Intelligent Sensory Pen for Aiding in the Diagnosis of Parkinson’s Disease from Dynamic Handwriting Analysis

Clicks: 172
ID: 273608
2020
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Abstract
In this paper, we propose a pen device capable of detecting specific features from dynamic handwriting tests for aiding on automatic Parkinson’s disease identification. The method used in this work uses machine learning to compare the raw signals from different sensors in the device coupled to a pen and extract relevant information such as tremors and hand acceleration to diagnose the patient clinically. Additionally, the datasets composed of raw signals from healthy and Parkinson’s disease patients acquired here are made available to further contribute to research related to this topic.
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júnior2020sensorsintelligent Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Eugênio Peixoto Júnior;Italo L. D. Delmiro;Naercio Magaia;Fernanda M. Maia;Mohammad Mehedi Hassan;Victor Hugo C. Albuquerque;Giancarlo Fortino;Júnior, Eugênio Peixoto;Delmiro, Italo L. D.;Magaia, Naercio;Maia, Fernanda M.;Hassan, Mohammad Mehedi;Albuquerque, Victor Hugo C.;Fortino, Giancarlo;
Journal sensors
Year 2020
DOI
10.3390/s20205840
URL
https://www.mdpi.com/1424-8220/20/20/5840
Keywords
Machine learning parkinson’s disease handwritten dynamics

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