{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T16:25:55Z","timestamp":1784132755935,"version":"3.55.0"},"reference-count":32,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2020,8,4]],"date-time":"2020-08-04T00:00:00Z","timestamp":1596499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007637","name":"Departamento Administrativo de Ciencia, Tecnolog\u00eda e Innovaci\u00f3n (COLCIENCIAS)","doi-asserted-by":"publisher","award":["845-2017"],"award-info":[{"award-number":["845-2017"]}],"id":[{"id":"10.13039\/100007637","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In patients with Parkinson\u2019s disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorporates triaxial accelerometers. The aim of this work is to develop a low-cost, assistive diagnostic tool for use in quantifying the arm swing kinematics of patients with PD. Ten patients with PD and 11 age-matched, healthy subjects are included in the study. Four feature extraction techniques were applied: (i) Asymmetry estimation based on root mean square (RMS) differences between arm movements; (ii) posterior\u2013anterior phase and cycle regularity through autocorrelation; (iii) tremor energy, established using Fourier transform analysis; and (iv) signal complexity through the fractal dimension by wavelet analysis. The PD group showed significant (p &lt; 0.05) reductions in arm swing RMS values, higher arm swing asymmetry, higher anterior\u2013posterior phase regularities, greater \u201chigh energy frequency\u201d signals, and higher complexity in their XZ plane signals. Therefore, the novel, portable system provides a reliable means to support clinical practice in PD assessment.<\/jats:p>","DOI":"10.3390\/s20154339","type":"journal-article","created":{"date-parts":[[2020,8,4]],"date-time":"2020-08-04T05:56:46Z","timestamp":1596520606000},"page":"4339","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson\u2019s Disease"],"prefix":"10.3390","volume":"20","author":[{"given":"Domiciano","family":"Rinc\u00f3n","sequence":"first","affiliation":[{"name":"12t Research Group, Universidad Icesi, Cali 760031, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8016-4050","authenticated-orcid":false,"given":"Jaime","family":"Valderrama","sequence":"additional","affiliation":[{"name":"Centro de Investigaciones Cl\u00ednicas (CIC), Fundaci\u00f3n Valle del Lili, Cali 760032, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1061-4164","authenticated-orcid":false,"given":"Maria Camila","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Centro de Investigaciones Cl\u00ednicas (CIC), Fundaci\u00f3n Valle del Lili, Cali 760032, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8688-7172","authenticated-orcid":false,"given":"Beatriz","family":"Mu\u00f1oz","sequence":"additional","affiliation":[{"name":"Department of Clinical Neurophsicology, Fundaci\u00f3n Valle del Lili, Cali 760032, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jorge","family":"Orozco","sequence":"additional","affiliation":[{"name":"Department of Clinical Neurophsicology, Fundaci\u00f3n Valle del Lili, Cali 760032, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linda","family":"Montilla","sequence":"additional","affiliation":[{"name":"12t Research Group, Universidad Icesi, Cali 760031, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yor","family":"Casta\u00f1o","sequence":"additional","affiliation":[{"name":"12t Research Group, Universidad Icesi, Cali 760031, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4154-2119","authenticated-orcid":false,"given":"Andr\u00e9s","family":"Navarro","sequence":"additional","affiliation":[{"name":"12t Research Group, Universidad Icesi, Cali 760031, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,4]]},"reference":[{"key":"ref_1","first-page":"389","article-title":"Parkinson\u2019s Disease","volume":"Volume 65","author":"Harris","year":"2012","journal-title":"Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1002\/mds.24973","article-title":"Motor signs in the prodromal phase of Parkinson\u2019s disease","volume":"27","author":"Maetzler","year":"2012","journal-title":"Mov. Disord."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.parkreldis.2004.06.003","article-title":"Measuring gait and gait-related activities in Parkinson\u2019s patients own home environment: A reliability, responsiveness and feasibility study","volume":"11","author":"Lim","year":"2005","journal-title":"Parkinsonism Relat. Disord."},{"key":"ref_4","first-page":"6139716","article-title":"Quantitative Analysis of Motor Status in Parkinson\u2019s Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications","volume":"2017","author":"Suzuki","year":"2017","journal-title":"Parkinson\u2019s Dis."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1109\/TNSRE.2007.908933","article-title":"Locomotor Function in the Early Stage of Parkinson\u2019s Disease","volume":"15","author":"Carpinella","year":"2007","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.gaitpost.2011.08.020","article-title":"Arm swing asymmetry in Parkinson\u2019s disease measured with ultrasound based motion analysis during treadmill gait","volume":"35","author":"Roggendorf","year":"2012","journal-title":"Gait Posture"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1109\/JBHI.2018.2865218","article-title":"IMU-Based Classification of Parkinson\u2019s Disease From Gait: A Sensitivity Analysis on Sensor Location and Feature Selection","volume":"22","author":"Caramia","year":"2018","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Dranca, L., de Mendarozketa, L.D.A.R., Gppo\u00f1i, A., Illarramendi, A., Gomez, I.N., Alvarado, M.D., and Rodr\u00edguez-Oroz, M.C. (2018). Using Kinect to classify Parkinson\u2019s disease stages related to severity of gait impairment. BMC Bioinform., 19, Available online: https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-018-2488-4.","DOI":"10.1186\/s12859-018-2488-4"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1392","DOI":"10.1249\/MSS.0b013e31819b3533","article-title":"A comparison of questionnaire, accelerometer, and pedometer: Measures in older people","volume":"41","author":"Harris","year":"2009","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1249\/mss.0b013e3804ec4e9","article-title":"Validity of the Actical Accelerometer Step-Count Function","volume":"39","author":"Esliger","year":"2007","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Brajdic, A., and Harle, R. (2013). Walk detection and step counting on unconstrained smartphones. The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing-Ubicomp \u201913, ACM Press. Available online: http:\/\/dl.acm.org\/citation.cfm?doid=2493432.2493449.","DOI":"10.1145\/2493432.2493449"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.gaitpost.2012.05.028","article-title":"Analysis of gait and balance through a single triaxial accelerometer in presymptomatic and symptomatic Huntington\u2019s disease","volume":"37","author":"Dalton","year":"2013","journal-title":"Gait Posture"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2747","DOI":"10.1016\/j.jbiomech.2009.08.008","article-title":"Novel approach to ambulatory assessment of human segmental orientation on a wearable sensor system","volume":"42","author":"Liu","year":"2009","journal-title":"J. Biomech."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.gaitpost.2011.10.180","article-title":"Both coordination and symmetry of arm swing are reduced in Parkinson\u2019s disease","volume":"35","author":"Huang","year":"2012","journal-title":"Gait Posture"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Erdem, N.S., Ersoy, C., and Tunca, C. (2019, January 8\u201311). Gait analysis using smartwatches. Proceedings of the 2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops), Istanbul, Turkey.","DOI":"10.1109\/PIMRCW.2019.8880821"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.gaitpost.2020.06.004","article-title":"Gait Event Detection using a Thigh-Worn Accelerometer","volume":"80","author":"Gurchiek","year":"2020","journal-title":"Gait Posture"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1049\/htl.2019.0015","article-title":"Comparison of gait speeds from wearable camera and accelerometer in structured and semi-structured environments","volume":"7","author":"Schneider","year":"2020","journal-title":"Healthc. Technol. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Leir\u00f3s-Rodr\u00edguez, R., Romo-P\u00e9rez, V., Garc\u00eda-Soid\u00e1n, J.L., and Soto-Rodr\u00edguez, A. (2020). Identification of Body Balance Deterioration of Gait in Women Using Accelerometers. Sustainability, 12.","DOI":"10.3390\/su12031222"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Rastegari, E., Azizian, S., and Ali, H. (2019, January 8\u201311). Machine learning and similarity network approaches to support automatic classification of parkinson\u2019s diseases using accelerometer-based gait analysis. Proceedings of the 52nd Hawaii International Conference on System Sciences, Grand Wailea, Maui, HI, USA.","DOI":"10.24251\/HICSS.2019.511"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Choi, S.-I., Moon, J., Park, H.-C., and Choi, S.T. (2019). User identification from gait analysis using multi-modal sensors in smart insole. Sensors, 19.","DOI":"10.3390\/s19173785"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.gaitpost.2019.10.039","article-title":"Wearable inertial sensors to measure gait and posture characteristic differences in older adult fallers and non-fallers: A scoping review","volume":"76","author":"Patel","year":"2020","journal-title":"Gait Posture"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"265","DOI":"10.23736\/S1973-9087.18.05306-6","article-title":"Inertial sensors versus standard systems in gait analysis: A systematic review and meta-analysis","volume":"55","author":"Petraglia","year":"2019","journal-title":"Eur. J. Phys. Rehabil. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1123\/jpah.2019-0088","article-title":"Application of Raw Accelerometer Data and Machine-Learning Techniques to Characterize Human Movement Behavior: A Systematic Scoping Review","volume":"17","author":"Narayanan","year":"2020","journal-title":"J. Phys. Act. Health"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1109\/TBME.2008.2006190","article-title":"A Comparison of Feature Extraction Methods for the Classification of Dynamic Activities from Accelerometer Data","volume":"56","author":"Preece","year":"2009","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"7314","DOI":"10.3390\/s110807314","article-title":"Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System","volume":"11","author":"Yang","year":"2011","journal-title":"Sensors"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/S0021-9290(03)00233-1","article-title":"Estimation of gait cycle characteristics by trunk accelerometry","volume":"37","author":"Helbostad","year":"2004","journal-title":"J. Biomech."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1109\/TNSRE.2002.802879","article-title":"Discrimination of walking patterns using wavelet-based fractal analysis","volume":"10","author":"Sekine","year":"2002","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.gaitpost.2009.10.013","article-title":"Arm swing magnitude and asymmetry during gait in the early stages of Parkinson\u2019s disease","volume":"31","author":"Lewek","year":"2010","journal-title":"Gait Posture"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.jns.2014.03.041","article-title":"Is reduced arm and leg swing in Parkinson\u2019s disease associated with rigidity or bradykinesia?","volume":"341","author":"Kwon","year":"2014","journal-title":"J. Neurol. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1179\/1743132811Y.0000000044","article-title":"Gait variability in Parkinson\u2019s disease: Influence of walking speed and dopaminergic treatment","volume":"33","author":"Bryant","year":"2011","journal-title":"Neurol. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/j.gaitpost.2018.04.011","article-title":"The reliability of gait variability measures for individuals with Parkinson\u2019s disease and healthy older adults\u2014The effect of gait speed","volume":"62","author":"Rennie","year":"2018","journal-title":"Gait Posture"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Sugiarto, T., Lin, Y., Chang, C., and Hsu, W. (2017, January 11\u201314). Gait analysis based on an inertial measurement unit sensor: Validation of spatiotemporal parameters calculation in healthy young and older adults. Proceedings of the 2017 IEEE\/SICE International Symposium on System Integration (SII), Taipei, Taiwan.","DOI":"10.1109\/SII.2017.8279273"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/15\/4339\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:54:08Z","timestamp":1760176448000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/15\/4339"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,4]]},"references-count":32,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["s20154339"],"URL":"https:\/\/doi.org\/10.3390\/s20154339","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,4]]}}}