{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T17:53:18Z","timestamp":1791913998159,"version":"4.3.4"},"reference-count":51,"publisher":"American Association for the Advancement of Science (AAAS)","issue":"14","content-domain":{"domain":["www.science.org"],"crossmark-restriction":true},"short-container-title":["Sci. Adv."],"published-print":{"date-parts":[[2025,4,4]]},"abstract":"<jats:p>Parkinson\u2019s disease (PD) is one of the rapidly growing neurodegenerative diseases, affecting more than 10 million people worldwide. Early and accurate diagnosis of PD is highly desirable for therapeutic interventions but remains a substantial challenge. We developed a soft, portable intelligent keyboard leveraging magnetoelasticity to detect subtle pressure variations in keystroke dynamics by converting continuous keystrokes into high-fidelity electrical signals, thus enabling the quantitative analysis of PD motor symptoms using machine learning. Relying on a fundamental working mechanism, the intelligent keyboard demonstrates highly sensitive, intrinsically waterproof, and biocompatible properties, with the successful demonstration in a pilot study on patients with PD. To facilitate the potential continuous monitoring of PD, a customized cellphone application was developed to integrate the intelligent keyboard into a wireless platform. Together, the intelligent keyboard system\u2019s compelling properties position it as a promising tool for advancing early diagnosis and facilitating personalized, predictive, preventative, and participatory approaches to PD healthcare.<\/jats:p>","DOI":"10.1126\/sciadv.adt6631","type":"journal-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T17:59:14Z","timestamp":1743789554000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":24,"title":["Diagnosing Parkinson\u2019s disease via behavioral biometrics of keystroke dynamics"],"prefix":"10.1126","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9068-8325","authenticated-orcid":true,"given":"Trinny","family":"Tat","sequence":"first","affiliation":[{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8387-5723","authenticated-orcid":true,"given":"Guorui","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3157-6902","authenticated-orcid":true,"given":"Jing","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5543-0081","authenticated-orcid":true,"given":"Xun","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2213-0167","authenticated-orcid":true,"given":"Yunsheng","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3439-0495","authenticated-orcid":true,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41531-020-0117-1"},{"key":"e_1_3_2_3_2","doi-asserted-by":"crossref","first-page":"370","DOI":"10.3389\/fneur.2020.00370","article-title":"Dopamine buffering capacity imaging: A pharmacodynamic fMRI method for staging Parkinson disease","volume":"11","author":"Black K. J.","year":"2020","unstructured":"K. J. Black, H. K. Acevedo, J. M. Koller, Dopamine buffering capacity imaging: A pharmacodynamic fMRI method for staging Parkinson disease. Front. Neurol. 11, 370 (2020).","journal-title":"Front. Neurol."},{"key":"e_1_3_2_4_2","first-page":"S32","article-title":"Problems with long-term levodopa therapy for Parkinson\u2019s disease","volume":"17","author":"Marsden C. D.","year":"1994","unstructured":"C. D. Marsden, Problems with long-term levodopa therapy for Parkinson\u2019s disease. Clin. Neuropharmacol. 17, S32\u2013S44 (1994).","journal-title":"Clin. Neuropharmacol."},{"key":"e_1_3_2_5_2","doi-asserted-by":"crossref","first-page":"e0225723","DOI":"10.1371\/journal.pone.0225723","article-title":"The characteristics and treatment patterns of patients with Parkinson\u2019s disease in the United States and United Kingdom: A retrospective cohort study","volume":"14","author":"Kalilani L.","year":"2019","unstructured":"L. Kalilani, D. Friesen, N. Boudiaf, M. Asgharnejad, The characteristics and treatment patterns of patients with Parkinson\u2019s disease in the United States and United Kingdom: A retrospective cohort study. PLOS ONE 14, e0225723 (2019).","journal-title":"PLOS ONE"},{"key":"e_1_3_2_6_2","first-page":"CD008165","article-title":"Interventions to improve the appropriate use of polypharmacy for older people","volume":"2018","author":"Rankin A.","year":"2018","unstructured":"A. Rankin, C. A. Cadogan, S. M. Patterson, N. Kerse, C. R. Cardwell, M. C. Bradley, C. Ryan, C. Hughes, Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst. Rev. 2018, CD008165 (2018).","journal-title":"Cochrane Database Syst. Rev."},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.fertnstert.2018.05.006"},{"key":"e_1_3_2_8_2","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1002\/mds.21198","article-title":"Movement Disorder Society-sponsored revision of the Unified Parkinson\u2019s Disease Rating Scale (MDS-UPDRS): Process, format, and clinimetric testing plan","volume":"22","author":"Goetz C. G.","year":"2007","unstructured":"C. G. Goetz, S. Fahn, P. Martinez-Martin, W. Poewe, C. Sampaio, G. T. Stebbins, M. B. Stern, B. C. Tilley, R. Dodel, B. Dubois, R. Holloway, J. Jankovic, J. Kulisevsky, A. E. Lang, A. Lees, S. Leurgans, P. A. LeWitt, D. Nyenhuis, C. W. Olanow, O. Rascol, A. Schrag, J. A. Teresi, J. J. Van Hilten, N. LaPelle, Movement Disorder Society-sponsored revision of the Unified Parkinson\u2019s Disease Rating Scale (MDS-UPDRS): Process, format, and clinimetric testing plan. Mov. Disord. 22, 41\u201347 (2007).","journal-title":"Mov. Disord."},{"key":"e_1_3_2_9_2","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.parkreldis.2014.10.026","article-title":"Parkinson\u2019s disease severity levels and MDS-Unified Parkinson\u2019s Disease Rating Scale","volume":"21","author":"Mart\u00ednez-Mart\u00edn P.","year":"2015","unstructured":"P. Mart\u00ednez-Mart\u00edn, C. Rodr\u00edguez-Bl\u00e1zquez, M. Alvarez, T. Arakaki, V. C. Arillo, P. Chan\u00e1, W. Fern\u00e1ndez, N. Garretto, J. C. Mart\u00ednez-Castrillo, M. Rodr\u00edguez-Violante, M. Serrano-Due\u00f1as, D. Ballesteros, J. M. Rojo-Abuin, K. R. Chaudhuri, M. Merello, Parkinson\u2019s disease severity levels and MDS-Unified Parkinson\u2019s Disease Rating Scale. Parkinsonism Relat. Disord. 21, 50\u201354 (2015).","journal-title":"Parkinsonism Relat. Disord."},{"key":"e_1_3_2_10_2","doi-asserted-by":"crossref","unstructured":"W. R. Adams \u201cChapter 20\u2014Keyboard typing for the detection of early Parkinson\u2019s disease\u201d in Diagnosis and Management in Parkinson\u2019s Disease C. R. Martin V. R. Preedy Eds. (Academic Press 2020) pp. 331\u2013344.","DOI":"10.1016\/B978-0-12-815946-0.00020-X"},{"key":"e_1_3_2_11_2","doi-asserted-by":"crossref","first-page":"1436","DOI":"10.1212\/01.wnl.0000183359.50822.f2","article-title":"Progression of motor impairment and disability in Parkinson disease: A population-based study","volume":"65","author":"Alves G.","year":"2005","unstructured":"G. Alves, T. Wentzel-Larsen, D. Aarsland, J. P. Larsen, Progression of motor impairment and disability in Parkinson disease: A population-based study. Neurology 65, 1436\u20131441 (2005).","journal-title":"Neurology"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp.2007.131045"},{"key":"e_1_3_2_13_2","first-page":"20","article-title":"Impact of DaTscan in the clinical evaluation of patients with diagnostically uncertain parkinsonism","volume":"1","author":"Kar S.","year":"2015","unstructured":"S. Kar, T. Aung, Impact of DaTscan in the clinical evaluation of patients with diagnostically uncertain parkinsonism. Metric J. 1, 20\u201323 (2015).","journal-title":"Metric J."},{"key":"e_1_3_2_14_2","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1111\/j.1525-1497.2004.30535.x","article-title":"Do neurologists and primary care physicians agree on the extent of specialty involvement of patients referred to neurologists?","volume":"19","author":"Swarztrauber K.","year":"2004","unstructured":"K. Swarztrauber, B. G. Vickrey, Do neurologists and primary care physicians agree on the extent of specialty involvement of patients referred to neurologists? J. Gen. Intern. Med. 19, 654\u2013661 (2004).","journal-title":"J. Gen. Intern. Med."},{"key":"e_1_3_2_15_2","first-page":"29","article-title":"The impact of DaTscan on the diagnosis and management of movement disorders: A retrospective study","volume":"2","author":"Seifert K. D.","year":"2013","unstructured":"K. D. Seifert, J. I. Wiener, The impact of DaTscan on the diagnosis and management of movement disorders: A retrospective study. Am. J. Neurodegener. Dis. 2, 29\u201334 (2013).","journal-title":"Am. J. Neurodegener. Dis."},{"key":"e_1_3_2_16_2","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.2967\/jnumed.114.138032","article-title":"Safety analysis of 10 clinical trials and for 13 years after first approval of ioflupane 123I injection (DaTscan)","volume":"55","author":"Grosset D. G.","year":"2014","unstructured":"D. G. Grosset, K. Tatsch, W. H. Oertel, E. Tolosa, N. Bajaj, A. Kupsch, J. T. O\u2019Brien, J. Seibyl, Z. Walker, P. Sherwin, C. Chen, I. D. Grachev, Safety analysis of 10 clinical trials and for 13 years after first approval of ioflupane 123I injection (DaTscan). J. Nucl. Med. 55, 1281\u20131287 (2014).","journal-title":"J. Nucl. Med."},{"key":"e_1_3_2_17_2","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1097\/00002826-198908000-00006","article-title":"Tremors in early Parkinson\u2019s disease","volume":"12","author":"Koller W. C.","year":"1989","unstructured":"W. C. Koller, B. Vetere-Overfield, R. Barter, Tremors in early Parkinson\u2019s disease. Clin. Neuropharmacol. 12, 293\u2013297 (1989).","journal-title":"Clin. Neuropharmacol."},{"key":"e_1_3_2_18_2","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1212\/WNL.37.6.951","article-title":"Parkinson\u2019s disease: Sensory and motor problems in arms and hands","volume":"37","author":"Schneider J. S.","year":"1987","unstructured":"J. S. Schneider, S. G. Diamond, C. H. Markham, Parkinson\u2019s disease: Sensory and motor problems in arms and hands. Neurology 37, 951\u2013956 (1987).","journal-title":"Neurology"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00756.2018"},{"key":"e_1_3_2_20_2","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1586\/ern.12.49","article-title":"Distinguishing essential tremor from Parkinson\u2019s disease: Bedside tests and laboratory evaluations","volume":"12","author":"Thenganatt M. A.","year":"2012","unstructured":"M. A. Thenganatt, E. D. Louis, Distinguishing essential tremor from Parkinson\u2019s disease: Bedside tests and laboratory evaluations. Expert Rev. Neurother. 12, 687\u2013696 (2012).","journal-title":"Expert Rev. Neurother."},{"key":"e_1_3_2_21_2","unstructured":"J. C. Greenland R. A. Barker The Differential Diagnosis of Parkinson\u2019s Disease (Codon Publications 2018)."},{"key":"e_1_3_2_22_2","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1055\/s-0037-1601869","article-title":"The phenomenology of Parkinson\u2019s disease","volume":"37","author":"Hess C. W.","year":"2017","unstructured":"C. W. Hess, M. Hallett, The phenomenology of Parkinson\u2019s disease. Semin. Neurol. 37, 109\u2013117 (2017).","journal-title":"Semin. Neurol."},{"key":"e_1_3_2_23_2","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/TBME.2022.3187309","article-title":"Keystroke-dynamics for Parkinson\u2019s disease signs detection in an at-home uncontrolled population: A new benchmark and method","volume":"70","author":"Tripathi S.","year":"2023","unstructured":"S. Tripathi, T. Arroyo-Gallego, L. Giancardo, Keystroke-dynamics for Parkinson\u2019s disease signs detection in an at-home uncontrolled population: A new benchmark and method. IEEE Trans. Biomed. Eng. 70, 182\u2013192 (2023).","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"e_1_3_2_24_2","unstructured":"Average number of connected devices in U.S. 2020. Statista. www.statista.com\/statistics\/1107206\/average-number-of-connected-devices-us-house\/."},{"key":"e_1_3_2_25_2","doi-asserted-by":"crossref","first-page":"7690","DOI":"10.1038\/s41598-022-11865-7","article-title":"Diagnostic accuracy of keystroke dynamics as digital biomarkers for fine motor decline in neuropsychiatric disorders: A systematic review and meta-analysis","volume":"12","author":"Alfalahi H.","year":"2022","unstructured":"H. Alfalahi, A. H. Khandoker, N. Chowdhury, D. Iakovakis, S. B. Dias, K. R. Chaudhuri, L. J. Hadjileontiadis, Diagnostic accuracy of keystroke dynamics as digital biomarkers for fine motor decline in neuropsychiatric disorders: A systematic review and meta-analysis. Sci. Rep. 12, 7690 (2022).","journal-title":"Sci. Rep."},{"key":"e_1_3_2_26_2","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1002\/1531-8257(200001)15:1<36::AID-MDS1008>3.0.CO;2-M","article-title":"Quantitative digitography (QDG): A sensitive measure of digital motor control in idiopathic Parkinson\u2019s disease","volume":"15","author":"Bronte-Stewart H. M.","year":"2000","unstructured":"H. M. Bronte-Stewart, L. Ding, C. Alexander, Y. Zhou, G. P. Moore, Quantitative digitography (QDG): A sensitive measure of digital motor control in idiopathic Parkinson\u2019s disease. Mov. Disord. 15, 36\u201347 (2000).","journal-title":"Mov. Disord."},{"key":"e_1_3_2_27_2","doi-asserted-by":"crossref","first-page":"34468","DOI":"10.1038\/srep34468","article-title":"Computer keyboard interaction as an indicator of early Parkinson\u2019s disease","volume":"6","author":"Giancardo L.","year":"2016","unstructured":"L. Giancardo, A. S\u00e1nchez-Ferro, T. Arroyo-Gallego, I. Butterworth, C. S. Mendoza, P. Montero, M. Matarazzo, J. A. Obeso, M. L. Gray, R. S. J. Est\u00e9par, Computer keyboard interaction as an indicator of early Parkinson\u2019s disease. Sci. Rep. 6, 34468 (2016).","journal-title":"Sci. Rep."},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1002\/mds.26723"},{"key":"e_1_3_2_29_2","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.parkreldis.2020.10.047","article-title":"A validated measure of rigidity in Parkinson\u2019s disease using alternating finger tapping on an engineered keyboard","volume":"81","author":"Trager M. H.","year":"2020","unstructured":"M. H. Trager, K. B. Wilkins, M. M. Koop, H. Bronte-Stewart, A validated measure of rigidity in Parkinson\u2019s disease using alternating finger tapping on an engineered keyboard. Parkinsonism Relat. Disord. 81, 161\u2013164 (2020).","journal-title":"Parkinsonism Relat. Disord."},{"key":"e_1_3_2_30_2","doi-asserted-by":"crossref","first-page":"e0188226","DOI":"10.1371\/journal.pone.0188226","article-title":"High-accuracy detection of early Parkinson\u2019s disease using multiple characteristics of finger movement while typing","volume":"12","author":"Adams W. R.","year":"2017","unstructured":"W. R. Adams, High-accuracy detection of early Parkinson\u2019s disease using multiple characteristics of finger movement while typing. PLOS ONE 12, e0188226 (2017).","journal-title":"PLOS ONE"},{"key":"e_1_3_2_31_2","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1038\/s41598-021-03563-7","article-title":"Developing and assessing a new web-based tapping test for measuring distal movement in Parkinson\u2019s disease: A Distal Finger Tapping test","volume":"12","author":"Akram N.","year":"2022","unstructured":"N. Akram, H. Li, A. Ben-Joseph, C. Budu, D. A. Gallagher, J. P. Bestwick, A. Schrag, A. J. Noyce, C. Simonet, Developing and assessing a new web-based tapping test for measuring distal movement in Parkinson\u2019s disease: A Distal Finger Tapping test. Sci. Rep. 12, 386 (2022).","journal-title":"Sci. Rep."},{"key":"e_1_3_2_32_2","doi-asserted-by":"crossref","unstructured":"O. M. J. Hooman J. Oldfield M. A. Nicolaou \u201cDetecting early Parkinson\u2019s disease from keystroke dynamics using the tensor-train decomposition\u201d in 2019 27th European Signal Processing Conference (EUSIPCO) (IEEE 2019) pp. 1\u20135.","DOI":"10.23919\/EUSIPCO.2019.8902562"},{"key":"e_1_3_2_33_2","doi-asserted-by":"crossref","unstructured":"A. Milne K. Farrahi M. A. Nicolaou \u201cLess is more: Univariate modelling to detect early Parkinson\u2019s disease from keystroke dynamics\u201d in Discovery Science L. Soldatova J. Vanschoren G. Papadopoulos M. Ceci Eds. (Springer 2018) pp. 435\u2013446.","DOI":"10.1007\/978-3-030-01771-2_28"},{"key":"e_1_3_2_34_2","doi-asserted-by":"crossref","first-page":"e89","DOI":"10.2196\/jmir.9462","article-title":"Detecting motor impairment in early Parkinson\u2019s disease via natural typing interaction with keyboards: Validation of the neuroQWERTY approach in an uncontrolled at-home setting","volume":"20","author":"Arroyo-Gallego T.","year":"2018","unstructured":"T. Arroyo-Gallego, M. J. Ledesma-Carbayo, I. Butterworth, M. Matarazzo, P. Montero-Escribano, V. Puertas-Mart\u00edn, M. L. Gray, L. Giancardo, \u00c1. S\u00e1nchez-Ferro, Detecting motor impairment in early Parkinson\u2019s disease via natural typing interaction with keyboards: Validation of the neuroQWERTY approach in an uncontrolled at-home setting. J. Med. Internet Res. 20, e89 (2018).","journal-title":"J. Med. Internet Res."},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41563-021-01093-1"},{"key":"e_1_3_2_36_2","unstructured":"National Institute for Occupational Safety and Health Alternative Keyboards (U.S. Department of Health and Human Services Centers for Disease Control and Prevention 1997); https:\/\/stacks.cdc.gov\/view\/cdc\/5178."},{"key":"e_1_3_2_37_2","doi-asserted-by":"crossref","unstructured":"T. K. Ho \u201cRandom decision forests\u201d in Proceedings of 3rd International Conference on Document Analysis and Recognition (IEEE 1995) vol. 1 pp. 278\u2013282.","DOI":"10.1109\/ICDAR.1995.598994"},{"key":"e_1_3_2_38_2","unstructured":"S.-A. Rebuffi S. Gowal D. A. Calian F. Stimberg O. Wiles T. Mann Data augmentation can improve robustness. arXiv:2111.05328 [cs.CV] (2021)."},{"key":"e_1_3_2_39_2","doi-asserted-by":"crossref","unstructured":"S. C. Wong A. Gatt V. Stamatescu M. D. McDonnell \u201cUnderstanding data augmentation for classification: When to warp?\u201d in 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (IEEE 2016) pp. 1\u20136.","DOI":"10.1109\/DICTA.2016.7797091"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"key":"e_1_3_2_41_2","doi-asserted-by":"crossref","unstructured":"L. Torrey J. Shavlik L. Torrey J. Shavlik \u201cTransfer learning\u201d in Handbook of Research on Machine Learning Applications and Trends: Algorithms Methods and Techniques (IGI Global 2010) pp. 242\u2013264.","DOI":"10.4018\/978-1-60566-766-9.ch011"},{"key":"e_1_3_2_42_2","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s40537-016-0043-6","article-title":"A survey of transfer learning","volume":"3","author":"Weiss K.","year":"2016","unstructured":"K. Weiss, T. M. Khoshgoftaar, D. Wang, A survey of transfer learning. J. Big Data 3, 9 (2016).","journal-title":"J. Big Data"},{"key":"e_1_3_2_43_2","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/JPROC.2020.3004555","article-title":"A comprehensive survey on transfer learning","volume":"109","author":"Zhuang F.","year":"2021","unstructured":"F. Zhuang, Z. Qi, K. Duan, D. Xi, Y. Zhu, H. Zhu, H. Xiong, Q. He, A comprehensive survey on transfer learning. Proc. IEEE 109, 43\u201376 (2021).","journal-title":"Proc. IEEE"},{"key":"e_1_3_2_44_2","doi-asserted-by":"crossref","unstructured":"C. Szegedy W. Liu Y. Jia P. Sermanet S. Reed D. Anguelov D. Erhan V. Vanhoucke A. Rabinovich \u201cGoing deeper with convolutions\u201d in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE 2015) pp. 1\u20139.","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"e_1_3_2_45_2","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava N.","year":"2014","unstructured":"N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, R. Salakhutdinov, Dropout: A simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929\u20131958 (2014).","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_46_2","first-page":"1396","article-title":"CNN explainer: Learning convolutional neural networks with interactive visualization","volume":"27","author":"Wang Z. J.","year":"2021","unstructured":"Z. J. Wang, R. Turko, O. Shaikh, H. Park, N. Das, F. Hohman, M. Kahng, D. H. P. Chau, CNN explainer: Learning convolutional neural networks with interactive visualization. IEEE Trans. Vis. 27, 1396\u20131406 (2021).","journal-title":"IEEE Trans. Vis."},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1088\/1361-665X\/aadff5"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.matt.2021.09.012"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.3390\/s22186831"},{"key":"e_1_3_2_50_2","doi-asserted-by":"crossref","unstructured":"S. H. Roy B. T. Cole L. D. Gilmore C. J. De Luca S. H. Nawab \u201cResolving signal complexities for ambulatory monitoring of motor function in Parkinson\u2019s disease\u201d in 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE 2011) pp. 4836\u20134839.","DOI":"10.1109\/IEMBS.2011.6091198"},{"key":"e_1_3_2_51_2","doi-asserted-by":"crossref","first-page":"7076","DOI":"10.1109\/TMM.2022.3217392","article-title":"A robust frequency-domain-based graph adaptive network for Parkinson\u2019s disease detection from gait data","volume":"25","author":"Zhong C.","year":"2023","unstructured":"C. Zhong, W. W. Y. Ng, A robust frequency-domain-based graph adaptive network for Parkinson\u2019s disease detection from gait data. IEEE Trans. Multimedia 25, 7076\u20137088 (2023).","journal-title":"IEEE Trans. Multimedia"},{"key":"e_1_3_2_52_2","first-page":"787563","article-title":"Continuous and unconstrained tremor monitoring in Parkinson\u2019s disease using supervised machine learning and wearable sensors","volume":"2024","author":"Rodriguez F.","year":"2024","unstructured":"F. Rodriguez, P. Krauss, J. Kluckert, F. Ryser, L. Stieglitz, C. Baumann, R. Gassert, L. Imbach, O. Bichsel, Continuous and unconstrained tremor monitoring in Parkinson\u2019s disease using supervised machine learning and wearable sensors. Parkinsons Dis. 2024, 787563 (2024).","journal-title":"Parkinsons Dis."}],"container-title":["Science Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.science.org\/doi\/pdf\/10.1126\/sciadv.adt6631","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T18:11:05Z","timestamp":1743790265000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.science.org\/doi\/10.1126\/sciadv.adt6631"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,4]]},"references-count":51,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2025,4,4]]}},"alternative-id":["10.1126\/sciadv.adt6631"],"URL":"https:\/\/doi.org\/10.1126\/sciadv.adt6631","relation":{},"ISSN":["2375-2548"],"issn-type":[{"value":"2375-2548","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,4]]},"assertion":[{"value":"2024-10-06","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-28","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-04-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"eadt6631"}}