{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:30:11Z","timestamp":1772253011365,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,26]],"date-time":"2021-11-26T00:00:00Z","timestamp":1637884800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001826","name":"Netherlands Organisation for Health Research and Development","doi-asserted-by":"publisher","award":["PTO2 446001063"],"award-info":[{"award-number":["PTO2 446001063"]}],"id":[{"id":"10.13039\/501100001826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009709","name":"Stichting De Weijerhorst","doi-asserted-by":"publisher","award":["UTAP"],"award-info":[{"award-number":["UTAP"]}],"id":[{"id":"10.13039\/501100009709","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Motor fluctuations in Parkinson\u2019s disease are characterized by unpredictability in the timing and duration of dopaminergic therapeutic benefits on symptoms, including bradykinesia and rigidity. These fluctuations significantly impair the quality of life of many Parkinson\u2019s patients. However, current clinical evaluation tools are not designed for the continuous, naturalistic (real-world) symptom monitoring needed to optimize clinical therapy to treat fluctuations. Although commercially available wearable motor monitoring, used over multiple days, can augment neurological decision making, the feasibility of rapid and dynamic detection of motor fluctuations is unclear. So far, applied wearable monitoring algorithms are trained on group data. In this study, we investigated the influence of individual model training on short timescale classification of naturalistic bradykinesia fluctuations in Parkinson\u2019s patients using a single-wrist accelerometer. As part of the Parkinson@Home study protocol, 20 Parkinson patients were recorded with bilateral wrist accelerometers for a one hour OFF medication session and a one hour ON medication session during unconstrained activities in their own homes. Kinematic metrics were extracted from the accelerometer data from the bodyside with the largest unilateral bradykinesia fluctuations across medication states. The kinematic accelerometer features were compared over the 1 h duration of recording, and medication-state classification analyses were performed on 1 min segments of data. Then, we analyzed the influence of individual versus group model training, data window length, and total number of training patients included in group model training, on classification. Statistically significant areas under the curves (AUCs) for medication induced bradykinesia fluctuation classification were seen in 85% of the Parkinson patients at the single minute timescale using the group models. Individually trained models performed at the same level as the group trained models (mean AUC both 0.70, standard deviation respectively 0.18 and 0.10) despite the small individual training dataset. AUCs of the group models improved as the length of the feature windows was increased to 300 s, and with additional training patient datasets. We were able to show that medication-induced fluctuations in bradykinesia can be classified using wrist-worn accelerometry at the time scale of a single minute. Rapid, naturalistic Parkinson motor monitoring has the clinical potential to evaluate dynamic symptomatic and therapeutic fluctuations and help tailor treatments on a fast timescale.<\/jats:p>","DOI":"10.3390\/s21237876","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"7876","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Rapid Dynamic Naturalistic Monitoring of Bradykinesia in Parkinson\u2019s Disease Using a Wrist-Worn Accelerometer"],"prefix":"10.3390","volume":"21","author":[{"given":"Jeroen G. V.","family":"Habets","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, School of Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands"}]},{"given":"Christian","family":"Herff","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, School of Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands"}]},{"given":"Pieter L.","family":"Kubben","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, School of Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands"}]},{"given":"Mark L.","family":"Kuijf","sequence":"additional","affiliation":[{"name":"Department of Neurology, School of Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands"}]},{"given":"Yasin","family":"Temel","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, School of Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8241-5087","authenticated-orcid":false,"given":"Luc J. W.","family":"Evers","sequence":"additional","affiliation":[{"name":"Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GC Nijmegen, The Netherlands"}]},{"given":"Bastiaan R.","family":"Bloem","sequence":"additional","affiliation":[{"name":"Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GC Nijmegen, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2733-4003","authenticated-orcid":false,"given":"Philip A.","family":"Starr","sequence":"additional","affiliation":[{"name":"Department of Movement Disorders and Neuromodulation, University of California San Francisco, San Francisco, CA 94143, USA"}]},{"given":"Ro\u2019ee","family":"Gilron","sequence":"additional","affiliation":[{"name":"Department of Movement Disorders and Neuromodulation, University of California San Francisco, San Francisco, CA 94143, USA"}]},{"given":"Simon","family":"Little","sequence":"additional","affiliation":[{"name":"Department of Movement Disorders and Neuromodulation, University of California San Francisco, San Francisco, CA 94143, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","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 Lond. Engl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1136\/jnnp-2019-322338","article-title":"Parkinson\u2019s Disease: Etiopathogenesis and Treatment","volume":"91","author":"Jankovic","year":"2020","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.parkreldis.2019.05.009","article-title":"Predictors of Health-Related Quality of Life in Parkinson\u2019s Disease","volume":"65","author":"Kuhlman","year":"2019","journal-title":"Park. Relat. Disord."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/S1474-4422(20)30036-3","article-title":"Initiation of Pharmacological Therapy in Parkinson\u2019s Disease: When, Why, and How","volume":"19","author":"Clarke","year":"2020","journal-title":"Lancet Neurol."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Fasano, A., Fung, V.S.C., Lopiano, L., Elibol, B., Smolentseva, I.G., Seppi, K., Tak\u00e1ts, A., Onuk, K., Parra, J.C., and Bergmann, L. (2019). Characterizing Advanced Parkinson\u2019s Disease: OBSERVE-PD Observational Study Results of 2615 Patients. BMC Neurol., 19.","DOI":"10.1186\/s12883-019-1276-8"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1002\/mds.27882","article-title":"Motor Complications in Parkinson\u2019s Disease: 13-Year Follow-up of the CamPaIGN Cohort","volume":"35","author":"Kim","year":"2020","journal-title":"Mov. Disord."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1016\/j.parkreldis.2014.06.001","article-title":"Quality of Life in Parkinson\u2019s Disease Patients with Motor Fluctuations and Dyskinesias in Five European Countries","volume":"20","author":"Hechtner","year":"2014","journal-title":"Park. Relat. Disord."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1248","DOI":"10.1002\/mds.27372","article-title":"International Parkinson and Movement Disorder Society Evidence-Based Medicine Review: Update on Treatments for the Motor Symptoms of Parkinson\u2019s Disease","volume":"33","author":"Fox","year":"2018","journal-title":"Mov. Disord."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1136\/jnnp.54.11.976","article-title":"A New Approach in the Assessment of Motor Activity in Parkinson\u2019s Disease","volume":"54","author":"Middelkoop","year":"1991","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1002\/mds.27671","article-title":"A Roadmap for Implementation of Patient-Centered Digital Outcome Measures in Parkinson\u2019s Disease Obtained Using Mobile Health Technologies","volume":"34","author":"Espay","year":"2019","journal-title":"Mov. Disord."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/S1474-4422(19)30397-7","article-title":"Long-Term Unsupervised Mobility Assessment in Movement Disorders","volume":"19","author":"Warmerdam","year":"2020","journal-title":"Lancet Neurol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/S1474-4422(20)30033-8","article-title":"Wearable-Based Mobility Monitoring: The Long Road Ahead","volume":"19","author":"Fasano","year":"2020","journal-title":"Lancet Neurol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1038\/s41531-018-0051-7","article-title":"Viewpoint and Practical Recommendations from a Movement Disorder Specialist Panel on Objective Measurement in the Clinical Management of Parkinson\u2019s Disease","volume":"4","author":"Odin","year":"2018","journal-title":"NPJ Park. Dis."},{"key":"ref_14","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_15","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1136\/jnnp.2006.111161","article-title":"The 39 Item Parkinson\u2019s Disease Questionnaire (PDQ-39) Revisited: Implications for Evidence Based Medicine","volume":"78","author":"Hagell","year":"2007","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1001\/archneur.63.12.1756","article-title":"Factors Associated with the Development of Motor Fluctuations and Dyskinesias in Parkinson Disease","volume":"63","author":"Hauser","year":"2006","journal-title":"Arch. Neurol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1111\/j.1755-5949.2011.00253.x","article-title":"Patient Diaries as a Clinical Endpoint in Parkinson\u2019s Disease Clinical Trials","volume":"18","author":"Papapetropoulos","year":"2012","journal-title":"CNS Neurosci. Ther."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1036","DOI":"10.3389\/fneur.2018.01036","article-title":"Monitoring Motor Symptoms During Activities of Daily Living in Individuals With Parkinson\u2019s Disease","volume":"9","author":"Thorp","year":"2018","journal-title":"Front Neurol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Horne, M.K., McGregor, S., and Bergquist, F. (2015). An Objective Fluctuation Score for Parkinson\u2019s Disease. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0124522"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.compbiomed.2017.03.020","article-title":"Estimating Bradykinesia Severity in Parkinson\u2019s Disease by Analysing Gait through a Waist-Worn Sensor","volume":"84","author":"Sama","year":"2017","journal-title":"Comput. Biol. Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"eabd7865","DOI":"10.1126\/scitranslmed.abd7865","article-title":"Smartwatch Inertial Sensors Continuously Monitor Real-World Motor Fluctuations in Parkinson\u2019s Disease","volume":"13","author":"Powers","year":"2021","journal-title":"Sci. Transl. Med."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Sica, M., Tedesco, S., Crowe, C., Kenny, L., Moore, K., Timmons, S., Barton, J., O\u2019Flynn, B., and Komaris, D.-S. (2021). Continuous Home Monitoring of Parkinson\u2019s Disease Using Inertial Sensors: A Systematic Review. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0246528"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1080\/14737175.2018.1503948","article-title":"Role of the Personal KinetiGraph in the Routine Clinical Assessment of Parkinson\u2019s Disease: Recommendations from an Expert Panel","volume":"18","author":"Pahwa","year":"2018","journal-title":"Expert Rev. Neurother."},{"key":"ref_24","first-page":"207","article-title":"Qualitative Evaluation of the Personal KinetiGraph TM Movement Recording System in a Parkinson\u2019s Clinic","volume":"9","author":"Santiago","year":"2019","journal-title":"J. Park. Dis."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.3389\/fneur.2019.01027","article-title":"PKG Movement Recording System Use Shows Promise in Routine Clinical Care of Patients with Parkinson\u2019s Disease","volume":"10","author":"Joshi","year":"2019","journal-title":"Front. Neurol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"914","DOI":"10.1007\/s00415-020-10222-w","article-title":"Assessment of Wearing Off in Parkinson\u2019s Disease Using Objective Measurement","volume":"268","author":"Farzanehfar","year":"2020","journal-title":"J. Neurol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Ossig, C., Gandor, F., Fauser, M., Bosredon, C., Churilov, L., Reichmann, H., Horne, M.K., Ebersbach, G., and Storch, A. (2016). Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0161559"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"e9","DOI":"10.2196\/mhealth.3321","article-title":"Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson\u2019s Disease","volume":"3","author":"Sama","year":"2015","journal-title":"JMIR Mhealth Uhealth"},{"key":"ref_29","unstructured":"Rodriguez-Molinero, A. (2021, May 03). Monitoring of Mobility of Parkinson\u2019s Patients for Therapeutic Purposes\u2014Clinical Trial (MoMoPa-EC), Available online: https:\/\/clinicialtrials.gov\/ct2\/show\/NCT04176302."},{"key":"ref_30","unstructured":"(2021, May 03). Great Lake Technologies Kinesia 360 Parkinson\u2019s Monitoring Study 2018, Available online: https:\/\/clinicialtrials.gov\/ct2\/show\/NCT02657655."},{"key":"ref_31","first-page":"S11","article-title":"Personalized Care Management for Persons with Parkinson\u2019s Disease","volume":"10","author":"Munneke","year":"2020","journal-title":"J. Park. Dis."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s12938-021-00872-w","article-title":"Ensemble Deep Model for Continuous Estimation of Unified Parkinson\u2019s Disease Rating Scale III","volume":"20","author":"Hssayeni","year":"2021","journal-title":"Biomed. Eng. Online"},{"key":"ref_33","unstructured":"Clarke, C.E., Patel, S., Ives, N., Rick, C.E., Woolley, R., Wheatley, K., Walker, M.F., Zhu, S., Kandiyali, R., and Yao, G. (2021, May 03). UK Parkinson\u2019s Disease Society Brain Bank Diagnostic Criteria, Available online: www.ncbi.nlm.nih.gov\/books\/NBK37."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s12984-020-00684-4","article-title":"Role of Data Measurement Characteristics in the Accurate Detection of Parkinson\u2019s Disease Symptoms Using Wearable Sensors","volume":"17","author":"Shawen","year":"2020","journal-title":"J. NeuroEng. Rehabil."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1038\/s41746-018-0071-z","article-title":"Wearable Sensors for Parkinson\u2019s Disease: Which Data Are Worth Collecting for Training Symptom Detection Models","volume":"1","author":"Lonini","year":"2018","journal-title":"Npj Digit. Med."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.parkreldis.2016.09.009","article-title":"Unsupervised Home Monitoring of Parkinson\u2019s Disease Motor Symptoms Using Body-Worn Accelerometers","volume":"33","author":"Fisher","year":"2016","journal-title":"Park. Relat. Disord."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e19068","DOI":"10.2196\/19068","article-title":"Real-Life Gait Performance as a Digital Biomarker for Motor Fluctuations: The Parkinson@Home Validation Study","volume":"22","author":"Evers","year":"2020","journal-title":"J Med. Internet Res."},{"key":"ref_38","first-page":"e5990","article-title":"Large-Scale Wearable Sensor Deployment in Parkinson\u2019s Patients: The Parkinson@Home Study Protocol","volume":"5","author":"Hahn","year":"2016","journal-title":"JMIR Res. Protoc."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"De Lima, A.L.S., Hahn, T., Evers, L.J.W., de Vries, N.M., Cohen, E., Afek, M., Bataille, L., Daeschler, M., Claes, K., and Boroojerdi, B. (2017). Feasibility of Large-Scale Deployment of Multiple Wearable Sensors in Parkinson\u2019s Disease. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0189161"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1137\/070690274","article-title":"Trend Filtering","volume":"51","author":"Kim","year":"2009","journal-title":"SIAM Rev."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s40734-020-00086-7","article-title":"Quantification of Tremor Using Consumer Product Accelerometry Is Feasible in Patients with Essential Tremor and Parkinson\u2019s Disease: A Comparative Study","volume":"7","author":"Ziagkos","year":"2020","journal-title":"J. Clin. Mov. Disord."},{"key":"ref_42","first-page":"2825","article-title":"Scikit-Learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1038\/s41746-019-0217-7","article-title":"Development of Digital Biomarkers for Resting Tremor and Bradykinesia Using a Wrist-Worn Wearable Device","volume":"3","author":"Mahadevan","year":"2020","journal-title":"NPJ Digit. Med."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1002\/mds.20633","article-title":"Ambulatory Motor Assessment in Parkinson\u2019s Disease","volume":"21","author":"Keijsers","year":"2006","journal-title":"Mov. Disord."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1186\/s13059-019-1716-1","article-title":"A Practical Guide to Methods Controlling False Discoveries in Computational Biology","volume":"20","author":"Korthauer","year":"2019","journal-title":"Genome Biol."},{"key":"ref_46","unstructured":"(2021, May 03). Jgvhabets\/Brady_reallife: First Release for Short-Term, Individual and Group Modelling Analyses|Zenodo. Available online: https:\/\/zenodo.org\/record\/4734199#.YJAOZRQza3J."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Khodakarami, H., Ricciardi, L., Contarino, M.F., Pahwa, R., Lyons, K.E., Geraedts, V.J., Morgante, F., Leake, A., Paviour, D., and De Angelis, A. (2019). Prediction of the Levodopa Challenge Test in Parkinson\u2019s Disease Using Data from a Wrist-Worn Sensor. Sensors, 19.","DOI":"10.3390\/s19235153"},{"key":"ref_48","unstructured":"Vibhash, D.S., Safarpour, D., Mehta, S.H., Vanegas-Arroyave, N., Weiss, D., Cooney, J.W., Mari, Z., and Fasano, A. (2021). Telemedicine and Deep Brain Stimulation\u2014Current Practices and Recommendations. Park. Relat. Disord."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1097\/WCO.0000000000000953","article-title":"The State of Telemedicine for Persons with Parkinson\u2019s Disease","volume":"34","author":"Bloem","year":"2021","journal-title":"Curr. Opin. Neurol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"868","DOI":"10.1016\/j.brs.2019.02.020","article-title":"Dual Threshold Neural Closed Loop Deep Brain Stimulation in Parkinson Disease Patients","volume":"12","author":"Velisar","year":"2019","journal-title":"Brain Stimulat."},{"key":"ref_51","first-page":"421","article-title":"A Pilot Study on Data-Driven Adaptive Deep Brain Stimulation in Chronically Implanted Essential Tremor Patients","volume":"14","author":"Ferleger","year":"2020","journal-title":"Front. Hum. Neurosci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1078","DOI":"10.1038\/s41587-021-00897-5","article-title":"Long-Term Wireless Streaming of Neural Recordings for Circuit Discovery and Adaptive Stimulation in Individuals with Parkinson\u2019s Disease","volume":"39","author":"Gilron","year":"2021","journal-title":"Nat. Biotechnol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1834","DOI":"10.1002\/mds.115","article-title":"An Update on Adaptive Deep Brain Stimulation in Parkinson\u2019s Disease","volume":"33","author":"Habets","year":"2018","journal-title":"Mov. Disord."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1159\/000512513","article-title":"A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach","volume":"4","author":"Rochester","year":"2020","journal-title":"Digit. Biomark."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Kluge, F., Del Din, S., Cereatti, A., Ga\u00dfner, H., Hansen, C., Helbostadt, J.L., Klucken, J., K\u00fcderle, A., M\u00fcller, A., and Rochester, L. (2020). Consensus Based Framework for Digital Mobility Monitoring. medRxiv.","DOI":"10.1101\/2020.12.18.20248404"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1038\/s41531-019-0093-5","article-title":"Monitoring Parkinson\u2019s Disease Symptoms during Daily Life: A Feasibility Study","volume":"5","author":"Heijmans","year":"2019","journal-title":"NPJ Park. Dis."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Vizcarra, J.A., Sanchez-Ferro, A., Maetzler, W., Marsili, L., Zavala, L., Lang, A.E., Martinez-Martin, P., Mestre, T.A., Reilmann, R., and Hausdorff, J.M. (2019). The Parkinson\u2019s Disease e-Diary: Developing a Clinical and Research Tool for the Digital Age. Mov. Disord.","DOI":"10.1002\/mds.27673"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"e15628","DOI":"10.2196\/15628","article-title":"Mobile Health Daily Life Monitoring for Parkinson Disease: Development and Validation of Ecological Momentary Assessments","volume":"8","author":"Habets","year":"2020","journal-title":"JMIR Mhealth Uhealth"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Habets, J.G.V., Heijmans, M., Leentjens, A.F.G., Simons, C.J.P., Temel, Y., Kuijf, M.L., Kubben, P.L., and Herff, C. (2021). A Long-Term, Real-Life Parkinson Monitoring Database Combining Unscripted Objective and Subjective Recordings. Data, 6.","DOI":"10.3390\/data6020022"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Bourke, A.K., Ihlen, E.A.F., Bergquist, R., Wik, P.B., Vereijken, B., and Helbostad, J.L. (2017). A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology-The ADAPT Study Data-Set. Sensors, 17.","DOI":"10.3390\/s17030559"},{"key":"ref_61","first-page":"5534282","article-title":"Use of a Smartphone to Gather Parkinson\u2019s Disease Neurological Vital Signs during the COVID-19 Pandemic","volume":"2021","author":"Alberts","year":"2021","journal-title":"Park. Dis."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Bloem, B.R., Marks, W.J., Silva de Lima, A.L., Kuijf, M.L., van Laar, T., Jacobs, B.P.F., Verbeek, M.M., Helmich, R.C., van de Warrenburg, B.P., and Evers, L.J.W. (2019). The Personalized Parkinson Project: Examining Disease Progression through Broad Biomarkers in Early Parkinson\u2019s Disease. BMC Neurol., 19.","DOI":"10.1186\/s12883-019-1394-3"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Watts, J., Khojandi, A., Vasudevan, R., and Ramdhani, R. (2020, January 20\u201324). Optimizing Individualized Treatment Planning for Parkinson\u2019s Disease Using Deep Reinforcement Learning. Proceedings of the 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Montr\u00e9al, QC, Canada.","DOI":"10.1109\/EMBC44109.2020.9175311"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"677","DOI":"10.3389\/fneur.2017.00677","article-title":"A Perspective on Wearable Sensor Measurements and Data Science for Parkinson\u2019s Disease","volume":"8","author":"Matias","year":"2017","journal-title":"Front. Neurol."},{"key":"ref_65","unstructured":"MJFF, S. (2021, May 03). BEAT-PD DREAM Challenge (by Sage Bionetworks; Michael J. Fox Foundation). Available online: https:\/\/synapse.org\/#!synapse:syn20825169\/wiki\/600904."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1109\/TBME.2017.2697764","article-title":"Continuous Assessment of Levodopa Response in Parkinson\u2019s Disease Using Wearable Motion Sensors","volume":"65","author":"Pulliam","year":"2018","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"6410","DOI":"10.1109\/JSEN.2019.2910105","article-title":"Monitoring Insole (MONI): A Low Power Solution Toward Daily Gait Monitoring and Analysis","volume":"19","author":"Hua","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Daneault, J., Lee, S.I., Golabchi, F.N., Patel, S., Shih, L.C., Paganoni, S., and Bonato, P. (2017, January 17\u201319). Estimating Bradykinesia in Parkinson\u2019s Disease with a Minimum Number of Wearable Sensors. Proceedings of the 2017 IEEE\/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Philadelphia, PA, USA.","DOI":"10.1109\/CHASE.2017.94"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1038\/s41597-021-00830-0","article-title":"Accelerometer Data Collected with a Minimum Set of Wearable Sensors from Subjects with Parkinson\u2019s Disease","volume":"8","author":"Daneault","year":"2021","journal-title":"Sci. Data"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/7876\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:36:21Z","timestamp":1760168181000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/7876"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,26]]},"references-count":69,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["s21237876"],"URL":"https:\/\/doi.org\/10.3390\/s21237876","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.09.03.458142","asserted-by":"object"}]},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,26]]}}}