{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T17:33:48Z","timestamp":1782408828639,"version":"3.54.5"},"reference-count":39,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["THC"],"published-print":{"date-parts":[[2022,7,8]]},"abstract":"<jats:p>BACKGROUND: Resting tremor is an essential characteristic in patients suffering from Parkinson\u2019s disease (PD). OBJECTIVE: Quantification and monitoring of tremor severity is clinically important to help achieve medication or rehabilitation guidance in daily monitoring. METHODS: Wrist-worn tri-axial accelerometers were utilized to record the long-term acceleration signals of PD patients with different tremor severities rated by Unified Parkinson\u2019s Disease Rating Scale (UPDRS). Based on the extracted features, three kinds of classifiers were used to identify different tremor severities. Statistical tests were further designed for the feature analysis. RESULTS: The support vector machine (SVM) achieved the best performance with an overall accuracy of 94.84%. Additional feature analysis indicated the validity of the proposed feature combination and revealed the importance of different features in differentiating tremor severities. CONCLUSION: The present work obtains a high-accuracy classification in tremor severity, which is expected to play a crucial role in PD treatment and symptom monitoring in real life.<\/jats:p>","DOI":"10.3233\/thc-213205","type":"journal-article","created":{"date-parts":[[2021,10,15]],"date-time":"2021-10-15T19:05:31Z","timestamp":1634324731000},"page":"895-907","source":"Crossref","is-referenced-by-count":11,"title":["Comprehensive analysis of resting tremor based on acceleration signals of patients with Parkinson\u2019s disease"],"prefix":"10.1177","volume":"30","author":[{"given":"Sen","family":"Liu","sequence":"first","affiliation":[{"name":"Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"},{"name":"Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Yuan","sequence":"additional","affiliation":[{"name":"Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"},{"name":"Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiali","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Shenzhen Second People\u2019s Hospital, the First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China"},{"name":"Shenzhen University School of Medicine, Shenzhen, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Shenzhen Second People\u2019s Hospital, the First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China"},{"name":"Shenzhen University School of Medicine, Shenzhen, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cuiwei","family":"Yang","sequence":"additional","affiliation":[{"name":"Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"},{"name":"Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai Engineering Research Center of Assistive Devices, Shanghai, China"},{"name":"Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Shenzhen Second People\u2019s Hospital, the First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China"},{"name":"Shenzhen University School of Medicine, Shenzhen, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"issue":"8","key":"10.3233\/THC-213205_ref1","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1136\/jnnp-2019-322676","article-title":"Systematic clinical approach for diagnosing upper limb tremor","volume":"91","author":"van de Wardt","year":"2020","journal-title":"J Neurol Neurosurg Psychiatry."},{"issue":"13","key":"10.3233\/THC-213205_ref2","doi-asserted-by":"publisher","first-page":"1583","DOI":"10.1002\/mds.25945","article-title":"The prevalence of Parkinson\u2019s disease: a systematic review and meta-analysis","volume":"29","author":"Pringsheim","year":"2014","journal-title":"Mov Disord."},{"issue":"2","key":"10.3233\/THC-213205_ref3","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1097\/00004691-199603000-00002","article-title":"Clinical neurophysiology of tremor","volume":"13","author":"Deuschl","year":"1996","journal-title":"J Clin Neurophysiol."},{"key":"10.3233\/THC-213205_ref5","unstructured":"Fahn S. Unified Parkinson\u2019s Disease Rating Scale, In: S. Fahn, C.D. Marsden, D.B. Calne and M. Goldstein, Recent Developments in Parkinson\u2019s Disease. Macmillan Health Care Information. 1987; 2: 153-163."},{"key":"10.3233\/THC-213205_ref6","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.artmed.2018.04.010","article-title":"Symptoms and medications change patterns for Parkinson\u2019s disease patients stratification","volume":"91","author":"Valmarska","year":"2018","journal-title":"Artif Intell Med."},{"issue":"3","key":"10.3233\/THC-213205_ref7","doi-asserted-by":"publisher","first-page":"036019","DOI":"10.1088\/1741-2560\/10\/3\/036019","article-title":"Pathological tremor prediction using surface electromyogram and acceleration: potential use in \u2018ON-OFF\u2019 demand driven deep brain stimulator design","volume":"10","author":"Basu","year":"2013","journal-title":"J Neural Eng."},{"key":"10.3233\/THC-213205_ref8","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2015.7318662"},{"issue":"1","key":"10.3233\/THC-213205_ref9","doi-asserted-by":"publisher","first-page":"468","DOI":"10.1016\/j.bbe.2020.01.009","article-title":"Pose and Optical Flow Fusion (POFF) for accurate tremor detection and quantification","volume":"40","author":"Alper","year":"2020","journal-title":"Biocybern Biomed Eng"},{"key":"10.3233\/THC-213205_ref10","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1007\/978-3-030-04491-6_26","article-title":"Tremor Signal Analysis for Parkinson\u2019s Disease Detection Using Leap Motion Device","author":"Vivar-Estudillo","year":"2018","journal-title":"Lect. Notes Comput. Sci."},{"issue":"1","key":"10.3233\/THC-213205_ref11","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.bbe.2019.05.006","article-title":"Automated detection of Parkinson\u2019s disease using minimum average maximum tree and singular value decomposition method with vowels","volume":"40","author":"Tuncer","year":"2020","journal-title":"Biocybern Biomed Eng"},{"issue":"4","key":"10.3233\/THC-213205_ref12","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."},{"issue":"5","key":"10.3233\/THC-213205_ref13","doi-asserted-by":"publisher","first-page":"1264","DOI":"10.1109\/TBME.2012.2183367","article-title":"Novel speech signal processing algorithms for high-accuracy classification of Parkinson\u2019s disease","volume":"59","author":"Tsanas","year":"2012","journal-title":"IEEE Trans Biomed Eng."},{"issue":"1","key":"10.3233\/THC-213205_ref14","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":"2020","journal-title":"Biocybern Biomed Eng"},{"issue":"5","key":"10.3233\/THC-213205_ref15","doi-asserted-by":"publisher","first-page":"205","DOI":"10.4236\/nm.2014.55024","article-title":"Understanding tremor in rapid upper limb movements using 3d accelerometers data","volume":"5","author":"Pascoal-Faria","year":"2014","journal-title":"Neurosci Med"},{"issue":"4","key":"10.3233\/THC-213205_ref16","doi-asserted-by":"publisher","first-page":"046019","DOI":"10.1088\/1741-2560\/12\/4\/046019","article-title":"One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor","volume":"12","author":"Dideriksen","year":"2015","journal-title":"J Neural Eng."},{"issue":"10","key":"10.3233\/THC-213205_ref17","doi-asserted-by":"publisher","first-page":"2423","DOI":"10.1007\/s10439-017-1881-x","article-title":"Quantification of Hand Motor Symptoms in Parkinson\u2019s Disease: A Proof-of-Principle Study Using Inertial and Force Sensors","volume":"45","author":"van den Noort","year":"2017","journal-title":"Ann Biomed Eng."},{"issue":"10","key":"10.3233\/THC-213205_ref18","doi-asserted-by":"publisher","first-page":"25055","DOI":"10.3390\/s151025055","article-title":"Quantitative Assessment of Parkinsonian Tremor Based on an Inertial Measurement Unit","volume":"15","author":"Dai","year":"2015","journal-title":"Sensors (Basel)."},{"issue":"5","key":"10.3233\/THC-213205_ref19","doi-asserted-by":"publisher","first-page":"461","DOI":"10.3233\/THC-191947","article-title":"Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals","volume":"28","author":"Hossen","year":"2020","journal-title":"Technol Health Care."},{"issue":"3","key":"10.3233\/THC-213205_ref20","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1088\/0967-3334\/33\/3\/395","article-title":"Linear and nonlinear tremor acceleration characteristics in patients with Parkinson\u2019s disease","volume":"33","author":"Meigal","year":"2012","journal-title":"Physiol Meas."},{"issue":"9","key":"10.3233\/THC-213205_ref21","doi-asserted-by":"publisher","first-page":"1516","DOI":"10.1088\/0967-3334\/37\/9\/1516","article-title":"Clinical validation of a precision electromagnetic tremor measurement system in participants receiving deep brain stimulation for essential tremor","volume":"37","author":"Perera","year":"2016","journal-title":"Physiol Meas."},{"key":"10.3233\/THC-213205_ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2014.09.006"},{"key":"10.3233\/THC-213205_ref23","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1016\/j.ijmedinf.2018.03.002","article-title":"Rest tremor quantification based on fuzzy inference systems and wearable sensors","volume":"114","author":"Sanchez-Perez","year":"2018","journal-title":"Int J Med Inform."},{"key":"10.3233\/THC-213205_ref24","doi-asserted-by":"publisher","first-page":"357","DOI":"10.3389\/fnhum.2012.00357","article-title":"Using a smart phone as a standalone platform for detection and monitoring of pathological tremors","volume":"6","author":"Daneault","year":"2013","journal-title":"Front Hum Neurosci."},{"key":"10.3233\/THC-213205_ref25","doi-asserted-by":"publisher","first-page":"103477","DOI":"10.1016\/j.compbiomed.2019.103477","article-title":"Bag of Samplings for computer-assisted Parkinson\u2019s disease diagnosis based on Recurrent Neural Networks","volume":"115","author":"Ribeiro","year":"2019","journal-title":"Comput Biol Med."},{"key":"10.3233\/THC-213205_ref26","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.artmed.2018.04.001","article-title":"Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson\u2019s disease identification","volume":"87","author":"Pereira","year":"2018","journal-title":"Artif Intell Med."},{"key":"10.3233\/THC-213205_ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2019.101683"},{"issue":"1","key":"10.3233\/THC-213205_ref28","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1186\/s12984-019-0534-8","article-title":"The influence of posture duration on hand tremor during tasks with attention-distraction in persons with Parkinson\u2019s disease","volume":"16","author":"Malling","year":"2019","journal-title":"J Neuroeng Rehabil."},{"issue":"11","key":"10.3233\/THC-213205_ref29","doi-asserted-by":"publisher","first-page":"1980","DOI":"10.1088\/1361-6579\/aa8e1f","article-title":"High-accuracy automatic classification of Parkinsonian tremor severity using machine learning method","volume":"38","author":"Jeon","year":"2017","journal-title":"Physiol Meas."},{"issue":"1","key":"10.3233\/THC-213205_ref30","first-page":"12","article-title":"Assessment of rest tremor in Parkinson\u2019s disease","volume":"42","author":"Budzianowska","year":"2008","journal-title":"Neurol Neurochir Pol."},{"key":"10.3233\/THC-213205_ref31","doi-asserted-by":"publisher","first-page":"2660","DOI":"10.1093\/brain\/awl190","article-title":"Tremor amplitude is logarithmically related to 4- and 5-point tremor rating scales","volume":"129","author":"Elble","year":"2006","journal-title":"Brain."},{"issue":"12","key":"10.3233\/THC-213205_ref32","doi-asserted-by":"publisher","first-page":"1938","DOI":"10.1002\/mds.23201","article-title":"Correlation between Kinesia system assessments and clinical tremor scores in patients with essential tremor","volume":"25","author":"Mostile","year":"2010","journal-title":"Mov Disord."},{"key":"10.3233\/THC-213205_ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2018.01.008"},{"issue":"3","key":"10.3233\/THC-213205_ref34","doi-asserted-by":"publisher","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."},{"issue":"6","key":"10.3233\/THC-213205_ref35","doi-asserted-by":"publisher","first-page":"H2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am J Physiol Heart Circ Physiol."},{"issue":"12","key":"10.3233\/THC-213205_ref36","doi-asserted-by":"publisher","first-page":"125702","DOI":"10.1088\/0957-0233\/27\/12\/125702","article-title":"Evaluating machine learning algorithms estimating tremor severity ratings on the Bain-Findley scale","volume":"27","author":"Yohanandan","year":"2016","journal-title":"Meas Sci Technol."},{"key":"10.3233\/THC-213205_ref37","doi-asserted-by":"crossref","unstructured":"Cramer JS. The origins of logistic regression. 2002.","DOI":"10.2139\/ssrn.360300"},{"key":"10.3233\/THC-213205_ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"10.3233\/THC-213205_ref39","doi-asserted-by":"publisher","DOI":"10.1109\/BIOCAS.2018.8584721"},{"key":"10.3233\/THC-213205_ref40","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"}],"container-title":["Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/THC-213205","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:53:47Z","timestamp":1777614827000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/THC-213205"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,8]]},"references-count":39,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/thc-213205","relation":{},"ISSN":["0928-7329","1878-7401"],"issn-type":[{"value":"0928-7329","type":"print"},{"value":"1878-7401","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,8]]}}}