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Descripción
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| The mPower: Mobile Parkinson Disease (PD) Stydy is an observational study developed to evaluate the feasibility of remotely collecting information about PD symptoms. With the mPower App, voice recordings have been collected by volunteer participants with their own smartphones, which was then added to each individual PD diagnosis. In this papaer we present a basic analysis of the voice data and a feature extraction process on a sample of 2218 participants. Statistical analysis was performed to idebtify diagnosis through such parameteres and some demographical variables. principal Componente Analysis (PCA), analysis of variance (ANOVA), and multilayer perceptron (MLP) were used in order to build a prediction model. The 62 initial parameters were reduced to 5, obtaining similar predictive capacity with 62 or 5 parameters. The use of acoustic voice parameteres has been proposed as an objetive and non-invasive method for the early diagnosis of the disease. This work contibutes to ideentify voice parameters that allow through prediction models, remote monitoring of patientes,and reducing cost. | |
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Internacional
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Si |
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Entidad
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The 13th World Congress on Controversies in Neurology (CONy) |
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Lugar
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Madrid |
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Páginas
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Tipo de publicación
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Poster |