{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T17:45:45Z","timestamp":1785519945517,"version":"3.56.0"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T00:00:00Z","timestamp":1700524800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T00:00:00Z","timestamp":1700524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP22K20843"],"award-info":[{"award-number":["JP22K20843"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Neurol"],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1007\/s00415-023-12091-5","type":"journal-article","created":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T20:02:50Z","timestamp":1700596970000},"page":"1004-1012","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Differentiation of speech in Parkinson\u2019s disease and spinocerebellar degeneration using deep neural networks"],"prefix":"10.1007","volume":"271","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2988-2532","authenticated-orcid":false,"given":"Katsuki","family":"Eguchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroaki","family":"Yaguchi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ikue","family":"Kudo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ibuki","family":"Kimura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomoko","family":"Nabekura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryuto","family":"Kumagai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenichi","family":"Fujita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuichi","family":"Nakashiro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuki","family":"Iida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinsuke","family":"Hamada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanae","family":"Honma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asako","family":"Takei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fumio","family":"Moriwaka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ichiro","family":"Yabe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,11,21]]},"reference":[{"key":"12091_CR1","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1044\/jshr.1202.246","volume":"12","author":"FL Darley","year":"1969","unstructured":"Darley FL, Aronson AE, Brown JR (1969) Differential diagnostic patterns of dysarthria. J Speech Hear Res 12:246\u2013269. https:\/\/doi.org\/10.1044\/jshr.1202.246","journal-title":"J Speech Hear Res"},{"key":"12091_CR2","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1016\/j.tins.2008.02.011","volume":"31","author":"H Ackermann","year":"2008","unstructured":"Ackermann H (2008) Cerebellar contributions to speech production and speech perception: psycholinguistic and neurobiological perspectives. Trends Neurosci 31:265\u2013272. https:\/\/doi.org\/10.1016\/j.tins.2008.02.011","journal-title":"Trends Neurosci"},{"key":"12091_CR3","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1002\/mds.24030","volume":"27","author":"T Schmitz-H\u00fcbsch","year":"2012","unstructured":"Schmitz-H\u00fcbsch T, Eckert O, Schlegel U, Klockgether T, Skodda S (2012) Instability of syllable repetition in patients with spinocerebellar ataxia and Parkinson\u2019s disease. Mov Disord 27:316\u2013319. https:\/\/doi.org\/10.1002\/mds.24030","journal-title":"Mov Disord"},{"key":"12091_CR4","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1007\/s00415-019-09271-7","volume":"266","author":"J Rusz","year":"2019","unstructured":"Rusz J, Tykalov\u00e1 T, Salerno G, Bancone S, Scarpelli J, Pellecchia MT (2019) Distinctive speech signature in cerebellar and parkinsonian subtypes of multiple system atrophy. J Neurol 266:1394\u20131404. https:\/\/doi.org\/10.1007\/s00415-019-09271-7","journal-title":"J Neurol"},{"key":"12091_CR5","doi-asserted-by":"publisher","DOI":"10.2196\/46105","volume":"19","author":"A Idrisoglu","year":"2023","unstructured":"Idrisoglu A, Dallora AL, Anderberg P, Berglund JS (2023) Applied machine learning techniques to diagnose voice-affecting conditions and disorders: systematic literature review. J Med Internet Res 19:e46105. https:\/\/doi.org\/10.2196\/46105","journal-title":"J Med Internet Res"},{"key":"12091_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2022.107133","volume":"226","author":"QC Ngo","year":"2022","unstructured":"Ngo QC, Motin MA, Pah ND, Drot\u00e1r P, Kempster P, Kumar D (2022) Computerized analysis of speech and voice for Parkinson\u2019s disease: a systematic review. Comput Methods Programs Biomed 226:107133. https:\/\/doi.org\/10.1016\/j.cmpb.2022.107133","journal-title":"Comput Methods Programs Biomed"},{"key":"12091_CR7","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/JSTSP.2019.2908700","volume":"13","author":"H Purwins","year":"2019","unstructured":"Purwins H, Li B, Virtanen T, Schulter J, Chang S, Sainath T (2019) Deep learning for audio signal processing. IEEE J Sel Top Sig Process 13:206\u2013219. https:\/\/doi.org\/10.1109\/JSTSP.2019.2908700","journal-title":"IEEE J Sel Top Sig Process"},{"key":"12091_CR8","doi-asserted-by":"publisher","unstructured":"Ajit A, Acharya K, Samanta A (2020) A Review of Convolutional Neural Networks. International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). pp 1\u20135. https:\/\/doi.org\/10.1109\/ic-ETITE47903.2020.049","DOI":"10.1109\/ic-ETITE47903.2020.049"},{"key":"12091_CR9","doi-asserted-by":"publisher","unstructured":"Piczak KJ (2015) Environmental sound classification with convolutional neural networks. In: Proc. 25th Int. Workshop Mach. Learning Signal Process. pp 1\u20136. https:\/\/doi.org\/10.1109\/MLSP.2015.7324337","DOI":"10.1109\/MLSP.2015.7324337"},{"key":"12091_CR10","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1016\/j.bspc.2018.08.035","volume":"47","author":"Z Jianfeng","year":"2018","unstructured":"Jianfeng Z, Xia M, Lijiang C (2018) Speech emotion recognition using deep 1D & 2D CNN LSTM networks. Biomed Signal Process Control 47:312\u2013323. https:\/\/doi.org\/10.1016\/j.bspc.2018.08.035","journal-title":"Biomed Signal Process Control"},{"key":"12091_CR11","doi-asserted-by":"publisher","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. Presented at: Proceedings of the Advances in Neural Information Processing Systems pp 1\u201311. https:\/\/doi.org\/10.48550\/arXiv.1706.03762","DOI":"10.48550\/arXiv.1706.03762"},{"key":"12091_CR12","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2110.05069","author":"K Koutini","year":"2022","unstructured":"Koutini K, Schl\u00fcter J, Eghbal-zadeh H, Widmer G (2022) Efficient training of audio transformers with patchout. Proc Interspeech. https:\/\/doi.org\/10.48550\/arXiv.2110.05069","journal-title":"Proc Interspeech"},{"key":"12091_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105021","volume":"141","author":"M Hire\u0161","year":"2022","unstructured":"Hire\u0161 M, Gazda M, Drot\u00e1r P, Pah ND, Motin MA, Kumar DK (2022) Convolutional neural network ensemble for Parkinson\u2019s disease detection from voice recordings. Comput Biol Med 141:105021. https:\/\/doi.org\/10.1016\/j.compbiomed.2021.105021","journal-title":"Comput Biol Med"},{"key":"12091_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102850","volume":"69","author":"X Zhang","year":"2021","unstructured":"Zhang X, Ma J, Li Y, Wang P, Liu Y (2021) Few-shot learning of Parkinson\u2019s disease speech data with optimal convolution sparse kernel transfer learning. Biomed Signal Process Control 69:102850. https:\/\/doi.org\/10.1016\/j.bspc.2021.102850","journal-title":"Biomed Signal Process Control"},{"key":"12091_CR15","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1136\/jnnp.55.3.181","volume":"55","author":"AJ Hughes","year":"1992","unstructured":"Hughes AJ, Daniel SE, Kilford L, Lees AJ (1992) Accuracy of clinical diagnosis of idiopathic Parkinson\u2019s disease: a clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry 55:181\u2013184. https:\/\/doi.org\/10.1136\/jnnp.55.3.181","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"12091_CR16","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1212\/01.wnl.0000324625.00404.15","volume":"71","author":"S Gilman","year":"2008","unstructured":"Gilman S, Wenning GK, Low PA, Brooks DJ, Mathias CJ, Trojanowski JQ, Wood NW, Colosimo C, D\u00fcrr A, Fowler CJ, Kaufmann H, Klockgether T, Lees A, Poewe W, Quinn N, Revesz T, Robertson D, Sandroni P, Seppi K, Vidailhet M (2008) Second consensus statement on the diagnosis of multiple system atrophy. Neurology 71:670\u2013676. https:\/\/doi.org\/10.1212\/01.wnl.0000324625.00404.15","journal-title":"Neurology"},{"key":"12091_CR17","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1161\/01.STR.19.5.604","volume":"19","author":"JC van Swieten","year":"1988","unstructured":"van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J (1988) Interobserver agreement for the assessment of handicap in stroke patients. Stroke 19:604\u2013607. https:\/\/doi.org\/10.1161\/01.STR.19.5.604","journal-title":"Stroke"},{"key":"12091_CR18","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1212\/WNL.17.5.427","volume":"17","author":"MM Hoehn","year":"1967","unstructured":"Hoehn MM, Yahr MD (1967) Parkinsonism: onset, progression and mortality. Neurology 17:427\u2013442. https:\/\/doi.org\/10.1212\/WNL.17.5.427","journal-title":"Neurology"},{"key":"12091_CR19","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0053852","volume":"8","author":"H Zhou","year":"2013","unstructured":"Zhou H, Chen Z, Shi H, Wu Y, Yin S (2013) Categories of auditory performance and speech intelligibility ratings of early-implanted children without speech training. PLoS ONE 8:e53852. https:\/\/doi.org\/10.1371\/journal.pone.0053852","journal-title":"PLoS ONE"},{"key":"12091_CR20","doi-asserted-by":"publisher","unstructured":"Gemmeke JF, Ellis DPW, Freedman D, Jansen A, Lawrence W, Moore RC, Pakal M, Ritter M (2017) Audio set: an ontology and human-labeled dataset for audio events. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp 776\u2013780. https:\/\/doi.org\/10.1109\/ICASSP.2017.7952261","DOI":"10.1109\/ICASSP.2017.7952261"},{"key":"12091_CR21","doi-asserted-by":"publisher","unstructured":"Hendrycks D, Gimpel K (2016) Gaussian error linear units (Gelus) https:\/\/doi.org\/10.48550\/arXiv.1606.08415","DOI":"10.48550\/arXiv.1606.08415"},{"key":"12091_CR22","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s00521-019-04069-0","volume":"32","author":"A Naseer","year":"2020","unstructured":"Naseer A, Rani M, Naz S, Razzak MI, Imran M, Xu G (2020) Refining Parkinson\u2019s neurological disorder identification through deep transfer learning. Neural Comput Appl 32:39\u2013854. https:\/\/doi.org\/10.1007\/s00521-019-04069-0","journal-title":"Neural Comput Appl"},{"key":"12091_CR23","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/j.clinph.2019.09.031","volume":"131","author":"M Abou Jaoude","year":"2020","unstructured":"Abou Jaoude M, Jing J, Sun H, Jacobs CS, Pellerin KR, Westover MB, Cash SS, Lam AD (2020) Detection of mesial temporal lobe epileptiform discharges on intracranial electrodes using deep learning. Clin Neurophysiol 131:133\u2013141. https:\/\/doi.org\/10.1016\/j.clinph.2019.09.031","journal-title":"Clin Neurophysiol"},{"key":"12091_CR24","doi-asserted-by":"publisher","first-page":"1114360","DOI":"10.3389\/fneur.2023.1114360","volume":"14","author":"L Fast","year":"2023","unstructured":"Fast L, Temuulen U, Villringer K, Kufner A, Ali HF, Siebert E, Huo S, Piper SK, Sperber PS, Liman T, Endres M, Ritter K (2023) Machine learning-based prediction of clinical outcomes after first-ever ischemic stroke. Front Neurol 14:1114360. https:\/\/doi.org\/10.3389\/fneur.2023.1114360","journal-title":"Front Neurol"},{"key":"12091_CR25","doi-asserted-by":"publisher","first-page":"6585264","DOI":"10.1155\/2020\/6585264","volume":"24","author":"K Nakayama","year":"2020","unstructured":"Nakayama K, Yamamoto T, Oda C, Sato M, Murakami T, Horiguchi S (2020) Effectiveness of Lee Silverman voice treatment\u00ae LOUD on Japanese-speaking patients with Parkinson\u2019s disease. Rehabil Res Pract 24:6585264. https:\/\/doi.org\/10.1155\/2020\/6585264","journal-title":"Rehabil Res Pract"},{"key":"12091_CR26","doi-asserted-by":"publisher","first-page":"897","DOI":"10.1016\/j.recesp.2011.06.008","volume":"64","author":"CW Pattanayak","year":"2011","unstructured":"Pattanayak CW, Rubin DB, Zell ER (2011) Propensity score methods for creating covariate balance in observational studies. Rev Esp Cardiol 64:897\u2013903. https:\/\/doi.org\/10.1016\/j.recesp.2011.06.008","journal-title":"Rev Esp Cardiol"},{"key":"12091_CR27","doi-asserted-by":"publisher","first-page":"1257","DOI":"10.1016\/S1474-4422(16)30230-7","volume":"15","author":"A Ascherio","year":"2016","unstructured":"Ascherio A, Schwarzschild MA (2016) The epidemiology of Parkinson\u2019s disease: risk factors and prevention. Lancet Neurol 15:1257\u20131272. https:\/\/doi.org\/10.1016\/S1474-4422(16)30230-7","journal-title":"Lancet Neurol"}],"container-title":["Journal of Neurology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00415-023-12091-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00415-023-12091-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00415-023-12091-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T02:08:58Z","timestamp":1706666938000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00415-023-12091-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,21]]},"references-count":27,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,2]]}},"alternative-id":["12091"],"URL":"https:\/\/doi.org\/10.1007\/s00415-023-12091-5","relation":{},"ISSN":["0340-5354","1432-1459"],"issn-type":[{"value":"0340-5354","type":"print"},{"value":"1432-1459","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,21]]},"assertion":[{"value":"8 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 October 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2023","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 have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The study protocol was approved by the Institutional Review Board of the Hokuyukai Neurological Hospital (approval number: 2023-4).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was waived owing to the study\u2019s retrospective nature.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}}]}}