{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T14:09:50Z","timestamp":1778854190354,"version":"3.51.4"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2019,7,24]],"date-time":"2019-07-24T00:00:00Z","timestamp":1563926400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,24]],"date-time":"2019-07-24T00:00:00Z","timestamp":1563926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100014538","name":"Lembaga Pengelola Dana Pendidikan","doi-asserted-by":"crossref","award":["PRJ-2173\/LPDP\/2015"],"award-info":[{"award-number":["PRJ-2173\/LPDP\/2015"]}],"id":[{"id":"10.13039\/501100014538","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cogn Process"],"published-print":{"date-parts":[[2019,11]]},"DOI":"10.1007\/s10339-019-00924-z","type":"journal-article","created":{"date-parts":[[2019,7,24]],"date-time":"2019-07-24T07:30:31Z","timestamp":1563953431000},"page":"405-417","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":78,"title":["Improving the accuracy of EEG emotion recognition by combining valence lateralization and ensemble learning with tuning parameters"],"prefix":"10.1007","volume":"20","author":[{"given":"Evi Septiana","family":"Pane","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adhi Dharma","family":"Wibawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mauridhi Hery","family":"Purnomo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,24]]},"reference":[{"key":"924_CR1","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1016\/0028-3932(85)90081-8","volume":"23","author":"GL Ahern","year":"1985","unstructured":"Ahern GL, Schwartz GE (1985) Differential lateralization for positive and negative emotion in the human brain: EEG spectral analysis. Neuropsychologia 23:745\u2013755","journal-title":"Neuropsychologia"},{"key":"924_CR2","doi-asserted-by":"publisher","first-page":"2242","DOI":"10.1016\/S0028-3932(02)00107-0","volume":"40","author":"E Altenm\u00fcller","year":"2002","unstructured":"Altenm\u00fcller E, Sch\u00fcrmann K, Lim VK, Parlitz D (2002) Hits to the left, flops to the right: different emotions during listening to music are reflected in cortical lateralisation patterns. Neuropsychologia 40:2242\u20132256","journal-title":"Neuropsychologia"},{"key":"924_CR3","first-page":"63","volume":"1","author":"NT Alves","year":"2008","unstructured":"Alves NT, Fukusima SS, Aznar-Casanova JA (2008) Models of brain asymmetry in emotional processing. Psychol Neurosci 1:63\u201366","journal-title":"Psychol Neurosci"},{"key":"924_CR4","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.eswa.2015.10.049","volume":"47","author":"J Atkinson","year":"2016","unstructured":"Atkinson J, Campos D (2016) Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers. Expert Syst Appl 47:35\u201341. \nhttps:\/\/doi.org\/10.1016\/j.eswa.2015.10.049","journal-title":"Expert Syst Appl"},{"key":"924_CR5","first-page":"62","volume":"7","author":"LS Berk","year":"2001","unstructured":"Berk LS, Felten DL, Tan SA, Bittman BB, Westengard J (2001) Modulation of neuroimmune parameters during the eustress of humor-associated mirthful laughter. Altern Ther Health Med 7:62\u201376","journal-title":"Altern Ther Health Med"},{"key":"924_CR6","doi-asserted-by":"publisher","first-page":"1580","DOI":"10.1016\/j.patrec.2012.04.003","volume":"33","author":"S Bernard","year":"2012","unstructured":"Bernard S, Adam S, Heutte L (2012) Dynamic random forests. Pattern Recognit Lett 33:1580\u20131586","journal-title":"Pattern Recognit Lett"},{"key":"924_CR7","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.chb.2016.08.029","volume":"65","author":"AM Bhatti","year":"2016","unstructured":"Bhatti AM, Majid M, Anwar SM, Khan B (2016) Human emotion recognition and analysis in response to audio music using brain signals. Comput Hum Behav 65:267\u2013275. \nhttps:\/\/doi.org\/10.1016\/j.chb.2016.08.029","journal-title":"Comput Hum Behav"},{"key":"924_CR8","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1016\/0028-3932(88)90013-9","volume":"26","author":"JC Borod","year":"1988","unstructured":"Borod JC, Kent J, Koff E, Martin C, Alpert M (1988) Facial asymmetry while posing positive and negative emotions: support for the right hemisphere hypothesis. Neuropsychologia 26:759\u2013764. \nhttps:\/\/doi.org\/10.1016\/0028-3932(88)90013-9","journal-title":"Neuropsychologia"},{"key":"924_CR9","first-page":"1","volume":"56","author":"DO Bos","year":"2006","unstructured":"Bos DO (2006) EEG-based emotion recognition. Influ Vis Audit Stimul 56:1\u201317","journal-title":"Influ Vis Audit Stimul"},{"key":"924_CR10","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/0005-7916(94)90063-9","volume":"25","author":"MM Bradley","year":"1994","unstructured":"Bradley MM, Lang PJ (1994) Measuring emotion: the self-assessment manikin and the semantic differential. J Behav Ther Exp Psychiatry 25:49\u201359","journal-title":"J Behav Ther Exp Psychiatry"},{"key":"924_CR11","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45:5\u201332","journal-title":"Mach Learn"},{"key":"924_CR12","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/S0167-8760(03)00146-6","volume":"50","author":"JF Brosschot","year":"2003","unstructured":"Brosschot JF, Thayer JF (2003) Heart rate response is longer after negative emotions than after positive emotions. Int J Psychophysiol 50:181\u2013187. \nhttps:\/\/doi.org\/10.1016\/S0167-8760(03)00146-6","journal-title":"Int J Psychophysiol"},{"key":"924_CR13","doi-asserted-by":"crossref","unstructured":"Candra H, Yuwono M, Chai R, Handojoseno A, Elamvazuthi I, Nguyen HT, Su S (2015) Investigation of window size in classification of EEG-emotion signal with wavelet entropy and support vector machine. In: 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 7250\u20137253","DOI":"10.1109\/EMBC.2015.7320065"},{"key":"924_CR14","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1007\/s12559-016-9383-y","volume":"8","author":"JC Castillo","year":"2016","unstructured":"Castillo JC, Castro-Gonz\u00e1lez \u00c1, Fern\u00e1ndez-Caballero A, Latorre JM, Pastor JM, Fern\u00e1ndez-Sotos A, Salichs MA (2016) Software architecture for smart emotion recognition and regulation of the ageing adult. Cogn Comput 8:357\u2013367. \nhttps:\/\/doi.org\/10.1007\/s12559-016-9383-y","journal-title":"Cogn Comput"},{"key":"924_CR15","first-page":"202","volume":"16","author":"RJ Davidson","year":"1979","unstructured":"Davidson RJ, Schwartz GE, Saron C, Bennett J, Goleman DJ (1979) Frontal vs. parietal EEG asymmetry during positive and negative affect. Pyscophysiology 16:202\u2013203","journal-title":"Pyscophysiology"},{"key":"924_CR16","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1177\/1534582305276837","volume":"4","author":"HA Demaree","year":"2005","unstructured":"Demaree HA, Everhart DE, Youngstrom EA, Harrison DW (2005) Brain lateralization of emotional processing: historical roots and a future incorporating \u201cDominance\u201d. Behav Cogn Neurosci Rev 4:3\u201320. \nhttps:\/\/doi.org\/10.1177\/1534582305276837","journal-title":"Behav Cogn Neurosci Rev"},{"key":"924_CR17","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1109\/TNSRE.2016.2552539","volume":"24","author":"M Diykh","year":"2016","unstructured":"Diykh M, Li Y, Wen P (2016) EEG sleep stages classification based on time domain features and structural graph similarity. IEEE Trans Neural Syst Rehabil Eng 24:1159\u20131168. \nhttps:\/\/doi.org\/10.1109\/TNSRE.2016.2552539","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"924_CR18","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/0167-2789(88)90081-4","volume":"31","author":"T Higuchi","year":"1988","unstructured":"Higuchi T (1988) Approach to an irregular time series on the basis of the fractal theory. Physica D 31:277\u2013283","journal-title":"Physica D"},{"key":"924_CR19","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1016\/0013-4694(70)90143-4","volume":"29","author":"B Hjorth","year":"1970","unstructured":"Hjorth B (1970) EEG analysis based on time domain properties. Electroencephalogr Clin Neurophysiol 29:306\u2013310","journal-title":"Electroencephalogr Clin Neurophysiol"},{"key":"924_CR20","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1080\/17470919.2012.691078","volume":"7","author":"A Ibanez","year":"2012","unstructured":"Ibanez A, Melloni M, Huepe D, Helgiu E, Rivera-Rei A, Canales-Johnson A, Baker P, Moya A (2012) What event-related potentials (ERPs) bring to social neuroscience? Soc Neurosci 7:632\u2013649. \nhttps:\/\/doi.org\/10.1080\/17470919.2012.691078","journal-title":"Soc Neurosci"},{"key":"924_CR21","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1109\/TAFFC.2014.2339834","volume":"5","author":"R Jenke","year":"2014","unstructured":"Jenke R, Peer A, Buss M (2014) Feature extraction and selection for emotion recognition from EEG. IEEE Trans Affect Comput 5:327\u2013339. \nhttps:\/\/doi.org\/10.1109\/TAFFC.2014.2339834","journal-title":"IEEE Trans Affect Comput"},{"key":"924_CR22","doi-asserted-by":"crossref","unstructured":"Kaiser JF (1990) On a simple algorithm to calculate the \u2018energy\u2019 of a signal. In: 1990 international conference on acoustics, speech, and signal processing, 1990. ICASSP-90. IEEE, pp 381\u2013384","DOI":"10.1109\/ICASSP.1990.115702"},{"key":"924_CR23","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","volume":"3","author":"S Koelstra","year":"2012","unstructured":"Koelstra S, Muhl C, Soleymani M, Lee J-S, Yazdani A, Ebrahimi T, Pun T, Nijholt A, Patras I (2012) DEAP: a database for emotion analysis; using physiological signals. IEEE Trans Affect Comput 3:18\u201331","journal-title":"IEEE Trans Affect Comput"},{"key":"924_CR24","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/S0022-3999(97)00292-4","volume":"45","author":"KB Koh","year":"1998","unstructured":"Koh KB (1998) Emotion and immunity. J Psychosom Res 45:107\u2013115","journal-title":"J Psychosom Res"},{"key":"924_CR25","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/S0933-3657(01)00077-X","volume":"23","author":"I Kononenko","year":"2001","unstructured":"Kononenko I (2001) Machine learning for medical diagnosis: history, state of the art and perspective. Artif Intell Med 23:89\u2013109","journal-title":"Artif Intell Med"},{"key":"924_CR26","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1007\/s12559-017-9533-x","volume":"10","author":"J Li","year":"2017","unstructured":"Li J, Zhang Z, He H (2017) Hierarchical convolutional neural networks for EEG-based emotion recognition. Cogn Comput 10:368\u2013380. \nhttps:\/\/doi.org\/10.1007\/s12559-017-9533-x","journal-title":"Cogn Comput"},{"key":"924_CR27","doi-asserted-by":"publisher","first-page":"1798","DOI":"10.1109\/TBME.2010.2048568","volume":"57","author":"Y-P Lin","year":"2010","unstructured":"Lin Y-P, Wang C-H, Jung T-P, Wu T-L, Jeng S-K, Duann J-R, Chen J-H (2010) EEG-based emotion recognition in music listening. IEEE Trans Biomed Eng 57:1798\u20131806. \nhttps:\/\/doi.org\/10.1109\/TBME.2010.2048568","journal-title":"IEEE Trans Biomed Eng"},{"key":"924_CR28","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1007\/978-3-642-22336-5_13","volume-title":"Transactions on computational science XII","author":"Y Liu","year":"2011","unstructured":"Liu Y, Sourina O, Nguyen MK (2011) Real-time EEG-based emotion recognition and its applications. In: Gavrilova ML, Tan CJK, Sourin A, Sourina O (eds) Transactions on computational science XII. Springer, Berlin, Heidelberg, pp 256\u2013277"},{"key":"924_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-2149-8","author":"Z Mohammadi","year":"2016","unstructured":"Mohammadi Z, Frounchi J, Amiri M (2016) Wavelet-based emotion recognition system using EEG signal. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-015-2149-8","journal-title":"Neural Comput Appl"},{"key":"924_CR30","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.biopsycho.2007.11.006","volume":"77","author":"JK Olofsson","year":"2008","unstructured":"Olofsson JK, Nordin S, Sequeira H, Polich J (2008) Affective picture processing: an integrative review of ERP findings. Biol Psychol 77:247\u2013265. \nhttps:\/\/doi.org\/10.1016\/j.biopsycho.2007.11.006","journal-title":"Biol Psychol"},{"key":"924_CR31","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/s40708-017-0069-3","volume":"4","author":"MS \u00d6zerdem","year":"2017","unstructured":"\u00d6zerdem MS, Polat H (2017) Emotion recognition based on EEG features in movie clips with channel selection. Brain Informatics 4:241\u2013252. \nhttps:\/\/doi.org\/10.1007\/s40708-017-0069-3","journal-title":"Brain Informatics"},{"key":"924_CR32","doi-asserted-by":"publisher","unstructured":"Pane ES, Hendrawan MA, Wibawa AD, Purnomo MH (2017) Identifying rules for electroencephalograph (EEG) emotion recognition and classification. In: 2017 5th international conference on instrumentation, communications, information technology, and biomedical engineering (ICICI-BME). IEEE, pp 167\u2013172. \nhttps:\/\/doi.org\/10.1109\/ICICI-BME.2017.8537731","DOI":"10.1109\/ICICI-BME.2017.8537731"},{"key":"924_CR33","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1109\/TITB.2009.2034649","volume":"14","author":"PC Petrantonakis","year":"2010","unstructured":"Petrantonakis PC, Hadjileontiadis LJ (2010) Emotion recognition from EEG using higher order crossings. IEEE Trans Inf Technol Biomed 14:186\u2013197. \nhttps:\/\/doi.org\/10.1109\/TITB.2009.2034649","journal-title":"IEEE Trans Inf Technol Biomed"},{"key":"924_CR34","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1007\/s12559-015-9367-3","volume":"8","author":"P Pires","year":"2015","unstructured":"Pires P, Mendes L, Mendes J, Rodrigues R, Pereira A (2015) Integrated e-healthcare system for elderly support. Cogn Comput 8:368\u2013384. \nhttps:\/\/doi.org\/10.1007\/s12559-015-9367-3","journal-title":"Cogn Comput"},{"key":"924_CR35","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1037\/0033-2909.131.6.925","volume":"131","author":"SD Pressman","year":"2005","unstructured":"Pressman SD, Cohen S (2005) Does positive affect influence health? Psychol Bull 131:925\u2013971. \nhttps:\/\/doi.org\/10.1037\/0033-2909.131.6.925","journal-title":"Psychol Bull"},{"key":"924_CR36","volume-title":"Neuroscience","year":"2004","unstructured":"Purves D (ed) (2004) Neuroscience, 3rd edn. Sinauer Associates, Publishers, Sunderland","edition":"3"},{"key":"924_CR37","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/978-1-4419-9326-7_11","volume-title":"Ensemble machine learning","author":"Y Qi","year":"2012","unstructured":"Qi Y (2012) Random forest for bioinformatics. In: Zhang C, Ma Y (eds) Ensemble machine learning. Springer, Boston, MA, pp 307\u2013323"},{"key":"924_CR39","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1080\/0269993004200187","volume":"15","author":"LA Schmidt","year":"2001","unstructured":"Schmidt LA, Trainor LJ (2001) Frontal brain electrical activity (EEG) distinguishes valence and intensity of musical emotions. Cogn Emot 15:487\u2013500. \nhttps:\/\/doi.org\/10.1080\/0269993004200187","journal-title":"Cogn Emot"},{"key":"924_CR40","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1126\/science.1179210","volume":"190","author":"GE Schwartz","year":"1975","unstructured":"Schwartz GE, Davidson RJ, Maer F (1975) Right hemisphere lateralization for emotion in the human brain: interactions with cognition. Science 190:286\u2013288","journal-title":"Science"},{"key":"924_CR41","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/S1053-8119(03)00078-8","volume":"19","author":"TD Wager","year":"2003","unstructured":"Wager TD, Phan KL, Liberzon I, Taylor SF (2003) Valence, gender, and lateralization of functional brain anatomy in emotion: a meta-analysis of findings from neuroimaging. NeuroImage 19:513\u2013531. \nhttps:\/\/doi.org\/10.1016\/S1053-8119(03)00078-8","journal-title":"NeuroImage"},{"key":"924_CR42","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.neucom.2013.06.046","volume":"129","author":"X-W Wang","year":"2014","unstructured":"Wang X-W, Nie D, Lu B-L (2014) Emotional state classification from EEG data using machine learning approach. Neurocomputing 129:94\u2013106. \nhttps:\/\/doi.org\/10.1016\/j.neucom.2013.06.046","journal-title":"Neurocomputing"},{"key":"924_CR38","unstructured":"Wibawa AD, Purnomo MH, Marzuki A, Rumpa LD (2016) Physiological pattern of human state emotion based on ECG and pulse sensor. J Theor Appl Inf Technol 93(1)"},{"key":"924_CR43","doi-asserted-by":"publisher","first-page":"1558","DOI":"10.3390\/s16101558","volume":"16","author":"J Zhang","year":"2016","unstructured":"Zhang J, Chen M, Zhao S, Hu S, Shi Z, Cao Y (2016a) ReliefF-based EEG sensor selection methods for emotion recognition. Sensors 16:1558. \nhttps:\/\/doi.org\/10.3390\/s16101558","journal-title":"Sensors"},{"key":"924_CR44","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.neulet.2016.09.037","volume":"633","author":"Y Zhang","year":"2016","unstructured":"Zhang Y, Ji X, Zhang S (2016b) An approach to EEG-based emotion recognition using combined feature extraction method. Neurosci Lett 633:152\u2013157. \nhttps:\/\/doi.org\/10.1016\/j.neulet.2016.09.037","journal-title":"Neurosci Lett"},{"key":"924_CR45","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1109\/TCDS.2016.2587290","volume":"9","author":"W Zheng","year":"2017","unstructured":"Zheng W (2017) Multichannel EEG-based emotion recognition via group sparse canonical correlation analysis. IEEE Trans Cogn Dev Syst 9:281\u2013290. \nhttps:\/\/doi.org\/10.1109\/TCDS.2016.2587290","journal-title":"IEEE Trans Cogn Dev Syst"},{"key":"924_CR46","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1109\/TAMD.2015.2431497","volume":"7","author":"W-L Zheng","year":"2015","unstructured":"Zheng W-L, Lu B-L (2015) Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks. IEEE Trans Auton Ment Dev 7:162\u2013175. \nhttps:\/\/doi.org\/10.1109\/TAMD.2015.2431497","journal-title":"IEEE Trans Auton Ment Dev"}],"container-title":["Cognitive Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10339-019-00924-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10339-019-00924-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10339-019-00924-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,7,22]],"date-time":"2020-07-22T23:08:46Z","timestamp":1595459326000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10339-019-00924-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,24]]},"references-count":46,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,11]]}},"alternative-id":["924"],"URL":"https:\/\/doi.org\/10.1007\/s10339-019-00924-z","relation":{},"ISSN":["1612-4782","1612-4790"],"issn-type":[{"value":"1612-4782","type":"print"},{"value":"1612-4790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,24]]},"assertion":[{"value":"8 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants performed by any of the authors. The data being used in this article is the public dataset which can be accessed online and also cited as one of the references.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was obtained from all individual participants included in the study performed by the dataset creator, not the author of these articles.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}