{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T22:37:07Z","timestamp":1781044627456,"version":"3.54.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100019004","name":"Deanship of Research, Jordan University of Science and Technology","doi-asserted-by":"publisher","award":["20220146"],"award-info":[{"award-number":["20220146"]}],"id":[{"id":"10.13039\/501100019004","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s10586-022-03802-0","type":"journal-article","created":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T17:02:45Z","timestamp":1668013365000},"page":"3985-3995","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Detection of K-complexes in EEG signals using deep transfer learning and YOLOv3"],"prefix":"10.1007","volume":"26","author":[{"given":"Natheer","family":"Khasawneh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Fraiwan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luay","family":"Fraiwan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,9]]},"reference":[{"key":"3802_CR1","doi-asserted-by":"publisher","unstructured":"Cho, S.P., Lee, J., Park, H.D., Lee, K.J.: Detection of arousals in patients with respiratory sleep disorders using a single channel EEG. In: 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, Shanghai (2005). https:\/\/doi.org\/10.1109\/iembs.2005.1617036","DOI":"10.1109\/iembs.2005.1617036"},{"issue":"4","key":"3802_CR2","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1016\/0013-4694(75)90269-2","volume":"38","author":"JR Smith","year":"1975","unstructured":"Smith, J.R., Funke, W.F., Yeo, W.C., Ambuehl, R.A.: Detection of human sleep EEG waveforms. Electroencephalogr. Clin. Neurophysiol. 38(4), 435\u2013437 (1975). https:\/\/doi.org\/10.1016\/0013-4694(75)90269-2","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"issue":"4","key":"3802_CR3","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1016\/j.clinph.2007.12.016","volume":"119","author":"F Saccomandi","year":"2008","unstructured":"Saccomandi, F., Priano, L., Mauro, A., Nerino, R., Guiot, C.: Automatic detection of transient EEG events during sleep can be improved using a multi-channel approach. Clin. Neurophysiol. 119(4), 959\u2013967 (2008). https:\/\/doi.org\/10.1016\/j.clinph.2007.12.016","journal-title":"Clin. Neurophysiol."},{"issue":"9","key":"3802_CR4","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1109\/tnsre.2019.2934828","volume":"27","author":"S Hartmann","year":"2019","unstructured":"Hartmann, S., Baumert, M.: Automatic a-phase detection of cyclic alternating patterns in sleep using dynamic temporal information. IEEE Trans. Neural Syst. Rehabil. Eng. 27(9), 1695\u20131703 (2019). https:\/\/doi.org\/10.1109\/tnsre.2019.2934828","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"8","key":"3802_CR5","doi-asserted-by":"publisher","first-page":"1380","DOI":"10.3390\/diagnostics11081380","volume":"11","author":"M Sharma","year":"2021","unstructured":"Sharma, M., Patel, V., Tiwari, J., Acharya, U.R.: Automated characterization of cyclic alternating pattern using wavelet-based features and ensemble learning techniques with EEG signals. Diagnostics 11(8), 1380 (2021). https:\/\/doi.org\/10.3390\/diagnostics11081380","journal-title":"Diagnostics"},{"key":"3802_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2021.109353","volume":"363","author":"D Wen","year":"2021","unstructured":"Wen, D., Cheng, Z., Li, J., Zheng, X., Yao, W., Dong, X., Saripan, M.I., Li, X., Yin, S., Zhou, Y.: Classification of ERP signal from amnestic mild cognitive impairment with type 2 diabetes mellitus using single-scale multi-input convolution neural network. J. Neurosci. Methods 363, 109353 (2021). https:\/\/doi.org\/10.1016\/j.jneumeth.2021.109353","journal-title":"J. Neurosci. Methods"},{"issue":"8","key":"3802_CR7","doi-asserted-by":"publisher","first-page":"1176","DOI":"10.1016\/j.clinph.2009.12.039","volume":"121","author":"R Wennberg","year":"2010","unstructured":"Wennberg, R.: Intracranial cortical localization of the human k-complex. Clin. Neurophysiol. 121(8), 1176\u20131186 (2010). https:\/\/doi.org\/10.1016\/j.clinph.2009.12.039","journal-title":"Clin. Neurophysiol."},{"key":"3802_CR8","unstructured":"Gandhi, M.H., Emmady, P.D.: Physiology, k complex. StatPearls [Internet] (2021). Last accessed 15 March 2022"},{"issue":"4","key":"3802_CR9","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1109\/tbme.1970.4502759","volume":"17","author":"G Bremer","year":"1970","unstructured":"Bremer, G., Smith, J.R., Karacan, I.: Automatic detection of the k-complex in sleep electroencephalograms. IEEE Trans. Biomed. Eng. BME 17(4), 314\u2013323 (1970). https:\/\/doi.org\/10.1109\/tbme.1970.4502759","journal-title":"IEEE Trans. Biomed. Eng. BME"},{"issue":"21","key":"3802_CR10","doi-asserted-by":"publisher","first-page":"7230","DOI":"10.3390\/s21217230","volume":"21","author":"C Dumitrescu","year":"2021","unstructured":"Dumitrescu, C., Costea, I.-M., Cormos, A.-C., Semenescu, A.: Automatic detection of k-complexes using the cohen class recursiveness and reallocation method and deep neural networks with EEG signals. Sensors 21(21), 7230 (2021). https:\/\/doi.org\/10.3390\/s21217230","journal-title":"Sensors"},{"key":"3802_CR11","doi-asserted-by":"publisher","first-page":"45","DOI":"10.3389\/fninf.2019.00045","volume":"13","author":"W Al-Salman","year":"2019","unstructured":"Al-Salman, W., Li, Y., Wen, P.: Detection of EEG k-complexes using fractal dimension of time frequency images technique coupled with undirected graph features. Front. Neuroinform. 13, 45 (2019). https:\/\/doi.org\/10.3389\/fninf.2019.00045","journal-title":"Front. Neuroinform."},{"key":"3802_CR12","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.neuroscience.2019.10.034","volume":"422","author":"W AL-Salman","year":"2019","unstructured":"AL-Salman, W., Li, Y., Wen, P.: K-complexes detection in EEG signals using fractal and frequency features coupled with an ensemble classification model. Neuroscience 422, 119\u2013133 (2019). https:\/\/doi.org\/10.1016\/j.neuroscience.2019.10.034","journal-title":"Neuroscience"},{"key":"3802_CR13","doi-asserted-by":"publisher","unstructured":"Kantar, T., Erdamar, A.: Detection of k-complexes in sleep EEG with support vector machines. In: 2017 25th Signal Processing and Communications Applications Conference (SIU), pp. 1\u20134 (2017). https:\/\/doi.org\/10.1109\/SIU.2017.7960311","DOI":"10.1109\/SIU.2017.7960311"},{"issue":"8","key":"3802_CR14","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s00521-017-2865-3","volume":"29","author":"C Y\u00fccelba\u015f","year":"2017","unstructured":"Y\u00fccelba\u015f, C., Y\u00fccelba\u015f, \u015e, \u00d6z\u015fen, S., Tezel, G., K\u00fc\u00e7\u00e7\u00fckt\u00fcrk, S., Yosunkaya, \u015e: A novel system for automatic detection of k-complexes in sleep EEG. Neural Comput. Appl. 29(8), 137\u2013157 (2017). https:\/\/doi.org\/10.1007\/s00521-017-2865-3","journal-title":"Neural Comput. Appl."},{"key":"3802_CR15","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2017.00015","author":"T Lajnef","year":"2016","unstructured":"Lajnef, T.: Meet spinky: an open-source spindle and k-complex detection toolbox validated on the open-access montreal archive of sleep studies (MASS). Front. Neuroinform. (2016). https:\/\/doi.org\/10.3389\/fninf.2017.00015","journal-title":"Front. Neuroinform."},{"key":"3802_CR16","doi-asserted-by":"publisher","unstructured":"Patti, C.R., Abdullah, H., Shoji, Y., Hayley, A., Schilling, C., Schredl, M., Cvetkovic, D.: K-complex detection based on pattern matched wavelets. In: 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES). IEEE, Kuala Lumpur (2016). https:\/\/doi.org\/10.1109\/iecbes.2016.7843495","DOI":"10.1109\/iecbes.2016.7843495"},{"key":"3802_CR17","doi-asserted-by":"publisher","first-page":"414","DOI":"10.3389\/fnhum.2015.00414","volume":"9","author":"T Lajnef","year":"2015","unstructured":"Lajnef, T., Chaibi, S., Eichenlaub, J.B., Ruby, P.M., Aguera, P.E., Samet, M., Kachouri, A., Jerbi, K.: Sleep spindle and k-complex detection using tunable q-factor wavelet transform and morphological component analysis. Front Hum Neurosci 9, 414 (2015). https:\/\/doi.org\/10.3389\/fnhum.2015.00414","journal-title":"Front Hum Neurosci"},{"key":"3802_CR18","doi-asserted-by":"publisher","unstructured":"Krohne, L.K., Hansen, R.B., Christensen, J.A.E., Sorensen, H.B.D., Jennum, P.: Detection of k-complexes based on the wavelet transform. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, Chicago (2014). https:\/\/doi.org\/10.1109\/embc.2014.6944859","DOI":"10.1109\/embc.2014.6944859"},{"key":"3802_CR19","doi-asserted-by":"publisher","first-page":"384","DOI":"10.21914\/anziamj.v55i0.7802","volume":"55","author":"ZR Zamir","year":"2014","unstructured":"Zamir, Z.R., Sukhorukova, N., Amiel, H., Ugon, A., Philippe, C.: Optimization-based features extraction for k-complex detection. ANZIAM J 55, 384 (2014). https:\/\/doi.org\/10.21914\/anziamj.v55i0.7802","journal-title":"ANZIAM J"},{"key":"3802_CR20","doi-asserted-by":"publisher","unstructured":"Zacharaki, E.I., Pippa, E., Koupparis, A., Kokkinos, V., Kostopoulos, G.K., Megalooikonomou, V.: One-class classification of temporal EEG patterns for k-complex extraction. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Osaka (2013). https:\/\/doi.org\/10.1109\/embc.2013.6610870","DOI":"10.1109\/embc.2013.6610870"},{"key":"3802_CR21","first-page":"1","volume":"4","author":"VV Shete","year":"2012","unstructured":"Shete, V.V., Sonar, S., Charantimatp, A., Elgendelwar, S.: Detection of k-complex in sleep EEG signal with matched filter and neural network. Int. J. Eng. Res. Technol. 4, 1\u20134 (2012)","journal-title":"Int. J. Eng. Res. Technol."},{"key":"3802_CR22","doi-asserted-by":"publisher","unstructured":"Devuyst, S., Dutoit, T., Stenuit, P., Kerkhofs, M.: Automatic k-complexes detection in sleep EEG recordings using likelihood thresholds. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE, Buenos Aires (2010). https:\/\/doi.org\/10.1109\/iembs.2010.5626447","DOI":"10.1109\/iembs.2010.5626447"},{"issue":"s3","key":"3802_CR23","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1515\/bmte.1998.43.s3.113","volume":"43","author":"C Strungaru","year":"1998","unstructured":"Strungaru, C., Popescu, M.S.: Neural network for sleep EEG k-complex detection. Biomed. Tech. 43(s3), 113\u2013116 (1998). https:\/\/doi.org\/10.1515\/bmte.1998.43.s3.113","journal-title":"Biomed. Tech."},{"key":"3802_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2022.100514","volume":"19","author":"SS Gill","year":"2022","unstructured":"...Gill, S.S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., Abraham, A., Singh, M., Mehta, H., Ghosh, S.K., Baker, T., Parlikad, A.K., Lutfiyya, H., Kanhere, S.S., Sakellariou, R., Dustdar, S., Rana, O., Brandic, I., Uhlig, S.: AI for next generation computing: emerging trends and future directions. Internet Things 19, 100514 (2022). https:\/\/doi.org\/10.1016\/j.iot.2022.100514","journal-title":"Internet Things"},{"key":"3802_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-022-03707-y","author":"Z Yu","year":"2022","unstructured":"Yu, Z., Wang, K., Wan, Z., Xie, S., Lv, Z.: Popular deep learning algorithms for disease prediction: a review. Clust. Comput. (2022). https:\/\/doi.org\/10.1007\/s10586-022-03707-y","journal-title":"Clust. Comput."},{"issue":"S6","key":"3802_CR26","doi-asserted-by":"publisher","first-page":"13521","DOI":"10.1007\/s10586-018-1995-4","volume":"22","author":"MR Kumar","year":"2018","unstructured":"Kumar, M.R., Rao, Y.S.: Epileptic seizures classification in EEG signal based on semantic features and variational mode decomposition. Clust. Comput. 22(S6), 13521\u201313531 (2018). https:\/\/doi.org\/10.1007\/s10586-018-1995-4","journal-title":"Clust. Comput."},{"key":"3802_CR27","doi-asserted-by":"publisher","unstructured":"Devuyst, S.: The DREAMS Databases and Assessment Algorithm. Zenodo (2005) https:\/\/doi.org\/10.5281\/ZENODO.2650142. zenodo.org\/record\/2650142","DOI":"10.5281\/ZENODO.2650142."},{"key":"3802_CR28","unstructured":"Redmon, J., Farhadi, A.: YOLOv3: An Incremental Improvement (2018). http:\/\/arxiv.org\/abs\/1804.02767"},{"key":"3802_CR29","doi-asserted-by":"publisher","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2009). https:\/\/doi.org\/10.1109\/CVPR.2009.5206848","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"3802_CR30","unstructured":"Redmon, J.: Darknet: Open Source Neural Networks in C (2013\u20132016). http:\/\/pjreddie.com\/darknet\/"},{"key":"3802_CR31","doi-asserted-by":"publisher","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.-C.: Mobilenetv2: Inverted residuals and linear bottlenecks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00474","DOI":"10.1109\/CVPR.2018.00474"},{"key":"3802_CR32","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"3802_CR33","unstructured":"Iandola, F.N., Moskewicz, M.W., Ashraf, K., Han, S., Dally, W.J., Keutzer, K.: Squeezenet: Alexnet-level accuracy with 50x fewer parameters and<1mb model size. arXiv (2016)"},{"key":"3802_CR34","doi-asserted-by":"publisher","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C.L., Doll\u00e1r, P.: Microsoft COCO: Common Objects in Context. arXiv (2014). https:\/\/doi.org\/10.48550\/ARXIV.1405.0312. https:\/\/arxiv.org\/abs\/1405.0312","DOI":"10.48550\/ARXIV.1405.0312"},{"issue":"6","key":"3802_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-021-00815-1","volume":"2","author":"IH Sarker","year":"2021","unstructured":"Sarker, I.H.: Deep learning: a comprehensive overview on techniques, taxonomy, applications and research directions. SN Comput. Sci. 2(6), 1\u201320 (2021). https:\/\/doi.org\/10.1007\/s42979-021-00815-1","journal-title":"SN Comput. Sci."},{"key":"3802_CR36","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.neures.2021.03.012","volume":"172","author":"W Al-Salman","year":"2021","unstructured":"Al-Salman, W., Li, Y., Wen, P.: Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier. Neurosci. Res. 172, 26\u201340 (2021). https:\/\/doi.org\/10.1016\/j.neures.2021.03.012","journal-title":"Neurosci. Res."},{"key":"3802_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113331","volume":"151","author":"GHBS Oliveira","year":"2020","unstructured":"Oliveira, G.H.B.S., Coutinho, L.R., da Silva, J.C., Pinto, I.J.P., Ferreira, J.M.S., Silva, F.J.S., Santos, D.V., Teles, A.S.: Multitaper-based method for automatic k-complex detection in human sleep EEG. Expert Syst. Appl. 151, 113331 (2020). https:\/\/doi.org\/10.1016\/j.eswa.2020.113331","journal-title":"Expert Syst. Appl."},{"key":"3802_CR38","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.patrec.2018.01.001","volume":"115","author":"R Ranjan","year":"2018","unstructured":"Ranjan, R., Arya, R., Fernandes, S.L., Sravya, E., Jain, V.: A fuzzy neural network approach for automatic k-complex detection in sleep EEG signal. Pattern Recognit. Lett. 115, 74\u201383 (2018). https:\/\/doi.org\/10.1016\/j.patrec.2018.01.001","journal-title":"Pattern Recognit. Lett."},{"issue":"2","key":"3802_CR39","doi-asserted-by":"publisher","first-page":"214","DOI":"10.22060\/eej.2017.12577.5096","volume":"49","author":"Z Ghanbari","year":"2017","unstructured":"Ghanbari, Z., Moradi, M.: K-complex detection based on synchrosqueezing transform. AUT J. Electr. Eng. 49(2), 214\u2013222 (2017). https:\/\/doi.org\/10.22060\/eej.2017.12577.5096","journal-title":"AUT J. Electr. Eng."},{"key":"3802_CR40","doi-asserted-by":"publisher","unstructured":"Patti, C.R., Abdullah, H., Shoji, Y., Hayley, A., Schilling, C., Schredl, M., Cvetkovic, D.: K-complex detection based on pattern matched wavelets. In: 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), pp. 470\u2013474 (2016). https:\/\/doi.org\/10.1109\/IECBES.2016.7843495","DOI":"10.1109\/IECBES.2016.7843495"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-022-03802-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-022-03802-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-022-03802-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,16]],"date-time":"2023-10-16T20:12:21Z","timestamp":1697487141000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-022-03802-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,9]]},"references-count":40,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["3802"],"URL":"https:\/\/doi.org\/10.1007\/s10586-022-03802-0","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,9]]},"assertion":[{"value":"4 August 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 October 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 October 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 November 2022","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 competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical statement"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}