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Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer
BACKGROUND: The differential diagnosis between patients with essential tremor (ET) and those with Parkinson’s disease (PD) whose main manifestation is tremor may be difficult unless using complex neuroimaging techniques such as (123)I-FP-CIT SPECT. We considered that using smartphone’s accelerometer...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571972/ https://www.ncbi.nlm.nih.gov/pubmed/28841694 http://dx.doi.org/10.1371/journal.pone.0183843 |
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author | Barrantes, Sergi Sánchez Egea, Antonio J. González Rojas, Hernán A. Martí, Maria J. Compta, Yaroslau Valldeoriola, Francesc Simo Mezquita, Ester Tolosa, Eduard Valls-Solè, Josep |
author_facet | Barrantes, Sergi Sánchez Egea, Antonio J. González Rojas, Hernán A. Martí, Maria J. Compta, Yaroslau Valldeoriola, Francesc Simo Mezquita, Ester Tolosa, Eduard Valls-Solè, Josep |
author_sort | Barrantes, Sergi |
collection | PubMed |
description | BACKGROUND: The differential diagnosis between patients with essential tremor (ET) and those with Parkinson’s disease (PD) whose main manifestation is tremor may be difficult unless using complex neuroimaging techniques such as (123)I-FP-CIT SPECT. We considered that using smartphone’s accelerometer to stablish a diagnostic test based on time-frequency differences between PD an ET could support the clinical diagnosis. METHODS: The study was carried out in 17 patients with PD, 16 patients with ET, 12 healthy volunteers and 7 patients with tremor of undecided diagnosis (TUD), who were re-evaluated one year after the first visit to reach the definite diagnosis. The smartphone was placed over the hand dorsum to record epochs of 30 s at rest and 30 s during arm stretching. We generated frequency power spectra and calculated receiver operating characteristics curves (ROC) curves of total spectral power, to establish a threshold to separate subjects with and without tremor. In patients with PD and ET, we found that the ROC curve of relative energy was the feature discriminating better between the two groups. This threshold was then used to classify the TUD patients. RESULTS: We could correctly classify 49 out of 52 subjects in the category with/without tremor (97.96% sensitivity and 83.3% specificity) and 27 out of 32 patients in the category PD/ET (84.38% discrimination accuracy). Among TUD patients, 2 of 2 PD and 2 of 4 ET were correctly classified, and one patient having PD plus ET was classified as PD. CONCLUSIONS: Based on the analysis of smartphone accelerometer recordings, we found several kinematic features in the analysis of tremor that distinguished first between healthy subjects and patients and, ultimately, between PD and ET patients. The proposed method can give immediate results for the clinician to gain valuable information for the diagnosis of tremor. This can be useful in environments where more sophisticated diagnostic techniques are unavailable. |
format | Online Article Text |
id | pubmed-5571972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55719722017-09-09 Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer Barrantes, Sergi Sánchez Egea, Antonio J. González Rojas, Hernán A. Martí, Maria J. Compta, Yaroslau Valldeoriola, Francesc Simo Mezquita, Ester Tolosa, Eduard Valls-Solè, Josep PLoS One Research Article BACKGROUND: The differential diagnosis between patients with essential tremor (ET) and those with Parkinson’s disease (PD) whose main manifestation is tremor may be difficult unless using complex neuroimaging techniques such as (123)I-FP-CIT SPECT. We considered that using smartphone’s accelerometer to stablish a diagnostic test based on time-frequency differences between PD an ET could support the clinical diagnosis. METHODS: The study was carried out in 17 patients with PD, 16 patients with ET, 12 healthy volunteers and 7 patients with tremor of undecided diagnosis (TUD), who were re-evaluated one year after the first visit to reach the definite diagnosis. The smartphone was placed over the hand dorsum to record epochs of 30 s at rest and 30 s during arm stretching. We generated frequency power spectra and calculated receiver operating characteristics curves (ROC) curves of total spectral power, to establish a threshold to separate subjects with and without tremor. In patients with PD and ET, we found that the ROC curve of relative energy was the feature discriminating better between the two groups. This threshold was then used to classify the TUD patients. RESULTS: We could correctly classify 49 out of 52 subjects in the category with/without tremor (97.96% sensitivity and 83.3% specificity) and 27 out of 32 patients in the category PD/ET (84.38% discrimination accuracy). Among TUD patients, 2 of 2 PD and 2 of 4 ET were correctly classified, and one patient having PD plus ET was classified as PD. CONCLUSIONS: Based on the analysis of smartphone accelerometer recordings, we found several kinematic features in the analysis of tremor that distinguished first between healthy subjects and patients and, ultimately, between PD and ET patients. The proposed method can give immediate results for the clinician to gain valuable information for the diagnosis of tremor. This can be useful in environments where more sophisticated diagnostic techniques are unavailable. Public Library of Science 2017-08-25 /pmc/articles/PMC5571972/ /pubmed/28841694 http://dx.doi.org/10.1371/journal.pone.0183843 Text en © 2017 Barrantes et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Barrantes, Sergi Sánchez Egea, Antonio J. González Rojas, Hernán A. Martí, Maria J. Compta, Yaroslau Valldeoriola, Francesc Simo Mezquita, Ester Tolosa, Eduard Valls-Solè, Josep Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer |
title | Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer |
title_full | Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer |
title_fullStr | Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer |
title_full_unstemmed | Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer |
title_short | Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer |
title_sort | differential diagnosis between parkinson's disease and essential tremor using the smartphone's accelerometer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571972/ https://www.ncbi.nlm.nih.gov/pubmed/28841694 http://dx.doi.org/10.1371/journal.pone.0183843 |
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