{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T02:29:57Z","timestamp":1789525797782,"version":"build-2803163510"},"reference-count":32,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T00:00:00Z","timestamp":1730073600000},"content-version":"vor","delay-in-days":27,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Brain and Behavior"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Purpose<\/jats:title><jats:p>The primary aim of this study is to develop an effective and reliable diagnostic system for neurodegenerative diseases by utilizing gait data transformed into QR codes and classified using convolutional neural networks (CNNs). The objective of this method is to enhance the precision of diagnosing neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), and Huntington's disease (HD), through the introduction of a novel approach to analyze gait patterns.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The research evaluates the CNN\u2010based classification approach using QR\u2010represented gait data to address the diagnostic challenges associated with neurodegenerative diseases. The gait data of subjects were converted into QR codes, which were then classified using a CNN deep learning model. The dataset includes recordings from patients with Parkinson's disease (<jats:italic>n<\/jats:italic> = 15), Huntington's disease (<jats:italic>n<\/jats:italic> = 20), and amyotrophic lateral sclerosis (<jats:italic>n<\/jats:italic> = 13), and from 16 healthy controls.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The accuracy rates obtained through 10\u2010fold cross\u2010validation were as follows: 94.86% for NDD versus control, 95.81% for PD versus control, 93.56% for HD versus control, 97.65% for ALS versus control, and 84.65% for PD versus HD versus ALS versus control. These results demonstrate the potential of the proposed system in distinguishing between different neurodegenerative diseases and control groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The results indicate that the designed system may serve as a complementary tool for the diagnosis of neurodegenerative diseases, particularly in individuals who already present with varying degrees of motor impairment. Further validation and research are needed to establish its wider applicability.<\/jats:p><\/jats:sec>","DOI":"10.1002\/brb3.70100","type":"journal-article","created":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T10:59:52Z","timestamp":1730113192000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["CNN\u2010Based Neurodegenerative Disease Classification Using QR\u2010Represented Gait Data"],"prefix":"10.1002","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3467-9923","authenticated-orcid":false,"given":"\u00c7a\u011fatay Berke","family":"Erda\u015f","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering Ba\u015fkent University  Ankara Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emre","family":"S\u00fcmer","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering Ba\u015fkent University  Ankara Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,10,28]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-65172-9_51"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-95957-3_80"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/mds.25475"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2018.06.002"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp-2019-321138"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2015.01.012"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2015.5"},{"key":"e_1_2_10_9_1","article-title":"Topographic Classification of EEG Patterns in Huntington's Disease","volume":"2004","author":"Bellotti R.","year":"2004","journal-title":"Neurology & Clinical Neurophysiology"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2016.08.163"},{"key":"e_1_2_10_11_1","first-page":"1367","article-title":"Gait Pattern Discrimination of ALS Patients Using Classification Methods","volume":"26","author":"Bilgin S.","year":"2018","journal-title":"Turkish Journal of Electrical Engineering & Computer Science"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2012.04.007"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278\u2010019\u201000241\u2010z"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2016.09.070"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103069"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.03.018"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12553-018-0274-y"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278\u2010019\u201000306\u2010z"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1152\/jappl.1997.82.1.262"},{"key":"e_1_2_10_20_1","first-page":"607","article-title":"Machine Learning Based Method for Huntington's Disease Gait Pattern Recognition","volume":"1142","author":"Huang X.","year":"2019","journal-title":"Neural Information Processing"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.7189\/jogh.13.04160"},{"issue":"2","key":"e_1_2_10_22_1","first-page":"20","volume":"8","author":"Kalea\u011fas\u0131 H.","journal-title":"T\u00fcrkiye Klinikleri Journal of Neurology Special Topics"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.01.084"},{"key":"e_1_2_10_24_1","doi-asserted-by":"crossref","unstructured":"Manap H. 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