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

被引：11

作者：

Junior, Eugenio Peixoto ^{[1
]}

Delmiro, Italo L. D. ^{[1
]}

Magaia, Naercio ^{[2
]}

Maia, Fernanda M. ^{[1
]}

Hassan, Mohammad Mehedi ^{[3
]}

Albuquerque, Victor Hugo C. ^{[1
]}

Fortino, Giancarlo ^{[4
]}

机构：

[1] Univ Fortaleza, Grad Program Appl Informat PPGIA, BR-60811905 Fortaleza, Ceara, Brazil

[2] Univ Lisbon, LASIGE, Dept Comp Sci, Fac Sci, P-1749016 Lisbon, Portugal

[3] King Saud Univ, Coll Comp & Informat Sci, Dept Informat Syst, Riyadh 11543, Saudi Arabia

[4] Univ Calabria, Dept Informat Modeling Elect & Syst, I-87036 Arcavacata Di Rende, Italy

来源：

SENSORS | 2020年 / 20卷 / 20期

关键词：

Parkinson’ s disease; machine learning; handwritten dynamics; ACTIVITY RECOGNITION; CLASSIFICATION;

D O I：

10.3390/s20205840

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

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.

引用

页码：1 / 21

页数：20

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