{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T09:39:46Z","timestamp":1782553186387,"version":"3.54.5"},"reference-count":39,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,17]],"date-time":"2015-09-17T00:00:00Z","timestamp":1442448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A challenge for the clinical management of advanced Parkinson\u2019s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and\/or treatment-induced motor symptoms.<\/jats:p>","DOI":"10.3390\/s150923727","type":"journal-article","created":{"date-parts":[[2015,9,17]],"date-time":"2015-09-17T16:40:26Z","timestamp":1442508026000},"page":"23727-23744","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["Automatic Spiral Analysis for Objective Assessment of Motor Symptoms in Parkinson\u2019s Disease"],"prefix":"10.3390","volume":"15","author":[{"given":"Mevludin","family":"Memedi","sequence":"first","affiliation":[{"name":"School of Technology and Business Studies, Computer Engineering, Dalarna University,  Falun SE-791-88, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aleksander","family":"Sadikov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Laboratory, Faculty of Computer and Information Science,  University of Ljubljana, Ljubljana 1000, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vida","family":"Groznik","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Laboratory, Faculty of Computer and Information Science,  University of Ljubljana, Ljubljana 1000, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jure","family":"\u017dabkar","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Laboratory, Faculty of Computer and Information Science,  University of Ljubljana, Ljubljana 1000, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Mo\u017eina","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Laboratory, Faculty of Computer and Information Science,  University of Ljubljana, Ljubljana 1000, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Filip","family":"Bergquist","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, Sahlgrenska Academy, University of Gothenburg,  Gothenburg 405 30, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anders","family":"Johansson","sequence":"additional","affiliation":[{"name":"Department of Clinical Neuroscience, Neurology, Karolinska Institutet, Stockholm 171 76, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dietrich","family":"Haubenberger","sequence":"additional","affiliation":[{"name":"Clinical Trials Unit, Office of the Clinical Director, NINDS Intramural Research Program, National Institutes of Health, 10 Center Drive, Rm 6C-5700, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dag","family":"Nyholm","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Neurology, Uppsala University, Uppsala 751 85, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1002\/mds.26082","article-title":"Levodopa therapy for Parkinson\u2019s disease: Pharmacokinetics and pharmacodynamics","volume":"30","author":"LeWitt","year":"2005","journal-title":"Mov. Disord."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/s100720170066","article-title":"Unawareness of dyskinesia in Parkinson\u2019s and Hunington\u2019s diseases","volume":"22","author":"Vitale","year":"2001","journal-title":"Neurol. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1002\/mds.10690","article-title":"Wireless real-time electronic data capture for self-assessment of motor function and quality of life in Parkinson\u2019s disease","volume":"19","author":"Nyholm","year":"2004","journal-title":"Mov. Disord."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1002\/mds.22340","article-title":"Movement Disorder Society-sponsored revision of the Unified Parkinson\u2019s Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results","volume":"23","author":"Goetz","year":"2008","journal-title":"Mov. Disord."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1020","DOI":"10.1002\/mds.20213","article-title":"Movement Disorder Society Task Force report on the Hoehn and Yahr staging scale: Status and recommendations","volume":"19","author":"Goetz","year":"2004","journal-title":"Mov. Disord."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1002\/mds.25628","article-title":"Quantitative wearable sensors for objective assessment of Parkinson\u2019s disease","volume":"28","author":"Maetzler","year":"2013","journal-title":"Mov. Disord."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16965","DOI":"10.3390\/s131216965","article-title":"Automatic and objective assessment of alternating tapping performance in Parkinson\u2019s disease","volume":"13","author":"Memedi","year":"2013","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1080\/00222895.2013.815152","article-title":"The discriminating properties of an optoelectronic movement analysis method in patients with Parkinsonism","volume":"45","author":"Zackrisson","year":"2013","journal-title":"J. Mot. Behav."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"21329","DOI":"10.3390\/s141121329","article-title":"PERFORM: A system for monitoring, assessment and management of patients with Parkinson\u2019s disease","volume":"14","author":"Tzallas","year":"2014","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"17235","DOI":"10.3390\/s140917235","article-title":"Wearability assessment of a wearable system for Parkinson\u2019s disease remote monitoring based on a body area network of sensors","volume":"14","author":"Cancela","year":"2014","journal-title":"Sensors"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1109\/TNSRE.2013.2287241","article-title":"Automatic identification and classification of freezing of gait episodes in Parkinson\u2019s disease patients","volume":"22","author":"Jovicic","year":"2014","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.cmpb.2012.10.016","article-title":"Automatic detection of freezing of gait events in patients with Parkinson\u2019s disease","volume":"110","author":"Tripoliti","year":"2013","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"884","DOI":"10.1109\/TBME.2009.2036000","article-title":"Accurate telemonitoring of Parkinson\u2019s disease progression by noninvasive speech tests","volume":"57","author":"Tsanas","year":"2010","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1109\/TBME.2011.2116017","article-title":"Hilbert-Huang-based tremor removal to assess postural properties from accelerometers","volume":"58","author":"Mellone","year":"2011","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.parkreldis.2014.02.022","article-title":"Clinician versus machine: Reliability and responsiveness of motor endpoints in Parkinson\u2019s disease","volume":"20","author":"Heldman","year":"2014","journal-title":"Parkinsonism Rel. Disord."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1109\/TITB.2011.2182616","article-title":"Assessment of tremor activity in the Parkinson\u2019s disease using a set of wearable sensors","volume":"16","author":"Rigas","year":"2012","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1109\/TBME.2006.886670","article-title":"Quantification of tremor and bradykinesia in Parkinson\u2019s disease using a novel ambulatory monitoring system","volume":"54","author":"Salarian","year":"2007","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"47","DOI":"10.3233\/JPD-2012-11071","article-title":"Automated assessment of bradykinesia and dyskinesia in Parkinson\u2019s disease","volume":"2","author":"Griffiths","year":"2012","journal-title":"J. Parkinson\u2019s Dis."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Dai, H., Lin, H., and Lueth, T.C. (2015). Quantitative assessment of parkinsonian bradykinesia based on an inertial measurement unit. Biomed. Eng. Online, 14.","DOI":"10.1186\/s12938-015-0067-8"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1002\/mds.10310","article-title":"Automatic assessment of levodopa-induced dyskinesia in daily life by neural networks","volume":"18","author":"Keijsers","year":"2003","journal-title":"Mov. Disord."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lopane, G., Mellone, S., Cortelli, P., Calandra-Buonaura, G., and Contin, M. (2015). Dyskinesia detection and monitoring by a single sensor in patients with Parkinson\u2019s disease. Mov. Disord., in press.","DOI":"10.1002\/mds.26313"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1002\/mds.21874","article-title":"Validity of spiral analysis in early Parkinson\u2019s disease","volume":"23","author":"Derby","year":"2008","journal-title":"Mov. Disord."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.jneumeth.2010.04.027","article-title":"A new computer method for assessing drawing impairment in Parkinson\u2019s disease","volume":"190","author":"Westin","year":"2010","journal-title":"J. Neurosci. Methods"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.jneumeth.2004.10.005","article-title":"Quantifying drug-induced dyskinesia in the arms using digitized spiral-drawing tasks","volume":"144","author":"Liu","year":"2005","journal-title":"J. Neurosci. Methods"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"868","DOI":"10.1136\/jnnp.56.8.868","article-title":"Assesing tremor severity","volume":"56","author":"Bain","year":"1993","journal-title":"J. Neurol. Neurosur. Psychiatry"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2073","DOI":"10.1002\/mds.23808","article-title":"Validation of digital spiral analysis as outcome parameter for clinical trials in Essential Tremor","volume":"26","author":"Haubenberger","year":"2011","journal-title":"Mov. Disord."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e29","DOI":"10.1111\/j.1600-0404.2012.01689.x","article-title":"Interim analysis of long-term intraduodenal levodopa infusion in advanced Parkinson disease","volume":"126","author":"Dizdar","year":"2012","journal-title":"Acta Neurol. Scand."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.cmpb.2009.08.001","article-title":"A home environment test battery for status assessment in patients with advanced Parkinson\u2019s disease","volume":"98","author":"Westin","year":"2010","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_29","first-page":"S112","article-title":"A web-based system for visualizing upper limb motor performance of Parkinson\u2019s disease patients","volume":"28","author":"Memedi","year":"2013","journal-title":"Mov. Disord."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1073\/pnas.88.6.2297","article-title":"Approximate entropy as a measure of system complexity","volume":"88","author":"Pincus","year":"1991","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_31","unstructured":"Sadikov, A., Groznik, V., \u017dabkar, J., Mo\u017eina, M., Georgiev, D., Pirto\u0161ek, Z., and Bratko, I. (2014, January 17\u201322). ParkinsonCheck smartphone App. Proceedings of the European Conference on Artificial Intelligence, Prague, Czech Republic."},{"key":"ref_32","unstructured":"Sadikov, A., \u017dabkar, J., Mo\u017eina, M., Groznik, V., Georgiev, D., and Bratko, I. PARKINSONCHECK: A Decision Support System for Spirographic Testing. Available online: http:\/\/www.ailab.si\/parkinsoncheck\/pc-tr.pdf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution\u2014A simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"J. Glob. Optim."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","article-title":"The WEKA data mining software: An update","volume":"11","author":"Hall","year":"2009","journal-title":"SIGKDD Explor."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/j.parkreldis.2013.01.011","article-title":"Spiral drawing during self-rated dyskinesia is more impaired than during self-rated off","volume":"19","author":"Memedi","year":"2013","journal-title":"Parkinsonism Rel. Disord."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1002\/(SICI)1097-0258(19971030)16:20<2349::AID-SIM667>3.0.CO;2-E","article-title":"Tutorial in biostatistics: Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data","volume":"16","author":"Cnaan","year":"1997","journal-title":"Stat. Med."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1007\/s10072-011-0844-5","article-title":"Validation of a home environment test battery for assessments in advanced Parkinson\u2019s disease","volume":"33","author":"Westin","year":"2012","journal-title":"Neurol. Sci."},{"key":"ref_38","unstructured":"Available online: http:\/\/users.du.se\/~mmi\/brad\/brad.swf.html."},{"key":"ref_39","unstructured":"Available online: http:\/\/users.du.se\/~mmi\/dys\/dys_case.swf.html."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/9\/23727\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:43Z","timestamp":1760215723000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/9\/23727"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,17]]},"references-count":39,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["s150923727"],"URL":"https:\/\/doi.org\/10.3390\/s150923727","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,9,17]]}}}