Assessment of Tremor Activity in the Parkinson's Disease Using a Set of Wearable Sensors
dc.contributor.author | Rigas, G. | en |
dc.contributor.author | Tzallas, A. | en |
dc.contributor.author | Tsipouras, M. | en |
dc.contributor.author | Bougia, P. | en |
dc.contributor.author | Tripoliti, E. | en |
dc.contributor.author | Baga, D. | en |
dc.contributor.author | Fotiadis, D. | en |
dc.contributor.author | Tsouli, S. | en |
dc.contributor.author | Konitsiotis, S. | en |
dc.date.accessioned | 2015-11-24T19:35:07Z | |
dc.date.available | 2015-11-24T19:35:07Z | |
dc.identifier.issn | 1558-0032 | - |
dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/23680 | |
dc.rights | Default Licence | - |
dc.title | Assessment of Tremor Activity in the Parkinson's Disease Using a Set of Wearable Sensors | en |
heal.abstract | Tremor is the most common motor disorder of Parkinsons Disease (PD) and consequently its detection plays a crucial role in the management and treatment of PD patients. The current diagnosis procedure is based on subject dependent clinical assessment which has a difficulty in capturing subtle tremor features. In this paper, an automated method for both resting and action/postural tremor assessment is proposed using a set of accelerometers mounted on different patients body segments. The estimation of tremor type (resting/action-postural) and severity is based on features extracted from the acquired signals and Hidden Markov models. The method is evaluated using data collected from 23 subjects (18 PD patients and 5 control subjects). The obtained results verified that the proposed method successfully: (i) quantifies tremor severity with 87% accuracy, (ii) discriminates resting from postural tremor and (iii) discriminates tremor from other Parkinsonian motor symptoms during daily activities. | en |
heal.access | campus | - |
heal.fullTextAvailability | TRUE | - |
heal.identifier.primary | 10.1109/TITB.2011.2182616 | - |
heal.identifier.secondary | http://www.ncbi.nlm.nih.gov/pubmed/22231198 | - |
heal.identifier.secondary | http://ieeexplore.ieee.org/ielx5/4233/4358869/06121951.pdf?tp=&arnumber=6121951&isnumber=4358869 | - |
heal.journalName | IEEE Trans Inf Technol Biomed | en |
heal.journalType | peer-reviewed | - |
heal.language | en | - |
heal.publicationDate | 2012 | - |
heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικής | el |
heal.type | journalArticle | - |
heal.type.el | Άρθρο Περιοδικού | el |
heal.type.en | Journal article | en |
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