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Characterizing Orthostatic Tremor Using a Smartphone Application

BACKGROUND: Orthostatic tremor is one of the few tremor conditions requiring an electromyogram for definitive diagnosis since leg tremor might not be visible to the naked eye. PHENOMENOLOGY SHOWN: An iOS application (iSeismometer, ObjectGraph LLC, New York) using an Apple iPhone 5 (Cupertino, CA, US...

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Detalles Bibliográficos
Autores principales: Balachandar, Arjun, Fasano, Alfonso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Columbia University Libraries/Information Services 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5623759/
https://www.ncbi.nlm.nih.gov/pubmed/28975048
http://dx.doi.org/10.7916/D8V12GRJ
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author Balachandar, Arjun
Fasano, Alfonso
author_facet Balachandar, Arjun
Fasano, Alfonso
author_sort Balachandar, Arjun
collection PubMed
description BACKGROUND: Orthostatic tremor is one of the few tremor conditions requiring an electromyogram for definitive diagnosis since leg tremor might not be visible to the naked eye. PHENOMENOLOGY SHOWN: An iOS application (iSeismometer, ObjectGraph LLC, New York) using an Apple iPhone 5 (Cupertino, CA, USA) inserted into the patient’s sock detected a tremor with a frequency of 16.4 Hz on both legs. EDUCATIONAL VALUE: The rapid and straightforward accelerometer-based recordings accomplished in this patient demonstrate the ease with which quantitative analysis of orthostatic tremor can be conducted and, importantly, demonstrates the potential application of this approach in the assessment of any lower limb tremor.
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spelling pubmed-56237592017-10-03 Characterizing Orthostatic Tremor Using a Smartphone Application Balachandar, Arjun Fasano, Alfonso Tremor Other Hyperkinet Mov (N Y) Teaching NeuroImages BACKGROUND: Orthostatic tremor is one of the few tremor conditions requiring an electromyogram for definitive diagnosis since leg tremor might not be visible to the naked eye. PHENOMENOLOGY SHOWN: An iOS application (iSeismometer, ObjectGraph LLC, New York) using an Apple iPhone 5 (Cupertino, CA, USA) inserted into the patient’s sock detected a tremor with a frequency of 16.4 Hz on both legs. EDUCATIONAL VALUE: The rapid and straightforward accelerometer-based recordings accomplished in this patient demonstrate the ease with which quantitative analysis of orthostatic tremor can be conducted and, importantly, demonstrates the potential application of this approach in the assessment of any lower limb tremor. Columbia University Libraries/Information Services 2017-07-18 /pmc/articles/PMC5623759/ /pubmed/28975048 http://dx.doi.org/10.7916/D8V12GRJ Text en © 2017 Balachandar et al. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution–Noncommerical–No Derivatives License, which permits the user to copy, distribute, and transmit the work provided that the original author and source are credited; that no commercial use is made of the work; and that the work is not altered or transformed.
spellingShingle Teaching NeuroImages
Balachandar, Arjun
Fasano, Alfonso
Characterizing Orthostatic Tremor Using a Smartphone Application
title Characterizing Orthostatic Tremor Using a Smartphone Application
title_full Characterizing Orthostatic Tremor Using a Smartphone Application
title_fullStr Characterizing Orthostatic Tremor Using a Smartphone Application
title_full_unstemmed Characterizing Orthostatic Tremor Using a Smartphone Application
title_short Characterizing Orthostatic Tremor Using a Smartphone Application
title_sort characterizing orthostatic tremor using a smartphone application
topic Teaching NeuroImages
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5623759/
https://www.ncbi.nlm.nih.gov/pubmed/28975048
http://dx.doi.org/10.7916/D8V12GRJ
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