Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/175419
Title: Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer
Author: Barrantes, Sergi
Sánchez Egea, Antonio J.
González Rojas, Hernán A.
Martí, Maria J.
Compta, Yaroslau
Valldeoriola Serra, Francesc
Simó Mezquita, Ester
Tolosa, Eduardo
Valls Solé, Josep
Keywords: Malaltia de Parkinson
Aplicacions mòbils
Diagnòstic
Parkinson's disease
Mobile apps
Diagnosis
Issue Date: 25-Aug-2017
Publisher: Public Library of Science (PLoS)
Abstract: 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 123I-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.
Note: Reproducció del document publicat a: https://doi.org/10.1371/journal.pone.0183843
It is part of: PLoS One, 2017, vol. 12, num. 8, p. e0183843
URI: http://hdl.handle.net/2445/175419
Related resource: https://doi.org/10.1371/journal.pone.0183843
ISSN: 1932-6203
Appears in Collections:Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)
Articles publicats en revistes (Medicina)

Files in This Item:
File Description SizeFormat 
695418.pdf2.85 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons