DIMETER: a haptic master device for tremor diagnosis in neurodegenerative diseases

González Herranz, Roberto and Barrientos Cruz, Antonio and Cerro Giner, Jaime del and Coca Hernandez, Benito (2014). DIMETER: a haptic master device for tremor diagnosis in neurodegenerative diseases. "Sensors", v. 14 (n. 3); pp. 4536-4559. ISSN 1424-8220. https://doi.org/10.3390/s140304536.

Description

Title: DIMETER: a haptic master device for tremor diagnosis in neurodegenerative diseases
Author/s:
  • González Herranz, Roberto
  • Barrientos Cruz, Antonio
  • Cerro Giner, Jaime del
  • Coca Hernandez, Benito
Item Type: Article
Título de Revista/Publicación: Sensors
Date: 2014
ISSN: 1424-8220
Volume: 14
Subjects:
Freetext Keywords: DIMETER; diagnostic tremor aids; Parkinson’s disease (PD) diagnosis; essential tremor (ET) diagnosis; neurodegenerative diseases; haptic master; tremor device
Faculty: E.U.I.T. Industrial (UPM)
Department: Electrónica, Automática e Informática Industrial [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this study, a device based on patient motion capture is developed for the reliable and non-invasive diagnosis of neurodegenerative diseases. The primary objective of this study is the classification of differential diagnosis between Parkinson's disease (PD) and essential tremor (ET). The DIMETER system has been used in the diagnoses of a significant number of patients at two medical centers in Spain. Research studies on classification have primarily focused on the use of well-known and reliable diagnosis criteria developed by qualified personnel. Here, we first present a literature review of the methods used to detect and evaluate tremor; then, we describe the DIMETER device in terms of the software and hardware used and the battery of tests developed to obtain the best diagnoses. All of the tests are classified and described in terms of the characteristics of the data obtained. A list of parameters obtained from the tests is provided, and the results obtained using multilayer perceptron (MLP) neural networks are presented and analyzed.

More information

Item ID: 23282
DC Identifier: http://oa.upm.es/23282/
OAI Identifier: oai:oa.upm.es:23282
DOI: 10.3390/s140304536
Official URL: http://www.mdpi.com/1424-8220/14/3/4536/pdf
Deposited by: Memoria Investigacion
Deposited on: 06 May 2014 08:09
Last Modified: 22 Mar 2019 08:17
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