{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T22:54:11Z","timestamp":1793228051560,"version":"4.5.0"},"reference-count":242,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:p>Parkinson\u2019s disease is a prevalent neurodegenerative disorder, where early diagnosis is essential for slowing disease progression and optimizing treatment strategies. The latest developments in artificial intelligence (AI) have introduced new opportunities for early detection. Studies have demonstrated that before obvious motor symptoms appear, PD patients exhibit a range of subtle but quantifiable motor abnormalities. This article provides an overview of AI-driven early detection approaches based on various motor symptoms of PD, including eye movement, facial expression, speech, handwriting, finger tapping, and gait. Specifically, we summarized the characteristic manifestations of these motor symptoms, analyzed the features of the data currently collected for AI-assisted diagnosis, collected the publicly available datasets, evaluated the performance of existing diagnostic models, and discussed their limitations. By scrutinizing the existing research methodologies, this review summarizes the application progress of motor symptom-based AI technology in the early detection of PD, explores the key challenges from experimental techniques to clinical translation applications, and proposes future research directions to promote the clinical practice of AI technology in PD diagnosis.<\/jats:p>","DOI":"10.3389\/fnagi.2025.1602426","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T06:02:50Z","timestamp":1752818570000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Motor symptoms of Parkinson\u2019s disease: critical markers for early AI-assisted diagnosis"],"prefix":"10.3389","volume":"17","author":[{"given":"Ni","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajun","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingzhi","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianghua","family":"Qi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"3511","DOI":"10.1109\/ACCESS.2023.3233969","article-title":"Deep transfer learning based parkinson\u2019s disease detection using optimized feature selection.","volume":"11","author":"Abdullah","year":"2023","journal-title":"IEEE Access."},{"key":"B2","doi-asserted-by":"publisher","first-page":"29","DOI":"10.5334\/tohm.712","article-title":"Tremor in Parkinson\u2019s disease: From pathophysiology to advanced therapies.","volume":"12","author":"Abusrair","year":"2022","journal-title":"Tremor Other Hyperkinet Mov. (N Y)"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2308.02588","article-title":"Unmasking Parkinson\u2019s disease with smile: An ai-enabled screening framework.","author":"Adnan","year":"2023","journal-title":"arXiv [preprint]"},{"key":"B4","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.future.2018.11.054","article-title":"A recurrence plot-based approach for Parkinson\u2019s disease identification.","volume":"94","author":"Afonso","year":"2019","journal-title":"Fut. Generat. Comp. Syst."},{"key":"B5","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1002\/MDS.870130308","article-title":"Clinical impairment of sequential finger movements in Parkinson\u2019s disease.","volume":"13","author":"Agostino","year":"1998","journal-title":"Mov. Disord."},{"key":"B6","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1002\/mds.21887","article-title":"Voluntary, spontaneous, and reflex blinking in Parkinson\u2019s disease.","volume":"23","author":"Agostino","year":"2008","journal-title":"Mov. Disord."},{"key":"B7","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s12984-021-00807-5","article-title":"Regularity of kinematic data between single and dual-task treadmill walking in people with Parkinson\u2019s disease.","volume":"18","author":"Ahmadi","year":"2021","journal-title":"J. Neuroeng. Rehabil."},{"key":"B8","doi-asserted-by":"publisher","first-page":"3015","DOI":"10.1007\/S11042-024-20466-7\/METRICS","article-title":"Review of Parkinson\u2019s disease detection with deep-learning machines.","volume":"84","author":"Aldujaili","year":"2025","journal-title":"Multimed. Tools Appl."},{"key":"B9","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1038\/s41746-021-00502-8","article-title":"Facial expressions can detect Parkinson\u2019s disease: Preliminary evidence from videos collected online.","volume":"4","author":"Ali","year":"2021","journal-title":"NPJ Digit. Med."},{"key":"B10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/LSENS.2020.2994938","article-title":"Machine learning algorithm for gait analysis and classification on early detection of parkinson.","volume":"4","author":"Alkhatib","year":"2020","journal-title":"IEEE Sens. Lett."},{"key":"B11","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1136\/jnnp.2008.160580","article-title":"Freezing of gait in Parkinson\u2019s disease: A perceptual cause for a motor impairment?","volume":"81","author":"Almeida","year":"2010","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"B12","article-title":"Objective assessment of the finger tapping task in parkinson\u2019s disease and control subjects using azure kinect and machine learning","author":"Amprimo","year":"2023","journal-title":"Proceedings of the 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)"},{"key":"B13","doi-asserted-by":"publisher","first-page":"11923","DOI":"10.1007\/S11042-022-13759-2","article-title":"A literature review of online handwriting analysis to detect Parkinson\u2019s disease at an early stage.","volume":"82","author":"Aouraghe","year":"2023","journal-title":"Multimed. Tools Appl."},{"key":"B14","doi-asserted-by":"crossref","DOI":"10.1109\/CCIS63231.2024.10932041","article-title":"Handwriting dynamic assessment using deep neural network multi layer perceptron for parkinsons disease classification","author":"Arasavali","year":"2024","journal-title":"Proceedings of the 2024 International Conference on Communication, Control, and Intelligent Systems (CCIS)"},{"key":"B15","doi-asserted-by":"publisher","first-page":"731","DOI":"10.1007\/S12559-017-9497-X\/METRICS","article-title":"Parkinson\u2019s disease and aging: Analysis of their effect in phonation and articulation of speech.","volume":"9","author":"Arias-Vergara","year":"2017","journal-title":"Cogn. Comput."},{"key":"B16","doi-asserted-by":"publisher","first-page":"715","DOI":"10.3233\/JPD-150686","article-title":"Oculo-Visual dysfunction in Parkinson\u2019s disease.","volume":"5","author":"Armstrong","year":"2015","journal-title":"J. Parkinsons Dis."},{"key":"B17","doi-asserted-by":"publisher","first-page":"5022","DOI":"10.3390\/s20185022","article-title":"Machine-Learning analysis of voice samples recorded through smartphones: The combined effect of ageing and gender.","volume":"20","author":"Asci","year":"2020","journal-title":"Sensors (Basel)"},{"key":"B18","doi-asserted-by":"publisher","first-page":"54","DOI":"10.4103\/ABR.ABR_254_21","article-title":"Evaluating the effect of parkinson\u2019s disease on jitter and shimmer speech features.","volume":"10","author":"Azadi","year":"2021","journal-title":"Adv. Biomed. Res."},{"key":"B19","doi-asserted-by":"publisher","first-page":"586233","DOI":"10.3389\/fnagi.2020.586233","article-title":"Classifying Parkinson\u2019s disease patients with syntactic and socio-emotional verbal measures.","volume":"12","author":"Baez","year":"2020","journal-title":"Front. Aging Neurosci."},{"key":"B20","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1111\/ene.14108","article-title":"Parkinson disease.","volume":"27","author":"Balestrino","year":"2020","journal-title":"Eur. J. Neurol."},{"key":"B21","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/j.jneumeth.2017.02.006","article-title":"Analysis of facial expressions in parkinson\u2019s disease through video-based automatic methods.","volume":"281","author":"Bandini","year":"2017","journal-title":"J. Neurosci. Methods"},{"key":"B22","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/S11265-011-0576-Z\/METRICS","article-title":"Advanced biometric pen system for recording and analyzing handwriting.","volume":"68","author":"Bashir","year":"2012","journal-title":"J. Signal. Process Syst."},{"key":"B23","doi-asserted-by":"publisher","first-page":"986","DOI":"10.1037\/XLM0001396","article-title":"Marking prosodic prominence for voice assistant and human addressees.","volume":"51","author":"Beier","year":"2025","journal-title":"J. Exp. Psychol. Learn. Mem. Cogn."},{"key":"B24","first-page":"S184","article-title":"Detection of Parkinson\u2019s disease by analysis of smooth pursuit eye movements and machine learning.","volume":"37","author":"Bejani","year":"2022","journal-title":"Mov. Disord."},{"key":"B25","doi-asserted-by":"publisher","first-page":"e14824","DOI":"10.1016\/j.heliyon.2023.e14824","article-title":"Quick computer aided differential diagnostics based on repetitive finger tapping in Parkinson\u2019s disease and atypical parkinsonisms.","volume":"9","author":"Beli\u0107","year":"2023","journal-title":"Heliyon"},{"key":"B26","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/s00401-025-02853-y","article-title":"A quantitative lewy-fold-specific alpha-synuclein seed amplification assay as a progression marker for Parkinson\u2019s disease.","volume":"149","author":"Bernhardt","year":"2025","journal-title":"Acta Neuropathol."},{"key":"B27","doi-asserted-by":"publisher","first-page":"2284","DOI":"10.1016\/S0140-6736(21)00218-X","article-title":"Parkinson\u2019s disease.","volume":"397","author":"Bloem","year":"2021","journal-title":"Lancet"},{"key":"B28","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1136\/jnnp-2012-303993","article-title":"Facial bradykinesia.","volume":"84","author":"Bologna","year":"2013","journal-title":"J. Neurol Neurosurg. Psychiatry"},{"key":"B29","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1016\/j.jns.2016.08.028","article-title":"Bradykinesia in early and advanced Parkinson\u2019s disease.","volume":"369","author":"Bologna","year":"2016","journal-title":"J. Neurol. Sci."},{"key":"B30","doi-asserted-by":"publisher","first-page":"614","DOI":"10.3390\/s21020614","article-title":"Prediction of freezing of gait in Parkinson\u2019s disease using wearables and machine learning.","volume":"21","author":"Borz\u00ec","year":"2021","journal-title":"Sensors (Basel)"},{"key":"B31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.35784\/ACS-2023-11","article-title":"CNN and LSTM for the classification of parkinson\u2019s disease based on the gtcc and MFCC.","volume":"19","author":"Boualoulou","year":"2023","journal-title":"Appl. Comp. Sci."},{"key":"B32","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1017\/S135561770606111X","article-title":"Faces of emotion in Parkinsons disease: Micro-expressivity and bradykinesia during voluntary facial expressions.","volume":"12","author":"Bowers","year":"2006","journal-title":"J. Int. Neuropsychol. Soc."},{"key":"B33","doi-asserted-by":"publisher","first-page":"105316","DOI":"10.1016\/j.parkreldis.2023.105316","article-title":"Classification and staging of Parkinson\u2019s disease using video-based eye tracking.","volume":"110","author":"Brien","year":"2023","journal-title":"Parkinson. Relat. Disord."},{"key":"B34","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1186\/S12911-019-0987-5","article-title":"A low-cost vision system based on the analysis of motor features for recognition and severity rating of Parkinson\u2019s Disease.","volume":"19","author":"Buongiorno","year":"2019","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"B35","doi-asserted-by":"publisher","first-page":"126804","DOI":"10.1016\/j.neucom.2023.126804","article-title":"A systematic literature review on object detection using near infrared and thermal images.","volume":"560","author":"Bustos","year":"2023","journal-title":"Neurocomputing"},{"key":"B36","author":"Carlos","year":"2016","journal-title":"Parkinson dataset with replicated acoustic features."},{"key":"B37","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1186\/s12911-019-0989-3","article-title":"Biometric handwriting analysis to support Parkinson\u2019s disease assessment and grading.","volume":"19","author":"Cascarano","year":"2019","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"B38","doi-asserted-by":"publisher","first-page":"1213772","DOI":"10.3389\/fneur.2023.1213772","article-title":"A study on the correlations between acoustic speech variables and bradykinesia in advanced Parkinson\u2019s disease.","volume":"14","author":"Cavallieri","year":"2023","journal-title":"Front. Neurol."},{"key":"B39","article-title":"Eye-Tracking and machine learning significance in parkinson\u2019s disease symptoms prediction","author":"Chudzik","year":"2020","journal-title":"Proceedings of the Asian Conference on Intelligent Information and Database Systems"},{"key":"B40","author":"Clarke","year":"2016","journal-title":"Clinical effectiveness and cost-effectiveness of physiotherapy and occupational therapy versus no therapy in mild to moderate Parkinson\u2019s disease: A large pragmatic randomised controlled trial (PD REHAB), appendix 1, UK Parkinson\u2019s disease society brain Bank diagnostic criteria."},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.2139\/SSRN.5249672","author":"Cluzel","year":"2025","journal-title":"Pilot study on gait performance and freezing detection in Parkinson\u2019s using smart insoles."},{"key":"B42","doi-asserted-by":"publisher","first-page":"180","DOI":"10.3390\/brainsci15020180","article-title":"Eye tracking as biomarker compared to neuropsychological tests in parkinson syndromes: An exploratory pilot study before and after deep transcranial magnetic stimulation.","volume":"15","author":"Cont","year":"2025","journal-title":"Brain Sci."},{"key":"B43","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC53108.2024.10782100","article-title":"Eye-tracking in mixed reality for diagnosis of neurodegenerative diseases","author":"Daniol","year":"2024","journal-title":"Proceedings of the 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.48308\/JICSE.2025.239594.1063","article-title":"Enhanced early diagnosis of parkinson\u2019s disease via transformer-based deep learning and GAN-Augmented handwriting analysis.","author":"Darkhal","year":"2025","journal-title":"J. Innov. Comp. Sci. Eng. (JICSE)."},{"key":"B45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1017\/ATSIP.2015.22","article-title":"Deep learning: From speech recognition to language and multimodal processing.","volume":"5","author":"Deng","year":"2015","journal-title":"SIP"},{"key":"B46","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/j.patrec.2019.08.018","article-title":"Dynamically enhanced static handwriting representation for parkinson\u2019s disease detection.","volume":"128","author":"Diaz","year":"2019","journal-title":"Patt. Recogn. Lett."},{"key":"B47","doi-asserted-by":"publisher","first-page":"22199","DOI":"10.1109\/ACCESS.2017.2762475","volume":"5","author":"Dimauro","year":"2017","journal-title":"IEEE Access."},{"key":"B48","doi-asserted-by":"publisher","first-page":"120196","DOI":"10.1016\/j.jns.2022.120196","article-title":"The pathophysiology of Parkinson\u2019s disease tremor.","volume":"435","author":"Dirkx","year":"2022","journal-title":"J. Neurol. Sci."},{"key":"B49","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1044\/jshr.3804.751","article-title":"Phonatory and articulatory changes associated with increased vocal intensity in Parkinson disease: A case study.","volume":"38","author":"Dromey","year":"1995","journal-title":"J. Speech Hear. Res."},{"key":"B50","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.artmed.2016.01.004","article-title":"Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson\u2019s disease.","volume":"67","author":"Drot\u00e1r","year":"2016","journal-title":"Artif. Intell. Med."},{"key":"B51","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1109\/TNSRE.2014.2359997","article-title":"Decision support framework for Parkinson\u2019s disease based on novel handwriting markers.","volume":"23","author":"Drot\u00e1r","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"B52","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/J.NEUROL.2015.09.012","article-title":"Epidemiology of Parkinson\u2019s disease.","volume":"172","author":"Elbaz","year":"2016","journal-title":"Rev. Neurol. (Paris)"},{"key":"B53","doi-asserted-by":"publisher","first-page":"103006","DOI":"10.1016\/j.bspc.2021.103006","article-title":"Parkinson\u2019s detection based on combined CNN and LSTM using enhanced speech signals with variational mode decomposition.","volume":"70","author":"Er","year":"2021","journal-title":"Biomed. Signal Proc. Control"},{"key":"B54","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2023-2287","article-title":"An automatic multimodal approach to analyze linguistic and acoustic cues on parkinson\u2019s disease patients","author":"Escobar-Grisales","year":"","journal-title":"Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH"},{"key":"B55","doi-asserted-by":"publisher","first-page":"2163","DOI":"10.3390\/diagnostics13132163","article-title":"Deep learning and artificial intelligence applied to model speech and language in Parkinson\u2019s disease.","volume":"13","author":"Escobar-Grisales","year":"","journal-title":"Diagnostics (Basel)"},{"key":"B56","doi-asserted-by":"crossref","DOI":"10.1145\/2502081.2502224","article-title":"Recent developments in openSMILE, the munich open-source multimedia feature extractor","author":"Eyben","year":"2013","journal-title":"Proceedings of the 21st ACM international conference on Multimedia"},{"key":"B57","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.cortex.2020.08.020","article-title":"From discourse to pathology: Automatic identification of Parkinson\u2019s disease patients via morphological measures across three languages.","volume":"132","author":"Eyigoz","year":"2020","journal-title":"Cortex"},{"key":"B58","article-title":"Unsupervised morphological segmentation for detecting Parkinson\u2019s disease","author":"Eyigoz","year":"2018","journal-title":"Proceedings of the Workshops of the 32nd AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence"},{"key":"B59","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1002\/MDC3.12408","article-title":"Resting and reemergent tongue tremor as presenting symptoms of Parkinson\u2019s disease.","volume":"4","author":"Fabbri","year":"2017","journal-title":"Mov. Disord. Clin. Pract."},{"key":"B60","doi-asserted-by":"publisher","first-page":"531","DOI":"10.3390\/bioengineering10050531","article-title":"CNN-Based identification of Parkinson\u2019s disease from continuous speech in noisy environments.","volume":"10","author":"Farag\u00f3","year":"2023","journal-title":"Bioengineering (Basel)"},{"key":"B61","article-title":"A Multi-Modal array of interpretable features to evaluate language and speech patterns in different neurological disorders","author":"Favaro","year":"","journal-title":"Proceedings of the 2022 IEEE Spoken Language Technology Workshop (SLT)"},{"key":"B62","doi-asserted-by":"publisher","first-page":"107559","DOI":"10.1016\/j.compbiomed.2023.107559","article-title":"Interpretable speech features vs. DNN embeddings: What to use in the automatic assessment of Parkinson\u2019s disease in multi-lingual scenarios.","volume":"166","author":"Favaro","year":"","journal-title":"Comput. Biol. Med."},{"key":"B63","article-title":"Cross-Lingual transferability of voice analysis models: A parkinson\u2019s disease case study","author":"Ferrante","year":"2023","journal-title":"Booklet of abstracts\u2013spoken language in the medical field: Linguistic analysis, technological applications and clinical tools."},{"key":"B64","doi-asserted-by":"publisher","first-page":"1567","DOI":"10.1177\/1541931213601362","article-title":"Making sense of mobile eye-tracking data in the real-world.","volume":"60","author":"Fong","year":"2016","journal-title":"Proc. Hum. Fact. Ergonom. Soc. Ann. Meet."},{"key":"B65","author":"Gagliano","year":"2017","journal-title":"Applications of machine learning in medical diagnosis."},{"key":"B66","article-title":"Self-Supervised facial representation learning with facial region awareness","author":"Gao","year":"2024","journal-title":"Proceedings of the 2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"B67","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.bandl.2016.07.008","article-title":"How language flows when movements don\u2019t: An automated analysis of spontaneous discourse in Parkinson\u2019s disease.","volume":"162","author":"Garc\u00eda","year":"2016","journal-title":"Brain Lang."},{"key":"B68","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1038\/s41531-022-00422-8","article-title":"Detecting Parkinson\u2019s disease and its cognitive phenotypes via automated semantic analyses of action stories.","volume":"8","author":"Garc\u00eda","year":"2022","journal-title":"NPJ Parkinsons Dis."},{"key":"B69","doi-asserted-by":"publisher","first-page":"6077","DOI":"10.1007\/s11042-023-14932-x","article-title":"Determining the severity of Parkinson\u2019s disease in patients using a multi task neural network.","volume":"83","author":"Garc\u00eda-Ord\u00e1s","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"B70","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1001\/archneur.62.5.828","article-title":"Cogwheel rigidity.","volume":"62","author":"Ghiglione","year":"2005","journal-title":"Arch. Neurol."},{"key":"B71","doi-asserted-by":"publisher","first-page":"624","DOI":"10.1136\/JNNP.67.5.624","article-title":"Bradykinesia akinesia inco-ordination test (BRAIN TEST): An objective computerised assessment of upper limb motor function.","volume":"67","author":"Giovannoni","year":"1999","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"B72","doi-asserted-by":"publisher","first-page":"4327597","DOI":"10.1155\/2018\/4327597","article-title":"Tremor types in Parkinson disease: A descriptive study using a new classification.","volume":"2018","author":"Gironell","year":"2018","journal-title":"Parkinsons Dis."},{"key":"B73","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1001\/archneurol.2012.70","article-title":"Pervasive ocular tremor in patients with Parkinson disease.","volume":"69","author":"Gitchel","year":"2012","journal-title":"Arch. Neurol."},{"key":"B74","doi-asserted-by":"publisher","first-page":"a008862","DOI":"10.1101\/cshperspect.a008862","article-title":"The history of Parkinson\u2019s disease: Early clinical descriptions and neurological therapies.","volume":"1","author":"Goetz","year":"2011","journal-title":"Cold Spring Harb. Perspect. Med."},{"key":"B75","doi-asserted-by":"publisher","DOI":"10.2139\/SSRN.4069648","article-title":"Exploring facial expressions and action unit domains for parkinson detection.","author":"G\u00f3mez-G\u00f3mez","year":"2022","journal-title":"SSRN Electron. J."},{"key":"B76","doi-asserted-by":"crossref","DOI":"10.1145\/3316782.3322756","article-title":"Detecting hypomimia symptoms by selfie photo analysis","author":"Grammatikopoulou","year":"2019","journal-title":"Proceedings of the 12th ACM international conference on pervasive technologies related to assistive environments"},{"key":"B77","doi-asserted-by":"publisher","first-page":"107104","DOI":"10.1016\/j.parkreldis.2024.107104","article-title":"What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson\u2019s disease from videos.","volume":"127","author":"Guar\u00edn","year":"2024","journal-title":"Parkinson. Relat Disord."},{"key":"B78","doi-asserted-by":"publisher","first-page":"107752","DOI":"10.1016\/J.BSPC.2025.107752","article-title":"A persistent homology gait analysis for parkinson disease characterization.","volume":"106","author":"Guayac\u00e1n","year":"2025","journal-title":"Biomed. Signal Process. Control"},{"key":"B79","doi-asserted-by":"publisher","first-page":"1376425","DOI":"10.1080\/23311908.2017.1376425","article-title":"Mapping spontaneous facial expression in people with Parkinson\u2019s disease: A multiple case study design.","volume":"4","author":"Gunnery","year":"2017","journal-title":"Cogent Psychol."},{"key":"B80","doi-asserted-by":"publisher","first-page":"3848","DOI":"10.1109\/JBHI.2022.3162386","article-title":"Vision-Based finger tapping test in patients with Parkinson\u2019s disease via spatial-temporal 3d hand pose estimation.","volume":"26","author":"Guo","year":"2022","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B81","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.cogsys.2018.06.006","article-title":"Optimized cuttlefish algorithm for diagnosis of Parkinson\u2019s disease.","volume":"52","author":"Gupta","year":"2018","journal-title":"Cogn. Syst. Res."},{"key":"B82","doi-asserted-by":"publisher","first-page":"102013","DOI":"10.1016\/j.arr.2023.102013","article-title":"New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson\u2019s disease.","volume":"90","author":"Gupta","year":"2023","journal-title":"Ageing Res. Rev."},{"key":"B83","author":"Hausdorff","year":"2000","journal-title":"Gait in neurodegenerative disease database."},{"key":"B84","author":"Hausdorff","year":"2008","journal-title":"Gait in Parkinson\u2019s disease."},{"key":"B85","doi-asserted-by":"publisher","first-page":"026113","DOI":"10.1063\/1.3147408","article-title":"Gait dynamics in Parkinson\u2019s disease: Common and distinct behavior among stride length, gait variability, and fractal-like scaling.","volume":"19","author":"Hausdorff","year":"2009","journal-title":"Chaos"},{"key":"B86","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/EMBC40787.2023.10340478","article-title":"Vision transformer for Parkinson\u2019s disease classification using multilingual sustained vowel recordings.","volume":"2023","author":"Hemmerling","year":"2023","journal-title":"Annu. Int. Conf. IEEE Eng. Med. Biol. Soc."},{"key":"B87","doi-asserted-by":"publisher","first-page":"105237","DOI":"10.1016\/j.ijmedinf.2023.105237","article-title":"On the inter-dataset generalization of machine learning approaches to Parkinson\u2019s disease detection from voice.","volume":"179","author":"Hire\u0161","year":"2023","journal-title":"Int. J. Med. Inform."},{"key":"B88","doi-asserted-by":"publisher","first-page":"105021","DOI":"10.1016\/j.compbiomed.2021.105021","article-title":"Convolutional neural network ensemble for Parkinson\u2019s disease detection from voice recordings.","volume":"141","author":"Hire\u0161","year":"2022","journal-title":"Comput. Biol. Med."},{"key":"B89","author":"Hlavnika","year":"2017","journal-title":"Early biomarkers of Parkinson\u2019s disease based on natural connected speech."},{"key":"B90","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1080\/136828200410654","article-title":"Voice characteristics in the progression of Parkinson\u2019s disease.","volume":"35","author":"Holmes","year":"2000","journal-title":"Int. J. Lang. Commun. Disord."},{"key":"B91","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/978-981-16-6372-7_29","article-title":"Visual detection of parkinson\u2019s disease via facial features recognition.","volume":"801","author":"Hou","year":"2022","journal-title":"Lect. Notes Electrical Eng."},{"key":"B92","doi-asserted-by":"publisher","first-page":"e29554","DOI":"10.2196\/29554","article-title":"A markerless 2D video, facial feature recognition-based, artificial intelligence model to assist with screening for parkinson disease: Development and usability study.","volume":"23","author":"Hou","year":"2021","journal-title":"J. Med. Int. Res."},{"key":"B93","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1117\/12.2255899","article-title":"Evaluation of the Intel RealSense SR300 camera for image-guided interventions and application in vertebral level localization.","volume":"10135","author":"House","year":"2017","journal-title":"Proc. SPIE - Int. Soc. Opt. Eng."},{"key":"B94","doi-asserted-by":"publisher","first-page":"e52022","DOI":"10.2196\/52022","article-title":"Virtual reality in clinical nursing practice over the past 10 years: Umbrella review of meta-analyses.","volume":"11","author":"Hu","year":"2023","journal-title":"JMIR Serious Games"},{"key":"B95","doi-asserted-by":"publisher","first-page":"2547","DOI":"10.1109\/JBHI.2023.3239780","article-title":"Auto diagnosis of Parkinson\u2019s disease via a deep learning model based on mixed emotional facial expressions.","volume":"28","author":"Huang","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B96","doi-asserted-by":"publisher","first-page":"e0123705","DOI":"10.1371\/journal.pone.0123705","article-title":"Wearable sensor use for assessing standing balance and walking stability in people with Parkinson\u2019s disease: A systematic review.","volume":"10","author":"Hubble","year":"2015","journal-title":"PLoS One"},{"key":"B97","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1109\/TSMCC.2008.923866","article-title":"Automatic signature verification: The state of the art.","volume":"38","author":"Impedovo","year":"2008","journal-title":"IEEE Trans. Syst. Man Cybernet. Part C: Appl. Rev."},{"key":"B98","author":"Isenkul","year":"2017","journal-title":"Parkinson disease spiral drawings using digitized graphics tablet."},{"key":"B99","doi-asserted-by":"publisher","first-page":"106074","DOI":"10.1016\/j.compbiomed.2022.106074","article-title":"Smart systems and data-driven services in healthcare.","volume":"158","author":"Izonin","year":"2023","journal-title":"Comput. Biol. Med."},{"key":"B100","doi-asserted-by":"publisher","first-page":"41435","DOI":"10.1007\/s11042-023-14770-x","article-title":"68 landmarks are efficient for 3D face alignment: What about more?: 3d face alignment method applied to face recognition.","volume":"82","author":"Jabberi","year":"2023","journal-title":"Multimed. Tools Appl."},{"key":"B101","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4842-1736-8_5","article-title":"The hardware of digital painting: Tablet and stylus","author":"Jackson","year":"2015","journal-title":"Digital painting techniques."},{"key":"B102","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1136\/jnnp.2007.131045","article-title":"Parkinson\u2019s disease: Clinical features and diagnosis.","volume":"79","author":"Jankovic","year":"2008","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"B103","doi-asserted-by":"publisher","first-page":"137956","DOI":"10.1016\/j.neulet.2024.137956","article-title":"Auxiliary diagnostic method of Parkinson\u2019s disease based on eye movement analysis in a virtual reality environment.","volume":"842","author":"Jiang","year":"2024","journal-title":"Neurosci. Lett."},{"key":"B104","doi-asserted-by":"publisher","first-page":"2703","DOI":"10.1109\/JBHI.2022.3146369","article-title":"Private facial prediagnosis as an edge service for Parkinson\u2019s DBS treatment valuation.","volume":"26","author":"Jiang","year":"2022","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B105","doi-asserted-by":"publisher","first-page":"e18697","DOI":"10.2196\/18697","article-title":"Diagnosing Parkinson disease through facial expression recognition: Video analysis.","volume":"22","author":"Jin","year":"2020","journal-title":"J. Med. Int. Res."},{"key":"B106","doi-asserted-by":"publisher","first-page":"2891","DOI":"10.2147\/NDT.S149227","article-title":"Altered emotional recognition and expression in patients with Parkinson\u2019s disease.","volume":"13","author":"Jin","year":"2017","journal-title":"Neuropsychiatr. Dis. Treat."},{"key":"B107","doi-asserted-by":"publisher","first-page":"1","DOI":"10.14802\/jmd.18034","article-title":"Abnormal eye movements in parkinsonism and movement disorders.","volume":"12","author":"Jung","year":"2019","journal-title":"J. Mov. Disord."},{"key":"B108","doi-asserted-by":"publisher","first-page":"325","DOI":"10.2478\/jee-2024-0039","article-title":"Real-time visual verification of leap motion controller measurements for reliable finger tapping test in parkinson\u2019s disease.","volume":"75","author":"Kajan","year":"2024","journal-title":"J. Electrical Eng."},{"key":"B109","doi-asserted-by":"publisher","first-page":"520","DOI":"10.56042\/JSIR.V84I5.4474","article-title":"Hybrid framework for the diagnosis of Parkinson\u2019s disease using handwritten drawings-spiral and wave: Diagnosis of parkinson\u2019s disease using hand drawings-spiral and wave.","volume":"84","author":"Kamireddy","year":"2025","journal-title":"J. Sci. Indust. Res. (JSIR)"},{"key":"B110","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1016\/j.future.2020.11.020","article-title":"Handwriting dynamics assessment using deep neural network for early identification of Parkinson\u2019s disease.","volume":"117","author":"Kamran","year":"2021","journal-title":"Fut. Generat. Comp. Syst."},{"key":"B111","doi-asserted-by":"publisher","first-page":"e0214957","DOI":"10.1371\/journal.pone.0214957","article-title":"Voluntary and spontaneous facial mimicry toward other\u2019s emotional expression in patients with Parkinson\u2019s disease.","volume":"14","author":"Kang","year":"2019","journal-title":"PLoS One"},{"key":"B112","doi-asserted-by":"publisher","first-page":"21880","DOI":"10.1109\/ACCESS.2025.3535232","article-title":"Drawing-aware Parkinson\u2019s disease detection through hierarchical deep learning models.","volume":"13","author":"Kansizoglou","year":"2025","journal-title":"IEEE Access"},{"key":"B113","doi-asserted-by":"publisher","first-page":"115013","DOI":"10.1016\/j.eswa.2021.115013","article-title":"Robust automated Parkinson disease detection based on voice signals with transfer learning.","volume":"178","author":"Karaman","year":"2021","journal-title":"Exp. Syst. Appl."},{"key":"B114","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.bbe.2019.05.005","article-title":"Parkinson disease prediction using intrinsic mode function based features from speech signal.","volume":"40","author":"Karan","year":"","journal-title":"Biocybernet. Biomed. Eng."},{"key":"B115","article-title":"Stacked auto-encoder based Time-frequency features of speech signal for parkinson disease prediction","author":"Karan","year":"","journal-title":"Proceedings of the 2020 international conference on Artificial Intelligence and Signal Processing (AISP)"},{"key":"B116","article-title":"Detection of Parkinson\u2019s disease through spiral drawings using convolutional autoencoders","author":"Kasab","year":"2024","journal-title":"Proceedings of the 2024 IEEE International Conference on Smart Systems and Power Management, IC2SPM"},{"key":"B117","article-title":"Pupil: An open source platform for pervasive eye tracking and mobile gaze-based interaction","author":"Kassner","year":"2014","journal-title":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing"},{"key":"B118","doi-asserted-by":"publisher","first-page":"671261","DOI":"10.1155\/2012\/671261","article-title":"The effects of instructions on dual-task walking and cognitive task performance in people with Parkinson\u2019s disease.","volume":"2012","author":"Kelly","year":"2012","journal-title":"Parkinsons Dis."},{"key":"B119","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.artmed.2013.11.004","article-title":"A computer vision framework for finger-tapping evaluation in Parkinson\u2019s disease.","volume":"60","author":"Khan","year":"2014","journal-title":"Artif. Intell. Med."},{"key":"B120","doi-asserted-by":"crossref","DOI":"10.1109\/LSC.2018.8572136","article-title":"Parkinson\u2019s disease diagnosis based on multivariate deep features of speech signal","author":"Khojasteh","year":"2018","journal-title":"Proceedings of the 2018 IEEE Life Sciences Conference (LSC)"},{"key":"B121","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1007\/s11517-010-0697-8","article-title":"Quantification of bradykinesia during clinical finger taps using a gyrosensor in patients with Parkinson\u2019s disease.","volume":"49","author":"Kim","year":"2011","journal-title":"Med. Biol. Eng. Comput."},{"key":"B122","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1186\/s12883-022-02934-5","article-title":"TURN-IT: A novel turning intervention program to improve quality of turning in daily life in people with Parkinson\u2019s disease.","volume":"22","author":"King","year":"2022","journal-title":"BMC Neurol."},{"key":"B123","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/s0933-3657(01)00077-x","article-title":"Machine learning for medical diagnosis: History, state of the art and perspective.","volume":"23","author":"Kononenko","year":"2001","journal-title":"Artif. Intell. Med."},{"key":"B124","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.bspc.2016.08.003","article-title":"Machine learning-based classification of simple drawing movements in Parkinson\u2019s disease.","volume":"31","author":"Kotsavasiloglou","year":"2017","journal-title":"Biomed. Signal Process Control."},{"key":"B125","doi-asserted-by":"crossref","DOI":"10.1109\/TSP52935.2021.9522597","article-title":"Multilingual analysis of speech and voice disorders in patients with Parkinson\u2019s disease","author":"Kovac","year":"2021","journal-title":"Proceedings of the 2021 44th International Conference on Telecommunications and Signal Processing, TSP 2021"},{"key":"B126","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1007\/s00702-005-0354-9","article-title":"Kinetic tremor in Parkinson\u2019s disease\u2013an underrated symptom.","volume":"113","author":"Kraus","year":"2006","journal-title":"J. Neural. Transm. (Vienna)"},{"key":"B127","doi-asserted-by":"publisher","first-page":"2131","DOI":"10.1007\/s12652-020-02311-5","article-title":"Graph based feature extraction and hybrid classification approach for facial expression recognition.","volume":"12","author":"Krithika","year":"2021","journal-title":"J. Ambient Intell. Humaniz Comput."},{"key":"B128","article-title":"BradykAn: A motion capture system for objectification of hand motor tests in Parkinson Disease","author":"Krupicka","year":"2017","journal-title":"Proceedings of the 2017 E-Health and Bioengineering Conference, EHB 2017"},{"key":"B129","doi-asserted-by":"publisher","first-page":"149540","DOI":"10.1016\/j.brainres.2025.149540","article-title":"Treadmill exercise mitigates rotenone-induced neuroinflammation and \u03b1-synuclein level in a mouse model of Parkinson\u2019s disease.","volume":"1854","author":"Kumar","year":"2025","journal-title":"Brain Res."},{"key":"B130","doi-asserted-by":"publisher","first-page":"11687","DOI":"10.1007\/S11042-023-15811-1","article-title":"Parkinson\u2019s disease diagnosis using recurrent neural network based deep learning model by analyzing online handwriting.","volume":"83","author":"Kumar","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"B131","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1504\/ijdmb.2012.048196","article-title":"Selection of vocal features for Parkinson\u2019s disease diagnosis.","volume":"6","author":"Kursun","year":"2012","journal-title":"Int. J. Data Min. Bioinform."},{"key":"B132","first-page":"S914","article-title":"PARKMIM: A transversal pilot study on hemihypomimia in Parkinson disease.","volume":"34","author":"Kurtis","year":"2019","journal-title":"Mov. Disord."},{"key":"B133","doi-asserted-by":"publisher","first-page":"105995","DOI":"10.1016\/j.jcomdis.2020.105995","article-title":"An exploratory model of speech intelligibility for healthy aging based on phonatory and articulatory measures.","volume":"87","author":"Kuruvilla-Dugdale","year":"2020","journal-title":"J. Commun. Disord."},{"key":"B134","author":"Kyprakis","year":"2025","journal-title":"A Deep Learning Approach for Depressive Symptoms assessment in Parkinson\u2019s Disease Patients Using Facial Videos"},{"key":"B135","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1109\/TBME.2021.3116935","article-title":"Parkinson\u2019s disease detection based on running speech data from phone calls.","volume":"69","author":"Laganas","year":"2022","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"B136","doi-asserted-by":"publisher","first-page":"e0158852","DOI":"10.1371\/journal.pone.0158852","article-title":"A validation study of a smartphone-based finger tapping application for quantitative assessment of bradykinesia in Parkinson\u2019s disease.","volume":"11","author":"Lee","year":"2016","journal-title":"PLoS One"},{"key":"B137","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41582-022-00618-9","article-title":"Multimodal brain and retinal imaging of dopaminergic degeneration in Parkinson disease.","volume":"18","author":"Lee","year":"2022","journal-title":"Nat. Rev. Neurol."},{"key":"B138","doi-asserted-by":"publisher","first-page":"1467","DOI":"10.1002\/MDS.25990","article-title":"From micrographia to Parkinson\u2019s disease dysgraphia.","volume":"29","author":"Letanneux","year":"2014","journal-title":"Mov. Disord."},{"key":"B139","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.neucom.2021.02.011","article-title":"Automated assessment of parkinsonian finger-tapping tests through a vision-based fine-grained classification model.","volume":"441","author":"Li","year":"2021","journal-title":"Neurocomputing"},{"key":"B140","doi-asserted-by":"publisher","first-page":"105791","DOI":"10.1016\/j.parkreldis.2023.105791","article-title":"Abnormal eye movements in Parkinson\u2019s disease: From experimental study to clinical application.","volume":"115","author":"Li","year":"2023","journal-title":"Parkinson. Relat. Disord."},{"key":"B141","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1007\/S40846-022-00701-Y\/METRICS","article-title":"An automatic evaluation method for Parkinson\u2019s dyskinesia using finger tapping video for small samples.","volume":"42","author":"Li","year":"2022","journal-title":"J. Med. Biol. Eng."},{"key":"B142","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1038\/S41531-025-00953-W","article-title":"Smartphone-derived multidomain features including voice, finger-tapping movement and gait aid early identification of Parkinson\u2019s disease.","volume":"11","author":"Lim","year":"2025","journal-title":"NPJ Parkinsons Dis."},{"key":"B143","author":"Little","year":"2007","journal-title":"Parkinsons."},{"key":"B144","doi-asserted-by":"publisher","first-page":"1952","DOI":"10.1109\/TNSRE.2019.2939596","article-title":"Vision-Based method for automatic quantification of parkinsonian bradykinesia.","volume":"27","author":"Liu","year":"2019","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"B145","first-page":"562-8, quiz 569","article-title":"Age related visual impairment in the elderly.","volume":"59","author":"Loh","year":"2004","journal-title":"Med. J. Malaysia"},{"key":"B146","doi-asserted-by":"publisher","first-page":"109","DOI":"10.3233\/JPD-2011-11019","article-title":"Saccadic eye movements are related to turning performance in Parkinson disease.","volume":"1","author":"Lohnes","year":"2011","journal-title":"J. Parkinsons Dis."},{"key":"B147","doi-asserted-by":"publisher","first-page":"102849","DOI":"10.1016\/j.bspc.2021.102849","article-title":"Deep dual-side learning ensemble model for Parkinson speech recognition.","volume":"69","author":"Ma","year":"2021","journal-title":"Biomed. Signal. Process Control."},{"key":"B148","doi-asserted-by":"publisher","first-page":"295","DOI":"10.3390\/bioengineering11030295","article-title":"Leveraging deep learning for fine-grained categorization of Parkinson\u2019s disease progression levels through analysis of vocal acoustic patterns.","volume":"11","author":"Malekroodi","year":"2024","journal-title":"Bioengineering (Basel)"},{"key":"B149","article-title":"Raw speech waveform based classification of patients with als, parkinson\u2019s disease and healthy controls using CNN-BLSTM","author":"Mallela","year":"","journal-title":"Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH"},{"key":"B150","article-title":"Voice based classification of patients with amyotrophic lateral sclerosis, parkinson\u2019s disease and healthy controls with CNN-LSTM using transfer learning","author":"Mallela","year":"","journal-title":"Proceedings of the ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"},{"key":"B151","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1016\/j.parkreldis.2014.01.013","article-title":"Bradykinesia of posed smiling and voluntary movement of the lower face in Parkinson\u2019s disease.","volume":"20","author":"Marsili","year":"2014","journal-title":"Parkinsonism Relat. Disord."},{"key":"B152","doi-asserted-by":"publisher","first-page":"1395827","DOI":"10.3389\/fnhum.2024.1395827","article-title":"Bradykinesia in dystonic hand tremor: Kinematic analysis and clinical rating.","volume":"18","author":"Matejicka","year":"2024","journal-title":"Front. Hum. Neurosci."},{"key":"B153","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1038\/231315a0","article-title":"Periodicity of speech in Parkinsonism.","volume":"231","author":"Mawdsley","year":"1971","journal-title":"Nature"},{"key":"B154","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1038\/s41597-024-04186-z","article-title":"NeuroVoz: A castillian Spanish corpus of parkinsonian speech.","volume":"11","author":"Mendes-Laureano","year":"2014","journal-title":"Sci. Data"},{"key":"B155","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1136\/practneurol-2017-001635","article-title":"Communication changes in Parkinson\u2019s disease.","volume":"17","author":"Miller","year":"2017","journal-title":"Pract. Neurol."},{"key":"B156","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-3523-5_16","article-title":"Parkinson\u2019s disease diagnosis through deep learning: A novel LSTM-Based approach for freezing of gait detection","author":"Mir","year":"2024","journal-title":"Proceedings of the International Conference on Advances in Distributed Computing and Machine Learning"},{"key":"B157","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1016\/S1474-4422(19)30044-4","article-title":"Gait impairments in Parkinson\u2019s disease.","volume":"18","author":"Mirelman","year":"2019","journal-title":"Lancet Neurol."},{"key":"B158","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2111.12086","article-title":"Simulation study and at home diagnostic tool for early detection of Parkinsons disease.","author":"Mishra","year":"2021","journal-title":"arXiv [Preprint]"},{"key":"B159","doi-asserted-by":"publisher","first-page":"742654","DOI":"10.3389\/fneur.2021.742654","article-title":"Remote evaluation of parkinson\u2019s disease using a conventional webcam and artificial intelligence.","volume":"12","author":"Monje","year":"2021","journal-title":"Front. Neurol."},{"key":"B160","doi-asserted-by":"crossref","DOI":"10.23919\/EUSIPCO.2019.8903088","article-title":"Analysis of Parkinson\u2019s disease dysgraphia based on optimized fractional order derivative features","author":"Mucha","year":"2019","journal-title":"Proceedings of the 27th European Signal Processing Conference (EUSIPCO)"},{"key":"B161","article-title":"Advanced Parkinson\u2019s disease dysgraphia analysis based on fractional derivatives of online handwriting","author":"Mucha","year":"2018","journal-title":"Proceedings of the International Congress on Ultra Modern Telecommunications and Control Systems and Workshops"},{"key":"B162","doi-asserted-by":"publisher","first-page":"135600","DOI":"10.1109\/ACCESS.2023.3337804","article-title":"Multi-Model fusion of CNNs for identification of parkinson\u2019s disease using handwritten samples.","volume":"11","author":"Naz","year":"2023","journal-title":"IEEE Access"},{"key":"B163","doi-asserted-by":"publisher","first-page":"726677","DOI":"10.3389\/FPHYS.2022.726677","article-title":"Foot trajectory features in gait of Parkinson\u2019s disease patients.","volume":"13","author":"Ogata","year":"2022","journal-title":"Front. Physiol."},{"key":"B164","author":"Olcay","year":"2013","journal-title":"Parkinson\u2019s speech with multiple types of sound recordings."},{"key":"B165","doi-asserted-by":"publisher","first-page":"1302","DOI":"10.1109\/TVCG.2017.2657018","article-title":"Emulation of physician tasks in eye-tracked virtual reality for remote diagnosis of neurodegenerative disease.","volume":"23","author":"Orlosky","year":"2017","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"B166","article-title":"New Spanish speech corpus database for the analysis of people suffering from Parkinson\u2019s disease","author":"Orozco-Arroyave","year":"2014","journal-title":"Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC\u201914)"},{"key":"B167","doi-asserted-by":"crossref","DOI":"10.1109\/BIBM49941.2020.9313106","article-title":"Predicting early indicators of cognitive decline from verbal utterances","author":"Padhee","year":"2020","journal-title":"Proceedings of the 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)"},{"key":"B168","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1177\/0891988719882094","article-title":"Impaired recognition of facial emotion in patients with Parkinson disease under dopamine therapy.","volume":"33","author":"Palmeri","year":"2020","journal-title":"J. Geriatr. Psychiatry Neurol."},{"key":"B169","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1590\/0004-282X-ANP-2020-0461","article-title":"Hemihypomimia: An atypical and interesting feature of Parkinson\u2019s disease.","volume":"79","author":"Panichelli","year":"2021","journal-title":"Arq. Neuropsiquiatr."},{"key":"B170","doi-asserted-by":"publisher","first-page":"e1761","DOI":"10.1212\/WNL.0000000000011654","article-title":"Machine learning-based automatic rating for cardinal symptoms of Parkinson disease.","volume":"96","author":"Park","year":"2021","journal-title":"Neurology"},{"key":"B171","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1109\/JBHI.2015.2461555","article-title":"An emerging era in the management of Parkinson\u2019s disease: Wearable technologies and the internet of things.","volume":"19","author":"Pasluosta","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B172","author":"Pereira","year":"2021","journal-title":"HandPD dataset."},{"key":"B173","doi-asserted-by":"crossref","DOI":"10.1109\/SIBGRAPI.2016.054","article-title":"Deep learning-aided Parkinson\u2019s disease diagnosis from handwritten dynamics","author":"Pereira","year":"2016","journal-title":"Proceedings of the 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)"},{"key":"B174","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-27947-9_7","article-title":"Natural language analysis to detect Parkinson\u2019s disease","author":"P\u00e9rez-Toro","year":"2019","journal-title":"Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics)"},{"key":"B175","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.1136\/jnnp-2020-323201","article-title":"Recognising hemihypomimia as a mimic of \u2018facial weakness\u2019.","volume":"91","author":"Phillips","year":"2020","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"B176","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1002\/mds.26424","article-title":"MDS clinical diagnostic criteria for Parkinson\u2019s disease.","volume":"30","author":"Postuma","year":"2015","journal-title":"Mov. Disord."},{"key":"B177","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.jns.2015.10.056","article-title":"Does Parkinson\u2019s disease lead to alterations in the facial expression of pain?","volume":"359","author":"Priebe","year":"2015","journal-title":"J. Neurol. Sci."},{"key":"B178","doi-asserted-by":"publisher","first-page":"74078","DOI":"10.1109\/ACCESS.2025.3562566","article-title":"Automated Parkinson\u2019s disease diagnosis using decomposition techniques and deep learning for accurate gait analysis.","volume":"13","author":"Priya","year":"2025","journal-title":"IEEE Access"},{"key":"B179","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1016\/j.bbe.2022.04.002","volume":"42","author":"Quan","year":"2022","journal-title":"Biocybernet. Biomed. Eng."},{"key":"B180","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1111\/ner.13347","article-title":"Freezing of gait in Parkinson\u2019s disease: Invasive and noninvasive.","volume":"24","author":"Rahimpour","year":"2021","journal-title":"Neuromodulation"},{"key":"B181","article-title":"Towards identification of hypomimia in Parkinson\u2019s disease based on face recognition methods","author":"Rajnoha","year":"2018","journal-title":"Proceedings of the 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)"},{"key":"B182","doi-asserted-by":"publisher","first-page":"2708","DOI":"10.3390\/diagnostics12112708","article-title":"Computerized analysis with machine learning techniques for the diagnosis of Parkinson\u2019s disease: Past studies and future perspectives.","volume":"12","author":"Rana","year":"","journal-title":"Diagnostics (Basel)"},{"key":"B183","doi-asserted-by":"publisher","first-page":"2003","DOI":"10.3390\/diagnostics12082003","article-title":"Imperative role of machine learning algorithm for detection of Parkinson\u2019s disease: Review, challenges and recommendations.","volume":"12","author":"Rana","year":"","journal-title":"Diagnostics (Basel)"},{"key":"B184","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-56703-2_18","article-title":"Transfer learning approach for differentiating parkinson\u2019s syndromes using voice recordings","author":"Reddy","year":"2024","journal-title":"Advanced computing"},{"key":"B185","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2406.02608","article-title":"PPINtonus: Early detection of parkinson\u2019s disease using deep-learning tonal analysis.","author":"Reddy","year":"2024","journal-title":"arXiv [Prperint]"},{"key":"B186","doi-asserted-by":"publisher","first-page":"3923","DOI":"10.1038\/s41467-020-17419-7","article-title":"Improving the accuracy of medical diagnosis with causal machine learning.","volume":"11","author":"Richens","year":"2020","journal-title":"Nat. Commun."},{"key":"B187","article-title":"End-to-End parkinson\u2019s disease detection using a deep convolutional recurrent network","author":"Rios-Urrego","year":"2022","journal-title":"Text, speech, and dialogue. TSD 2022. Lecture notes in computer science"},{"key":"B188","doi-asserted-by":"publisher","first-page":"47","DOI":"10.14802\/jmd.19043","article-title":"Comparison of spontaneous motor tempo during finger tapping, toe tapping and stepping on the spot in people with and without Parkinson\u2019s disease.","volume":"13","author":"Rose","year":"2020","journal-title":"J. Mov. Disord."},{"key":"B189","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1007\/s00415-015-7671-1","article-title":"Speech disorders reflect differing pathophysiology in Parkinson\u2019s disease, progressive supranuclear palsy and multiple system atrophy.","volume":"262","author":"Rusz","year":"2015","journal-title":"J. Neurol."},{"key":"B190","author":"Saha","year":"2024","journal-title":"Neurodegenerative diseases detection using pattern recognition and handwriting analysis through a multimodal approach based on archimedean spiral, meander and micrographia."},{"key":"B191","author":"Sakar","year":"2018","journal-title":"Parkinson\u2019s disease classification."},{"key":"B192","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1037\/neu0000331","article-title":"Dual tasking in Parkinson\u2019s disease: Cognitive consequences while walking.","volume":"31","author":"Salazar","year":"2017","journal-title":"Neuropsychology"},{"key":"B193","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.jtbi.2012.04.032","article-title":"Do the chaotic features of gait change in Parkinson\u2019s disease?","volume":"307","author":"Sarbaz","year":"2012","journal-title":"J. Theor. Biol."},{"key":"B194","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1007\/s42979-021-00765-8","article-title":"Data science and analytics: An overview from data-driven smart computing, decision-making and applications perspective.","volume":"2","author":"Sarker","year":"","journal-title":"SN Comput. Sci."},{"key":"B195","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1007\/s42979-021-00815-1","article-title":"Deep learning: A comprehensive overview on techniques, taxonomy, applications and research directions.","volume":"2","author":"Sarker","year":"","journal-title":"SN Comput. Sci."},{"key":"B196","doi-asserted-by":"publisher","first-page":"3","DOI":"10.2147\/EB.S384769","article-title":"Detecting abnormal eye movements in patients with neurodegenerative diseases - current insights.","volume":"16","author":"Sekar","year":"2024","journal-title":"Eye Brain"},{"key":"B197","doi-asserted-by":"crossref","DOI":"10.1109\/BMEiCon.2013.6687667","article-title":"Linear and non-linear speech features for detection of parkinson\u2019s disease","author":"Shahbakhti","year":"2013","journal-title":"Proceedings of the 6th 2013 Biomedical Engineering International Conference"},{"key":"B198","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.2174\/1389557521666210927151553","article-title":"A systematic review of machine learning based gait characteristics in Parkinson\u2019s disease.","volume":"22","author":"Sharma","year":"2022","journal-title":"Mini Rev. Med. Chem."},{"key":"B199","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1109\/TMECH.2018.2881002","article-title":"Quantitative evaluation of human finger tapping movements through magnetic measurements.","volume":"24","author":"Shima","year":"2019","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"B200","doi-asserted-by":"publisher","first-page":"52466","DOI":"10.1109\/ACCESS.2024.3386367","article-title":"Classification of hand-movement disabilities in Parkinson\u2019s disease using a motion-capture device and machine learning.","volume":"12","author":"Shin","year":"2024","journal-title":"IEEE Access"},{"key":"B201","doi-asserted-by":"publisher","first-page":"2388","DOI":"10.1080\/01969722.2022.2157599","article-title":"A novel approach using learning algorithm for Parkinson\u2019s disease detection with handwritten sketches\u2019.","volume":"55","author":"Shrivastava","year":"2024","journal-title":"Cybern Syst."},{"key":"B202","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1017\/S135561770410413X","article-title":"Emotional and nonemotional facial expressions in people with Parkinson\u2019s disease.","volume":"10","author":"Simons","year":"2004","journal-title":"J. Int. Neuropsychol. Soc."},{"key":"B203","doi-asserted-by":"publisher","first-page":"9004","DOI":"10.3390\/s23219004","article-title":"A deep learning approach for automatic and objective grading of the motor impairment severity in Parkinson\u2019s disease for use in tele-assessments.","volume":"23","author":"Singh","year":"2023","journal-title":"Sensors (Basel)"},{"key":"B204","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1017\/s1355617700001454","article-title":"Spontaneous and posed facial expression in Parkinson\u2019s disease.","volume":"2","author":"Smith","year":"1996","journal-title":"J. Int. Neuropsychol. Soc."},{"key":"B205","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.parkreldis.2022.04.003","article-title":"Differential diagnosis between Parkinson\u2019s disease and atypical parkinsonism based on gait and postural instability: Artificial intelligence using an enhanced weight voting ensemble model.","volume":"98","author":"Song","year":"2022","journal-title":"Parkinson. Relat. Disord."},{"key":"B206","article-title":"Finger tapping feature extraction in Parkinson\u2019s disease using low-cost accelerometers","author":"Stamatakis","year":"2010","journal-title":"Proceedings of the IEEE\/EMBS Region 8th International Conference on Information Technology Applications in Biomedicine, ITAB"},{"key":"B207","doi-asserted-by":"publisher","first-page":"012197","DOI":"10.1088\/1742-6596\/1693\/1\/012197","article-title":"A comparison of single-buffer and double-buffer design in a systolic array generator","volume":"1693","author":"Su","year":"2020","journal-title":"J. Phys. Conf. Ser."},{"key":"B208","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1038\/s41598-022-06572-2","article-title":"Parkinson\u2019s disease severity clustering based on tapping activity on mobile device.","volume":"12","author":"Surangsrirat","year":"2022","journal-title":"Sci. Rep."},{"key":"B209","doi-asserted-by":"publisher","first-page":"4180","DOI":"10.1038\/s41598-022-07994-8","article-title":"Amplitude setting and dopamine response of finger tapping and gait are related in Parkinson\u2019s disease.","volume":"12","author":"Syeda","year":"2022","journal-title":"Sci. Rep."},{"key":"B210","article-title":"Building classifiers for parkinson\u2019s disease using new eye tribe tracking method","author":"Szyma\u0144ski","year":"2017","journal-title":"Intelligent information and database systems. ACIIDS 2017. lecture notes in computer science"},{"key":"B211","article-title":"Feature selection for an improved Parkinson\u2019s disease identification based on handwriting","author":"Taleb","year":"2017","journal-title":"Proceedings of the 2017 1st IEEE International Workshop on Arabic Script Analysis and Recognition, ASAR 2017"},{"key":"B212","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3585314","article-title":"PDGes: An interpretable detection model for parkinson\u2019s disease using smartphones.","volume":"19","author":"Teng","year":"2023","journal-title":"ACM Trans. Sen. Netw."},{"key":"B213","doi-asserted-by":"publisher","first-page":"84240","DOI":"10.1109\/ACCESS.2025.3569056","article-title":"Efficacy of wearable devices in monitoring and treating Parkinson\u2019s disease symptoms: A systematic review and meta analyses.","volume":"13","author":"Terry","year":"2025","journal-title":"IEEE Access"},{"key":"B214","year":"2023","journal-title":"Parkinson\u2019s Freezing of Gait Prediction."},{"key":"B215","doi-asserted-by":"publisher","first-page":"884","DOI":"10.1109\/TBME.2009.2036000","article-title":"Accurate telemonitoring of Parkinson\u2019s disease progression by non-invasive speech tests.","volume":"57","author":"Tsanas","year":"2010","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"B216","doi-asserted-by":"publisher","first-page":"7873","DOI":"10.3390\/APP14177873","article-title":"Innovative speech-based deep learning approaches for Parkinson\u2019s disease classification: A systematic review.","volume":"14","author":"van Gelderen","year":"2024","journal-title":"Appl. Sci."},{"key":"B217","doi-asserted-by":"publisher","first-page":"e0244396","DOI":"10.1371\/journal.pone.0244396","article-title":"An artificial neural network approach to detect presence and severity of Parkinson\u2019s disease via gait parameters.","volume":"16","author":"Varrecchia","year":"2021","journal-title":"PLoS One"},{"key":"B218","doi-asserted-by":"publisher","first-page":"1618","DOI":"10.1109\/JBHI.2018.2866873","article-title":"Multimodal assessment of Parkinson\u2019s disease: A deep learning approach.","volume":"23","author":"Vasquez-Correa","year":"2019","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B219","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.patrec.2021.04.011","article-title":"Transfer learning helps to improve the accuracy to classify patients with different speech disorders in different languages.","volume":"150","author":"V\u00e1squez-Correa","year":"2021","journal-title":"Patt. Recogn. Lett."},{"key":"B220","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1016\/j.gaitpost.2014.03.003","article-title":"Disease severity affects obstacle crossing in people with Parkinson\u2019s disease.","volume":"40","author":"Vit\u00f3rio","year":"2014","journal-title":"Gait Posture"},{"key":"B221","doi-asserted-by":"publisher","first-page":"2258","DOI":"10.1007\/s00415-024-12220-8","article-title":"Artificial intelligence in neurology: Opportunities, challenges, and policy implications.","volume":"271","author":"Voigtlaender","year":"2024","journal-title":"J. Neurol."},{"key":"B222","doi-asserted-by":"publisher","first-page":"1794","DOI":"10.1109\/JBHI.2015.2450232","article-title":"Classification of Parkinson\u2019s disease gait using spatial-temporal gait features.","volume":"19","author":"Wahid","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B223","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2890511","article-title":"Recognizing parkinsonian gait pattern by exploiting Fine-Grained movement function features.","volume":"8","author":"Wang","year":"2016","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"B224","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.1002\/1531-8257(200011)15:6<1084::aid-mds1005>3.0.co;2-y","article-title":"Kinetic tremor in a reach-to-grasp movement in Parkinson\u2019s disease.","volume":"15","author":"Wenzelburger","year":"2000","journal-title":"Mov. Disord."},{"key":"B225","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.jocn.2020.09.046","article-title":"Seeing the unseen: Could Eulerian video magnification aid clinician detection of subclinical Parkinson\u2019s tremor?","volume":"81","author":"Williams","year":"","journal-title":"J. Clin. Neurosci."},{"key":"B226","doi-asserted-by":"publisher","first-page":"117003","DOI":"10.1016\/j.jns.2020.117003","article-title":"The discerning eye of computer vision: Can it measure Parkinson\u2019s finger tap bradykinesia?","volume":"416","author":"Williams","year":"","journal-title":"J. Neurol. Sci."},{"key":"B227","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2185520.2185561","article-title":"Eulerian video magnification for revealing subtle changes in the world.","volume":"31","author":"Wu","year":"2012","journal-title":"ACM Trans. Graph."},{"key":"B228","doi-asserted-by":"publisher","first-page":"427826","DOI":"10.1155\/2014\/427826","article-title":"Objectifying facial expressivity assessment of Parkinson\u2019s patients: Preliminary study.","volume":"2014","author":"Wu","year":"2014","journal-title":"Comput. Math. Methods Med."},{"key":"B229","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1109\/TNSRE.2009.2033062","article-title":"Statistical analysis of gait rhythm in patients with Parkinson\u2019s disease.","volume":"18","author":"Wu","year":"2010","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"B230","doi-asserted-by":"publisher","first-page":"1018362","DOI":"10.3389\/FNEUR.2022.1018362","article-title":"Facial muscle movements in patients with Parkinson\u2019s disease undergoing phonation tests.","volume":"13","author":"Xu","year":"2022","journal-title":"Front. Neurol."},{"key":"B231","doi-asserted-by":"publisher","first-page":"1468895","DOI":"10.3389\/fnagi.2025.1468895","article-title":"Advances in autonomic dysfunction research in Parkinson\u2019s disease.","volume":"17","author":"Xu","year":"2025","journal-title":"Front. Aging Neurosci."},{"key":"B232","doi-asserted-by":"publisher","first-page":"104283","DOI":"10.1016\/j.ijmedinf.2020.104283","article-title":"A novel ensemble of random forest for assisting diagnosis of Parkinson\u2019s disease on small handwritten dynamics dataset.","volume":"144","author":"Xu","year":"2020","journal-title":"Int. J. Med. Inform."},{"key":"B233","doi-asserted-by":"publisher","first-page":"66961","DOI":"10.1109\/ACCESS.2022.3183232","article-title":"Automatic detection pipeline for accessing the motor severity of parkinson\u2019s disease in finger tapping and postural stability.","volume":"10","author":"Yang","year":"2022","journal-title":"IEEE Access"},{"key":"B234","doi-asserted-by":"publisher","first-page":"105411","DOI":"10.1016\/j.parkreldis.2023.105411","article-title":"Analysis of spontaneous speech in Parkinson\u2019s disease by natural language processing.","volume":"113","author":"Yokoi","year":"2023","journal-title":"Parkinson. Relat. Disord."},{"key":"B235","doi-asserted-by":"publisher","first-page":"9149","DOI":"10.3390\/s23229149","article-title":"Clinically informed automated assessment of finger tapping videos in Parkinson\u2019s disease.","volume":"23","author":"Yu","year":"2023","journal-title":"Sensors (Basel)"},{"key":"B236","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001424400019","article-title":"Unveiling Parkinson\u2019s: Handwriting symptoms with explainable and interpretable CNN model.","author":"Zemmar","year":"2025","journal-title":"Int. J. Patt. Recogn. Artif. Intell."},{"key":"B237","doi-asserted-by":"publisher","first-page":"1648","DOI":"10.1109\/JBHI.2017.2762008","article-title":"Efficacy of guided spiral drawing in the classification of Parkinson\u2019s disease.","volume":"22","author":"Zham","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B238","doi-asserted-by":"publisher","first-page":"403","DOI":"10.3389\/FNEUR.2019.00403","article-title":"A kinematic study of progressive micrographia in Parkinson\u2019s disease.","volume":"10","author":"Zham","year":"2019","journal-title":"Front. Neurol."},{"key":"B239","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1007\/S10072-024-07941-7","article-title":"Global, regional and national temporal trends in Parkinson\u2019s disease incidence, disability-adjusted life year rates in middle-aged and older adults: A cross-national inequality analysis and Bayesian age-period-cohort analysis based on the global burden of disease 2021.","volume":"46","author":"Zhang","year":"2024","journal-title":"Neurol. Sci."},{"key":"B240","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/TPAMI.2024.3474858","article-title":"RGBE-Gaze: A large-scale event-based multimodal dataset for high frequency remote gaze tracking.","volume":"47","author":"Zhao","year":"2024","journal-title":"IEEE Trans. Patt. Anal. Mach. Intell."},{"key":"B241","doi-asserted-by":"publisher","first-page":"102860","DOI":"10.1016\/J.BSPC.2021.102860","article-title":"Accurate identification of parkinson\u2019s disease by distinctive features and ensemble decision trees.","volume":"69","author":"Zhao","year":"2021","journal-title":"Biomed. Signal Process. Control."},{"key":"B242","doi-asserted-by":"publisher","first-page":"672","DOI":"10.3748\/wjg.v25.i6.672","article-title":"Artificial intelligence in medical imaging of the liver.","volume":"25","author":"Zhou","year":"2019","journal-title":"World J. Gastroenterol."}],"container-title":["Frontiers in Aging Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnagi.2025.1602426\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T06:03:01Z","timestamp":1752818581000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnagi.2025.1602426\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,18]]},"references-count":242,"alternative-id":["10.3389\/fnagi.2025.1602426"],"URL":"https:\/\/doi.org\/10.3389\/fnagi.2025.1602426","relation":{},"ISSN":["1663-4365"],"issn-type":[{"value":"1663-4365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,18]]},"article-number":"1602426"}}