Literature DB >> 21096671

Implementation of an iPhone for characterizing Parkinson's disease tremor through a wireless accelerometer application.

Robert Lemoyne1, Timothy Mastroianni, Michael Cozza, Cristian Coroian, Warren Grundfest.   

Abstract

Parkinson's disease represents a chronic movement disorder, which is generally proportionally to age. The status of Parkinson's disease is traditionally classified through ordinal scale strategies, such as the Unified Parkinson's Disease Rating Scale. However, the application of the ordinal scale strategy inherently requires highly specialized and limited medical resources for interpretation. An alternative strategy involves the implementation of an iPhone application that enables the device to serve as a functional wireless accelerometer system. The Parkinson's disease tremor attributes may be recorded in either an effectively autonomous public or private setting, for which the resultant accelerometer signal of the tremor can be conveyed wireless and through email to a remote location for data post-processing. The initial testing and evaluation of the iPhone wireless accelerometer application for quantifying Parkinson's disease tremor successfully demonstrates the capacity to acquire tremor characteristics in an effectively autonomous environment, while potentially alleviating strain on limited and highly specialized medical resources.

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Year:  2010        PMID: 21096671     DOI: 10.1109/IEMBS.2010.5627240

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


  15 in total

1.  Validation of measures from the smartphone sway balance application: a pilot study.

Authors:  Jeremy A Patterson; Ryan Z Amick; Tarunkumar Thummar; Michael E Rogers
Journal:  Int J Sports Phys Ther       Date:  2014-04

2.  Smartphone-based diagnostic for preeclampsia: an mHealth solution for administering the Congo Red Dot (CRD) test in settings with limited resources.

Authors:  Stephan Michael Jonas; Thomas Martin Deserno; Catalin Sorin Buhimschi; Jennifer Makin; Michael Andrew Choma; Irina Alexandra Buhimschi
Journal:  J Am Med Inform Assoc       Date:  2015-05-29       Impact factor: 4.497

3.  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

4.  Reliability and criterion-related validity with a smartphone used in timed-up-and-go test.

Authors:  Alejandro Galán-Mercant; Francisco Javier Barón-López; María T Labajos-Manzanares; Antonio I Cuesta-Vargas
Journal:  Biomed Eng Online       Date:  2014-12-02       Impact factor: 2.819

5.  Mounted Smartphones as Measurement and Control Platforms for Motor-Based Laboratory Test-Beds.

Authors:  Jared A Frank; Anthony Brill; Vikram Kapila
Journal:  Sensors (Basel)       Date:  2016-08-20       Impact factor: 3.576

6.  Developing a Tool for Remote Digital Assessment of Parkinson's Disease.

Authors:  Panagiotis Kassavetis; Tabish A Saifee; George Roussos; Loukas Drougkas; Maja Kojovic; John C Rothwell; Mark J Edwards; Kailash P Bhatia
Journal:  Mov Disord Clin Pract       Date:  2015-10-20

Review 7.  Wearable Devices for Assessment of Tremor.

Authors:  Basilio Vescio; Andrea Quattrone; Rita Nisticò; Marianna Crasà; Aldo Quattrone
Journal:  Front Neurol       Date:  2021-06-11       Impact factor: 4.003

8.  Using a smart phone as a standalone platform for detection and monitoring of pathological tremors.

Authors:  Jean-François Daneault; Benoit Carignan; Carl Éric Codère; Abbas F Sadikot; Christian Duval
Journal:  Front Hum Neurosci       Date:  2013-01-18       Impact factor: 3.169

9.  Gait characteristic analysis and identification based on the iPhone's accelerometer and gyrometer.

Authors:  Bing Sun; Yang Wang; Jacob Banda
Journal:  Sensors (Basel)       Date:  2014-09-12       Impact factor: 3.576

Review 10.  Technologies for Assessment of Motor Disorders in Parkinson's Disease: A Review.

Authors:  Qi Wei Oung; Hariharan Muthusamy; Hoi Leong Lee; Shafriza Nisha Basah; Sazali Yaacob; Mohamed Sarillee; Chia Hau Lee
Journal:  Sensors (Basel)       Date:  2015-08-31       Impact factor: 3.576

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