{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T11:13:44Z","timestamp":1777634024170,"version":"3.51.4"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2018,8,30]],"date-time":"2018-08-30T00:00:00Z","timestamp":1535587200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,8,30]],"date-time":"2018-08-30T00:00:00Z","timestamp":1535587200000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1007\/s00521-018-3689-5","type":"journal-article","created":{"date-parts":[[2018,8,30]],"date-time":"2018-08-30T05:14:24Z","timestamp":1535606064000},"page":"10927-10933","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":463,"title":["A deep learning approach for Parkinson\u2019s disease diagnosis from EEG signals"],"prefix":"10.1007","volume":"32","author":[{"given":"Shu Lih","family":"Oh","sequence":"first","affiliation":[]},{"given":"Yuki","family":"Hagiwara","sequence":"additional","affiliation":[]},{"given":"U.","family":"Raghavendra","sequence":"additional","affiliation":[]},{"given":"Rajamanickam","family":"Yuvaraj","sequence":"additional","affiliation":[]},{"given":"N.","family":"Arunkumar","sequence":"additional","affiliation":[]},{"given":"M.","family":"Murugappan","sequence":"additional","affiliation":[]},{"given":"U. Rajendra","family":"Acharya","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,8,30]]},"reference":[{"issue":"4","key":"3689_CR1","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1007\/s11065-010-9148-4","volume":"20","author":"J Stiles","year":"2010","unstructured":"Stiles J, Jernigan TL (2010) The basics of brain development. Neuropsychol Rev 20(4):327\u2013348","journal-title":"Neuropsychol Rev"},{"issue":"3","key":"3689_CR2","doi-asserted-by":"publisher","first-page":"a020602","DOI":"10.1101\/cshperspect.a020602","volume":"7","author":"J Silver","year":"2015","unstructured":"Silver J, Schwab ME, Popovich PG (2015) Central nervous system regenerative failure: role of oligodendrocytes, astrocytes, and microglia. Cold Spring Harb Perspect Biol 7(3):a020602","journal-title":"Cold Spring Harb Perspect Biol"},{"key":"3689_CR3","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/S0079-6123(10)83004-3","volume":"183","author":"DJ Surmeier","year":"2010","unstructured":"Surmeier DJ, Guzman JN, Sanchez-Padilla J, Goldberg JA (2010) What causes the death of dopaminergic neurons in Parkinson\u2019s disease? Prog Brain Res 183:59\u201377","journal-title":"Prog Brain Res"},{"key":"3689_CR4","unstructured":"Heyn SN, Davis CP, Stoppler MC (2018) Parkinson\u2019s disease symptoms, signs, causes, stages, and treatment. Retrieved from Medicine Net. https:\/\/www.medicinenet.com\/parkinsons_disease\/article.htm#parkinsons_definition_and_disease_facts. Accessed 11 June 2018"},{"key":"3689_CR5","unstructured":"World Health Organization, Neurological Disorders Public Health Challenges (2006). http:\/\/www.who.int\/mental_health\/neurology\/neurological_disorders_report_web.pdf. Accessed 11 June 2018"},{"key":"3689_CR6","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1007\/s11571-013-9247-z","volume":"7","author":"CX Han","year":"2013","unstructured":"Han CX, Wang J, Yi GS, Che YQ (2013) Investigation of EEG abnormalities in the early stage of Parkinson\u2019s disease. Cogn Neurodyn 7:351\u2013359","journal-title":"Cogn Neurodyn"},{"key":"3689_CR7","first-page":"12","volume":"28","author":"R Yuvaraj","year":"2016","unstructured":"Yuvaraj R, Acharya UR, Hagiwara Y (2016) A novel Parkinson\u2019s diagnosis index using higher-order spectra features in EEG signals. Neural Comput Appl 28:12","journal-title":"Neural Comput Appl"},{"issue":"6","key":"3689_CR8","doi-asserted-by":"publisher","first-page":"10054","DOI":"10.1016\/j.eswa.2009.01.022","volume":"36","author":"CAM Lima","year":"2009","unstructured":"Lima CAM, Coelho ALV, Chagas S (2009) Automatic EEG signal classification for epilepsy diagnosis with relevance vector machines. Expert Syst Appl 36(6):10054\u201310059","journal-title":"Expert Syst Appl"},{"issue":"2","key":"3689_CR9","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.psychres.2009.04.004","volume":"169","author":"AF Leuchter","year":"2009","unstructured":"Leuchter AF, Cook IA, Gilmer WS, Marangell LB, Burgoyne KS, Howland RH, Trivedi MH, Zisook S, Jain R, Fava M, Iosifescu D, Greenwald S (2009) Effectiveness of a quantitative electroencephalographic biomarker for predicting differential response or remission with escitalopram and bupropion in major depressive disorder. Psychiatry Res 169(2):132\u2013138","journal-title":"Psychiatry Res"},{"issue":"3","key":"3689_CR10","doi-asserted-by":"publisher","first-page":"1504","DOI":"10.1016\/j.neuropharm.2011.02.007","volume":"62","author":"MJ Gandal","year":"2012","unstructured":"Gandal MJ, Edgar JC, Klook K, Siegel SJ (2012) Gamma synchrony: towards a translational biomarker for the treatment\u2014resistant symptoms of schizophrenia. Neuropharmacology 62(3):1504\u20131518","journal-title":"Neuropharmacology"},{"issue":"7","key":"3689_CR11","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1038\/nrd3115","volume":"9","author":"H Hampal","year":"2010","unstructured":"Hampal H, Frank R, Broich K, Teipel SJ, Katz RG, Hardy J, Herholz K, Bokde AL, Jessen F, Hoessler YC, Sanhai WR, Zetterberg H, Woodcock J, Blennow K (2010) Biomarker for Alzheimer\u2019s disease: academic, industry and regulatory perspectives. Nat Rev Drug Discov 9(7):560\u2013574","journal-title":"Nat Rev Drug Discov"},{"issue":"1","key":"3689_CR12","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1080\/03091900701559408","volume":"33","author":"KC Chua","year":"2009","unstructured":"Chua KC, Chandran V, Acharya UR, Lim CM (2009) Analysis epileptic EEG signals using higher order spectra. J Med Eng Technol 33(1):42\u201350","journal-title":"J Med Eng Technol"},{"issue":"6","key":"3689_CR13","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1142\/S0129065710002589","volume":"20","author":"UR Acharya","year":"2010","unstructured":"Acharya UR, Chua EC, Chua KC, Min LC, Tamura T (2010) Analysis and automatic identification of sleep stages using higher order spectra. Int J Neutral Syst 20(6):509\u2013521","journal-title":"Int J Neutral Syst"},{"key":"3689_CR14","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/j.bspc.2012.08.004","volume":"8","author":"RJ Martis","year":"2013","unstructured":"Martis RJ, Acharya UR, Mandana KM, Ray AK, Chakraborty C (2013) Cardiac decision making using higher order spectra. Biomed Signal Process Control 8:193\u2013203","journal-title":"Biomed Signal Process Control"},{"issue":"3","key":"3689_CR15","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.ijpsycho.2014.07.014","volume":"94","author":"R Yuvraj","year":"2014","unstructured":"Yuvraj R, Murugappan M, Norlinah MI, Sundaraj K, Omar MI, Khairiyah M, Palaniappan R (2014) Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson\u2019s disease. Int J Psychophysiol 94(3):482\u2013495","journal-title":"Int J Psychophysiol"},{"key":"3689_CR16","first-page":"1097","volume":"1","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) ImageNet classification with deep convolutional neural networks. Adv Neural Inf Process Syst 1:1097\u20131105","journal-title":"Adv Neural Inf Process Syst"},{"key":"3689_CR17","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.ins.2017.04.012","volume":"405","author":"UR Acharya","year":"2017","unstructured":"Acharya UR, Fujita H, Oh SL, Hagiwara Y, Tan JH, Muhammad A (2017) Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network. Inf Sci 405:81\u201390","journal-title":"Inf Sci"},{"key":"3689_CR18","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.knosys.2017.06.003","volume":"132","author":"UR Acharya","year":"2017","unstructured":"Acharya UR, Fujita H, Oh SL, Muhammad A, Tan JH, Chua KC (2017) Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network. Knowl Based Syst 132:62\u201371","journal-title":"Knowl Based Syst"},{"key":"3689_CR19","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.jocs.2017.02.006","volume":"20","author":"JH Tan","year":"2017","unstructured":"Tan JH, Acharya UR, Bhandary SV, Chua KC, Sivaprasad S (2017) Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural network. J Comput Sci 20:70\u201379","journal-title":"J Comput Sci"},{"key":"3689_CR20","first-page":"1","volume":"13","author":"UR Acharya","year":"2018","unstructured":"Acharya UR, Fujita H, Oh SL, Hagiwara Y, Tan JH, Muhammad A, Tan RS (2018) Deep convolutional neural network for the automated diagnosis of congestive heart failure using ECG signals. Appl Intell 13:1\u201312","journal-title":"Appl Intell"},{"key":"3689_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2017.09.017","author":"UR Acharya","year":"2017","unstructured":"Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adeli H (2017) Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals. Comput Biol Med. https:\/\/doi.org\/10.1016\/j.compbiomed.2017.09.017","journal-title":"Comput Biol Med"},{"key":"3689_CR22","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.cmpb.2018.04.012","volume":"161","author":"UR Acharya","year":"2018","unstructured":"Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adeli H, Subha DP (2018) Automated EEG-based screening of depression using deep convolutional neural network. Comput Methods Prog Biomed 161:103\u2013113","journal-title":"Comput Methods Prog Biomed"},{"issue":"3","key":"3689_CR23","doi-asserted-by":"publisher","first-page":"952","DOI":"10.1016\/j.future.2017.08.039","volume":"79","author":"UR Acharya","year":"2018","unstructured":"Acharya UR, Fujita H, Oh SL, Raghavendra U, Tan JH, Muhammad A, Gerytch A, Hagiwara Y (2018) Automated identification of shockable and non-shockable life-threatening ventricular arrhythmias using convolutional neural network. Future Gener Comput Syst 79(3):952\u2013959","journal-title":"Future Gener Comput Syst"},{"key":"3689_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cmpb.2018.04.005","volume":"161","author":"O Faust","year":"2018","unstructured":"Faust O, Hagiwara Y, Tan JH, Oh SL, Acharya UR (2018) Deep learning for healthcare applications based on physiological signals: a review. Comput Methods Prog Biomed 161:1\u201313","journal-title":"Comput Methods Prog Biomed"},{"key":"3689_CR25","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1038\/14819","volume":"2","author":"M Riesenhuber","year":"1999","unstructured":"Riesenhuber M, Poggio T (1999) Hierarchical models of object recognition in cortex. Nat Neurosci 2:1019\u20131025","journal-title":"Nat Neurosci"},{"key":"3689_CR26","doi-asserted-by":"crossref","unstructured":"Cire\u015fan D, Meier U, Masci J (2011) A committee of neural networks for traffic sign classification. In: 396 proceedings of the 2011 international joint conference on neural networks, IEEE, California vol 397, pp 1918\u20131921","DOI":"10.1109\/IJCNN.2011.6033458"},{"key":"3689_CR27","doi-asserted-by":"crossref","unstructured":"Scherer D, M\u00fcller A, Behnke S (2010) Evaluation of pooling operations in convolutional architectures for object recognition. In: International conference on artificial neural networks. Springer, pp 82\u201391","DOI":"10.1007\/978-3-642-15825-4_10"},{"key":"3689_CR28","doi-asserted-by":"crossref","unstructured":"Serre T, Wolf L, Poggio T (2005) Object recognition with features inspired by visual cortex. In: Computer vision and pattern recognition conference, pp 994\u20131000","DOI":"10.1109\/CVPR.2005.254"},{"key":"3689_CR29","unstructured":"Kingman DP, Ba J (2015) Adam: a method for stochastic optimization. In: 3rd international conference for learning representations, San Diego"},{"issue":"5","key":"3689_CR30","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1212\/WNL.17.5.427","volume":"17","author":"M Yahr","year":"1967","unstructured":"Yahr M, Hoehn M (1967) Parkinsonism: onset, progression and mortality. Neurology 17(5):427\u2013442","journal-title":"Neurology"},{"issue":"1","key":"3689_CR31","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.eswa.2012.07.014","volume":"40","author":"HL Chen","year":"2013","unstructured":"Chen HL, Huang CC, Yu XG, Xuc X, Sund X, Wang G, Wang SJ (2013) An efficient diagnosis system for detection of Parkinson\u2019s disease using fuzzy k-nearest neighbor approach. Expert Syst Appl 40(1):263\u2013271","journal-title":"Expert Syst Appl"},{"issue":"4","key":"3689_CR32","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1016\/j.bspc.2013.02.006","volume":"8","author":"WL Zuo","year":"2013","unstructured":"Zuo WL, Wang ZY, Liu T, Chen HL (2013) Effective detection of Parkinson\u2019s disease using an adaptive fuzzy K-nearest neighbor approach. Biomed Signal Process Control 8(4):364\u2013373","journal-title":"Biomed Signal Process Control"},{"key":"3689_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2014\/985789","volume":"2014","author":"C Ma","year":"2014","unstructured":"Ma C, Ouyang J, Chen HL, Zhao XH (2014) An efficient diagnosis system for Parkinson\u2019s disease using kernel-based extreme learning machine with subtractive clustering features weighting approach. Comput Math Methods Med 2014:1\u201314","journal-title":"Comput Math Methods Med"},{"issue":"1","key":"3689_CR34","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.bspc.2012.04.007","volume":"8","author":"MR Daliri","year":"2013","unstructured":"Daliri MR (2013) Chi square distance kernel of the gaits for the diagnosis of Parkinson\u2019s disease. Biomed Signal Process Control 8(1):66\u201370","journal-title":"Biomed Signal Process Control"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3689-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-018-3689-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3689-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T08:22:04Z","timestamp":1749802924000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-018-3689-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,30]]},"references-count":34,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["3689"],"URL":"https:\/\/doi.org\/10.1007\/s00521-018-3689-5","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,30]]},"assertion":[{"value":"4 July 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 August 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2018","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 declared no conflict of interest in this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}