","doi-asserted-by":"publisher","first-page":"1172","DOI":"10.1109\/TBME.2006.889197","volume":"54","author":"Z Lin","year":"2007","unstructured":"Lin, Z., Zhang, C., Wu, W., Gao, X.: Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Trans. Biomed. Eng. 54(6), 1172\u20136 (2007)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"4492_CR8","doi-asserted-by":"crossref","unstructured":"Ravi, A., Heydari, N., Jiang, N.: User-Independent SSVEP BCI Using Complex FFT Features and CNN Classification. In: IEEE International Conference on Systems, Man and Cybernetics (SMC). 4175-4180 (2019)","DOI":"10.1109\/SMC.2019.8914258"},{"issue":"4","key":"4492_CR9","first-page":"331","volume":"1","author":"F Beverina","year":"2003","unstructured":"Beverina, F., Palmas, G., Silvoni, S., Piccione, F., Giove, S.: User adaptive BCIs: SSVEP and P300 based interfaces. PsychNology J. 1(4), 331\u201354 (2003)","journal-title":"PsychNology J."},{"key":"4492_CR10","doi-asserted-by":"publisher","first-page":"114905","DOI":"10.1109\/ACCESS.2021.3100478","volume":"9","author":"Y Peng","year":"2021","unstructured":"Peng, Y., Wong, C.M., Wang, Z., Rosa, A.C., Wang, H.T., Wan, F.: Fatigue detection in SSVEP-BCIs based on wavelet entropy of EEG. IEEE Access. 9, 114905\u201313 (2021)","journal-title":"IEEE Access."},{"key":"4492_CR11","doi-asserted-by":"crossref","unstructured":"Yin, H., Ji, Z., Lian, Z., Yang, Y., Liu, N., Wang, H.: Application of Kurtosis Based Dynamic Window to Enhance SSVEP Recognition. China Automation Congress (CAC). 2022, 571\u2013576 (2022)","DOI":"10.1109\/CAC57257.2022.10055430"},{"key":"4492_CR12","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2022.870871","volume":"14","author":"L Li","year":"2022","unstructured":"Li, L., Zhang, Y., Huang, L., Zhao, J., Wang, J., Liu, T.: Robot assisted treatment of hand functional rehabilitation based on visual motor imagination. Front. Aging Neurosci. 14, 870871 (2022)","journal-title":"Front. Aging Neurosci."},{"key":"4492_CR13","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1109\/TNSRE.2022.3185262","volume":"30","author":"N Guo","year":"2022","unstructured":"Guo, N., Wang, X., Duanmu, D., Huang, X., Li, X., Fan, Y., et al.: SSVEP-based brain computer interface controlled soft robotic glove for post-stroke hand function rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 30, 1737\u201344 (2022)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"4492_CR14","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/6819056","author":"X Zeng","year":"2017","unstructured":"Zeng, X., Zhu, G., Yue, L., Zhang, M., Xie, S.: A Feasibility study of SSVEP-based passive training on an ankle rehabilitation robot. J. Healthcare Eng. (2017). https:\/\/doi.org\/10.1155\/2017\/6819056","journal-title":"J. Healthcare Eng."},{"issue":"5","key":"4492_CR15","doi-asserted-by":"publisher","first-page":"710","DOI":"10.3390\/brainsci13050710","volume":"13","author":"S Zhu","year":"2023","unstructured":"Zhu, S., Yang, J., Ding, P., Wang, F., Gong, A., Fu, Y.: Optimization of SSVEP-BCI virtual reality stereo stimulation parameters based on knowledge graph. Brain Sci. 13(5), 710 (2023)","journal-title":"Brain Sci."},{"key":"4492_CR16","doi-asserted-by":"crossref","unstructured":"Hongtao, W., Ting, L., Zhenfeng, H.: Remote control of an electrical car with SSVEP-Based BCI. In: 2010 IEEE International Conference on Information Theory and Information Security, pp.\u00a0837\u2013840 (2010)","DOI":"10.1109\/ICITIS.2010.5689710"},{"issue":"11","key":"4492_CR17","doi-asserted-by":"publisher","first-page":"3156","DOI":"10.1109\/TBME.2013.2270283","volume":"60","author":"Y Li","year":"2013","unstructured":"Li, Y., Pan, J., Wang, F., Yu, Z.: A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans. Biomed. Eng. 60(11), 3156\u201366 (2013)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"4492_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105530","volume":"88","author":"X Mai","year":"2024","unstructured":"Mai, X., Ai, J., Ji, M., Zhu, X., Meng, J.: A hybrid BCI combining SSVEP and EOG and its application for continuous wheelchair control. Biomed. Signal Process. Control 88, 105530 (2024)","journal-title":"Biomed. Signal Process. Control"},{"issue":"15","key":"4492_CR19","doi-asserted-by":"publisher","first-page":"5019","DOI":"10.3390\/s21155019","volume":"21","author":"Y-J Chen","year":"2021","unstructured":"Chen, Y.-J., Chen, P.-C., Chen, S.-C., Wu, C.-M.: Denoising autoencoder-based feature extraction to robust SSVEP-based BCIs. Sensors. 21(15), 5019 (2021)","journal-title":"Sensors."},{"issue":"1","key":"4492_CR20","doi-asserted-by":"publisher","first-page":"40","DOI":"10.26599\/JNR.2020.9040003","volume":"8","author":"N Shi","year":"2020","unstructured":"Shi, N., Wang, L., Chen, Y., Yan, X., Yang, C., Wang, Y., et al.: Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) of Chinese speller for a patient with amyotrophic lateral sclerosis: A case report. J. Neurorestoratol. 8(1), 40\u201352 (2020)","journal-title":"J. Neurorestoratol."},{"issue":"3","key":"4492_CR21","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/aab2f2","volume":"15","author":"F Lotte","year":"2018","unstructured":"Lotte, F., Bougrain, L., Cichocki, A., Clerc, M., Congedo, M., Rakotomamonjy, A., et al.: A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update. J. Neural Eng. 15(3), 031005 (2018)","journal-title":"J. Neural Eng."},{"key":"4492_CR22","doi-asserted-by":"publisher","first-page":"2615","DOI":"10.1109\/TNSRE.2021.3132162","volume":"29","author":"W Ding","year":"2021","unstructured":"Ding, W., Shan, J., Fang, B., Wang, C., Sun, F., Li, X.: Filter bank convolutional neural network for short time-window steady-state visual evoked potential classification. IEEE Trans. Neural Syst. Rehabil. Eng. 29, 2615\u201324 (2021)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"24","key":"4492_CR23","doi-asserted-by":"publisher","first-page":"4231","DOI":"10.3390\/electronics11244231","volume":"11","author":"C Tong","year":"2022","unstructured":"Tong, C., Wang, H., Cai, J.: A novel turbo detector design for a high-speed SSVEP-based brain speller. Electronics 11(24), 4231 (2022)","journal-title":"Electronics"},{"key":"4492_CR24","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1109\/TNSRE.2022.3225878","volume":"31","author":"R Bian","year":"2023","unstructured":"Bian, R., Wu, H., Liu, B., Wu, D.: Small data least-squares transformation (sd-LST) for fast calibration of SSVEP-based BCIs. IEEE Trans. Neural Syst. Rehabil. Eng. 31, 446\u201355 (2023)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"2","key":"4492_CR25","doi-asserted-by":"publisher","first-page":"1221","DOI":"10.1007\/s10586-022-03678-0","volume":"26","author":"PJ Hong","year":"2023","unstructured":"Hong, P.J., Asghar, M.A., Ullah, A., Shorfuzzaman, M., Masud, M., Mehmood, R.M.: AI-based Bayesian inference scheme to recognize electroencephalogram signals for smart healthcare. Clust. Comput. 26(2), 1221\u201330 (2023)","journal-title":"Clust. Comput."},{"issue":"4","key":"4492_CR26","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ac823e","volume":"19","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Qiu, S., Zhang, Y., Wang, K., Wang, Y., He, H.: Bidirectional Siamese correlation analysis method for enhancing the detection of SSVEPs. J. Neural Eng. 19(4), 046027 (2022)","journal-title":"J. Neural Eng."},{"issue":"3","key":"4492_CR27","doi-asserted-by":"publisher","first-page":"483","DOI":"10.3390\/brainsci13030483","volume":"13","author":"D Xu","year":"2023","unstructured":"Xu, D., Tang, F., Li, Y., Zhang, Q., Feng, X.: An analysis of deep learning models in SSVEP-based BCI: a survey. Brain Sci. 13(3), 483 (2023)","journal-title":"Brain Sci."},{"issue":"2","key":"4492_CR28","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1109\/TNSRE.2006.875576","volume":"14","author":"W Yijun","year":"2006","unstructured":"Yijun, W., Ruiping, W., Xiaorong, G., Bo, H., Shangkai, G.: A practical VEP-based brain-computer interface. IEEE Trans. Neural Syst. Rehabil. Eng. 14(2), 234\u201340 (2006)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"1","key":"4492_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-021-00478-y","volume":"8","author":"H Soltani","year":"2021","unstructured":"Soltani, H., Einalou, Z., Dadgostar, M., Maghooli, K.: Classification of SSVEP-based BCIs using genetic algorithm. J. Big Data 8(1), 1\u201311 (2021)","journal-title":"J. Big Data"},{"issue":"1","key":"4492_CR30","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.jneumeth.2007.09.024","volume":"168","author":"GR Mueller-Putz","year":"2008","unstructured":"Mueller-Putz, G.R., Eder, E., Wriessnegger, S.C., Pfurtscheller, G.: Comparison of DFT and lock-in amplifier features and search for optimal electrode positions in SSVEP-based BCI. J. Neurosci. Methods 168(1), 174\u201381 (2008)","journal-title":"J. Neurosci. Methods"},{"issue":"4","key":"4492_CR31","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/6\/4\/046002","volume":"6","author":"G Bin","year":"2009","unstructured":"Bin, G., Gao, X., Yan, Z., Hong, B., Gao, S.: An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J. Neural Eng. 6(4), 046002 (2009)","journal-title":"J. Neural Eng."},{"issue":"3","key":"4492_CR32","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab914e","volume":"18","author":"Y Chen","year":"2021","unstructured":"Chen, Y., Yang, C., Chen, X., Wang, Y., Gao, X.: A novel training-free recognition method for SSVEP-based BCIs using dynamic window strategy. J. Neural Eng. 18(3), 036007 (2021)","journal-title":"J. Neural Eng."},{"issue":"4","key":"4492_CR33","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/12\/4\/046008","volume":"12","author":"X Chen","year":"2015","unstructured":"Chen, X., Wang, Y., Gao, S., Jung, T.-P., Gao, X.: Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface. J. Neural Eng. 12(4), 046008 (2015)","journal-title":"J. Neural Eng."},{"issue":"1","key":"4492_CR34","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/TBME.2017.2694818","volume":"65","author":"M Nakanishi","year":"2018","unstructured":"Nakanishi, M., Wang, Y., Chen, X., Wang, Y.-T., Gao, X., Jung, T.-P.: Enhancing detection of SSVEPs for a high-speed brain speller using task-related component analysis. IEEE Trans. Biomed. Eng. 65(1), 104\u201312 (2018)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"1","key":"4492_CR35","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab2373","volume":"17","author":"CM Wong","year":"2020","unstructured":"Wong, C.M., Wan, F., Wang, B., Wang, Z., Nan, W., Lao, K.F., et al.: Learning across multi-stimulus enhances target recognition methods in SSVEP-based BCIs. J. Neural Eng. 17(1), 016026 (2020)","journal-title":"J. Neural Eng."},{"key":"4492_CR36","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.neucom.2014.01.062","volume":"149","author":"JN da Cruz","year":"2015","unstructured":"da Cruz, J.N., Wan, F., Wong, C.M., Cao, T.: Adaptive time-window length based on online performance measurement in SSVEP-based BCIs. Neurocomputing 149, 93\u20139 (2015)","journal-title":"Neurocomputing"},{"issue":"10","key":"4492_CR37","doi-asserted-by":"publisher","first-page":"1850028","DOI":"10.1142\/S0129065718500284","volume":"28","author":"C Yang","year":"2018","unstructured":"Yang, C., Han, X., Wang, Y., Saab, R., Gao, S., Gao, X.: A dynamic window recognition algorithm for SSVEP-based brain-computer interfaces using a spatio-temporal equalizer. Int. J. Neural Syst. 28(10), 1850028 (2018)","journal-title":"Int. J. Neural Syst."},{"key":"4492_CR38","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1109\/TNSRE.2022.3217789","volume":"31","author":"T Lee","year":"2023","unstructured":"Lee, T., Nam, S., Hyun, D.J.: Adaptive window method based on FBCCA for optimal SSVEP recognition. IEEE Trans. Neural Syst. Rehabil. Eng. 31, 78\u201386 (2023)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"10","key":"4492_CR39","doi-asserted-by":"publisher","first-page":"1746","DOI":"10.1109\/TNSRE.2016.2627556","volume":"25","author":"Y Wang","year":"2017","unstructured":"Wang, Y., Chen, X., Gao, X., Gao, S.: A benchmark dataset for SSVEP-based brain-computer interfaces. IEEE Trans. Neural Syst. Rehabil. Eng. 25(10), 1746\u201352 (2017)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"44","key":"4492_CR40","doi-asserted-by":"publisher","first-page":"E6058","DOI":"10.1073\/pnas.1508080112","volume":"112","author":"X Chen","year":"2015","unstructured":"Chen, X., Wang, Y., Nakanishi, M., Gao, X., Jung, T.-P., Gao, S.: High-speed spelling with a noninvasive brain-computer interface. Proc. Natl. Acad. Sci. U.S.A. 112(44), E6058\u2013E67 (2015)","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"issue":"18","key":"4492_CR41","doi-asserted-by":"publisher","first-page":"2975","DOI":"10.1016\/S0042-6989(99)00031-0","volume":"39","author":"F Di Russo","year":"1999","unstructured":"Di Russo, F., Spinelli, D.: Electrophysiological evidence for an early attentional mechanism in visual processing in humans. Vis. Res. 39(18), 2975\u201385 (1999)","journal-title":"Vis. Res."},{"issue":"6","key":"4492_CR42","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1016\/S1388-2457(02)00057-3","volume":"113","author":"JR Wolpaw","year":"2002","unstructured":"Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113(6), 767\u201391 (2002)","journal-title":"Clin. Neurophysiol."},{"key":"4492_CR43","doi-asserted-by":"publisher","first-page":"627","DOI":"10.3389\/fnins.2020.00627","volume":"14","author":"B Liu","year":"2020","unstructured":"Liu, B., Huang, X., Wang, Y., Chen, X., Gao, X.: BETA: a large benchmark database toward SSVEP-BCI application. Front. Neurosci. 14, 627 (2020)","journal-title":"Front. Neurosci."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-04492-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-024-04492-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-04492-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T19:36:48Z","timestamp":1725910608000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-024-04492-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,4]]},"references-count":43,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["4492"],"URL":"https:\/\/doi.org\/10.1007\/s10586-024-04492-6","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,4]]},"assertion":[{"value":"30 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 May 2024","order":4,"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 that they have no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}