Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review
Inertial sensors are commonly embedded in several devices, including smartphones, and other specific devices. This type of sensors may be used for different purposes, including the recognition of different diseases. Several studies are focused on the use of accelerometer signals for the automatic re...
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doaj-07a17d63f5f94d1abab4a6d0dbe7a1cd2020-11-25T03:26:44ZengMDPI AGElectronics2079-92922020-05-01977877810.3390/electronics9050778Identification of Diseases Based on the Use of Inertial Sensors: A Systematic ReviewVasco Ponciano0Ivan Miguel Pires1Fernando Reinaldo Ribeiro2Gonçalo Marques3Maria Vanessa Villasana4Nuno M. Garcia5Eftim Zdravevski6Susanna Spinsante7R&D Unit in Digital Services, Applications, and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalInstitute of Telecommunications, University of Beira Interior, 6200-001 Covilha, PortugalR&D Unit in Digital Services, Applications, and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalInstitute of Telecommunications, University of Beira Interior, 6200-001 Covilha, PortugalFaculty of Health Sciences, University of Beira Interior, 6200-506 Covilha, PortugalInstitute of Telecommunications, University of Beira Interior, 6200-001 Covilha, PortugalFaculty of Computer Science and Engineering, University of Cyril and Methodius, 1000 Skopje, MacedoniaDepartment of Information Engineering, Marche Polytechnic University, 60121 Ancona, ItalyInertial sensors are commonly embedded in several devices, including smartphones, and other specific devices. This type of sensors may be used for different purposes, including the recognition of different diseases. Several studies are focused on the use of accelerometer signals for the automatic recognition of different diseases, and it may empower the different treatments with the use of less invasive and painful techniques for patients. This paper aims to provide a systematic review of the studies available in the literature for the automatic recognition of different diseases by exploiting accelerometer sensors. The most reliably detectable disease using accelerometer sensors, available in 54% of the analyzed studies, is the Parkinson’s disease. The machine learning methods implemented for the automatic recognition of Parkinson’s disease reported an accuracy of 94%. The recognition of other diseases is investigated in a few other papers, and it appears to be the target of further analysis in the future.https://www.mdpi.com/2079-9292/9/5/778AccelerometerWearable electronic devicesDiseasesMonitoringAmbulatoryAutomatic identification |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Vasco Ponciano Ivan Miguel Pires Fernando Reinaldo Ribeiro Gonçalo Marques Maria Vanessa Villasana Nuno M. Garcia Eftim Zdravevski Susanna Spinsante |
spellingShingle |
Vasco Ponciano Ivan Miguel Pires Fernando Reinaldo Ribeiro Gonçalo Marques Maria Vanessa Villasana Nuno M. Garcia Eftim Zdravevski Susanna Spinsante Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review Electronics Accelerometer Wearable electronic devices Diseases Monitoring Ambulatory Automatic identification |
author_facet |
Vasco Ponciano Ivan Miguel Pires Fernando Reinaldo Ribeiro Gonçalo Marques Maria Vanessa Villasana Nuno M. Garcia Eftim Zdravevski Susanna Spinsante |
author_sort |
Vasco Ponciano |
title |
Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review |
title_short |
Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review |
title_full |
Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review |
title_fullStr |
Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review |
title_full_unstemmed |
Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review |
title_sort |
identification of diseases based on the use of inertial sensors: a systematic review |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2020-05-01 |
description |
Inertial sensors are commonly embedded in several devices, including smartphones, and other specific devices. This type of sensors may be used for different purposes, including the recognition of different diseases. Several studies are focused on the use of accelerometer signals for the automatic recognition of different diseases, and it may empower the different treatments with the use of less invasive and painful techniques for patients. This paper aims to provide a systematic review of the studies available in the literature for the automatic recognition of different diseases by exploiting accelerometer sensors. The most reliably detectable disease using accelerometer sensors, available in 54% of the analyzed studies, is the Parkinson’s disease. The machine learning methods implemented for the automatic recognition of Parkinson’s disease reported an accuracy of 94%. The recognition of other diseases is investigated in a few other papers, and it appears to be the target of further analysis in the future. |
topic |
Accelerometer Wearable electronic devices Diseases Monitoring Ambulatory Automatic identification |
url |
https://www.mdpi.com/2079-9292/9/5/778 |
work_keys_str_mv |
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