Literature DB >> 21096462

Home monitoring of patients with Parkinson's disease via wearable technology and a web-based application.

Shyamal Patel1, Bor-Rong Chen, Thomas Buckley, Ramona Rednic, Doug McClure, Daniel Tarsy, Ludy Shih, Jennifer Dy, Matt Welsh, Paolo Bonato.   

Abstract

Objective long-term health monitoring can improve the clinical management of several medical conditions ranging from cardiopulmonary diseases to motor disorders. In this paper, we present our work toward the development of a home-monitoring system. The system is currently used to monitor patients with Parkinson's disease who experience severe motor fluctuations. Monitoring is achieved using wireless wearable sensors whose data are relayed to a remote clinical site via a web-based application. The work herein presented shows that wearable sensors combined with a web-based application provide reliable quantitative information that can be used for clinical decision making.

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Year:  2010        PMID: 21096462     DOI: 10.1109/IEMBS.2010.5627124

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  18 in total

1.  Telemonitoring of patients with Parkinson's disease using inertia sensors.

Authors:  N E Piro; L Baumann; M Tengler; L Piro; R Blechschmidt-Trapp
Journal:  Appl Clin Inform       Date:  2014-05-28       Impact factor: 2.342

2.  Framework of sensor-based monitoring for pervasive patient care.

Authors:  Andreas K Triantafyllidis; Vassilis G Koutkias; Ioanna Chouvarda; Ilia Adami; Angelina Kouroubali; Nicos Maglaveras
Journal:  Healthc Technol Lett       Date:  2016-08-12

Review 3.  The promise of mHealth: daily activity monitoring and outcome assessments by wearable sensors.

Authors:  Bruce H Dobkin; Andrew Dorsch
Journal:  Neurorehabil Neural Repair       Date:  2011 Nov-Dec       Impact factor: 3.919

Review 4.  Using wearables to assess bradykinesia and rigidity in patients with Parkinson's disease: a focused, narrative review of the literature.

Authors:  Itay Teshuva; Inbar Hillel; Eran Gazit; Nir Giladi; Anat Mirelman; Jeffrey M Hausdorff
Journal:  J Neural Transm (Vienna)       Date:  2019-05-22       Impact factor: 3.575

5.  Empirical Wavelet Transform Based Features for Classification of Parkinson's Disease Severity.

Authors:  Qi Wei Oung; Hariharan Muthusamy; Shafriza Nisha Basah; Hoileong Lee; Vikneswaran Vijean
Journal:  J Med Syst       Date:  2017-12-29       Impact factor: 4.460

Review 6.  Objective and quantitative assessment of motor function in Parkinson's disease-from the perspective of practical applications.

Authors:  Ke Yang; Wei-Xi Xiong; Feng-Tao Liu; Yi-Min Sun; Susan Luo; Zheng-Tong Ding; Jian-Jun Wu; Jian Wang
Journal:  Ann Transl Med       Date:  2016-03

7.  Automatic assessment of the motor state of the Parkinson's disease patient--a case study.

Authors:  Bozena Kostek; Katarzyna Kaszuba; Pawel Zwan; Piotr Robowski; Jaroslaw Slawek
Journal:  Diagn Pathol       Date:  2012-02-19       Impact factor: 2.644

8.  Unbiased and mobile gait analysis detects motor impairment in Parkinson's disease.

Authors:  Jochen Klucken; Jens Barth; Patrick Kugler; Johannes Schlachetzki; Thore Henze; Franz Marxreiter; Zacharias Kohl; Ralph Steidl; Joachim Hornegger; Bjoern Eskofier; Juergen Winkler
Journal:  PLoS One       Date:  2013-02-19       Impact factor: 3.240

9.  A telemedicine instrument for remote evaluation of tremor: design and initial applications in fatigue and patients with Parkinson's disease.

Authors:  Mário C Barroso Júnior; Guilherme P Esteves; Thiago P Nunes; Lucia M G Silva; Alvaro C D Faria; Pedro L Melo
Journal:  Biomed Eng Online       Date:  2011-02-09       Impact factor: 2.819

10.  Feasibility study of a wearable system based on a wireless body area network for gait assessment in Parkinson's disease patients.

Authors:  Jorge Cancela; Matteo Pastorino; Maria T Arredondo; Konstantina S Nikita; Federico Villagra; Maria A Pastor
Journal:  Sensors (Basel)       Date:  2014-03-07       Impact factor: 3.576

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