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Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors
Parkinson’s disease (PD) is one of the most common chronic neurological diseases and one of the significant causes of disability for middle-aged and elderly people. Monitoring the patient’s condition and its compliance is the key to the success of the correction of the main clinical manifestations o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235735/ https://www.ncbi.nlm.nih.gov/pubmed/32290633 http://dx.doi.org/10.3390/diagnostics10040214 |
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author | Shichkina, Yulia Stanevich, Elizaveta Irishina, Yulia |
author_facet | Shichkina, Yulia Stanevich, Elizaveta Irishina, Yulia |
author_sort | Shichkina, Yulia |
collection | PubMed |
description | Parkinson’s disease (PD) is one of the most common chronic neurological diseases and one of the significant causes of disability for middle-aged and elderly people. Monitoring the patient’s condition and its compliance is the key to the success of the correction of the main clinical manifestations of PD, including the almost inevitable modification of the clinical picture of the disease against the background of prolonged dopaminergic therapy. In this article, we proposed an approach to assessing the condition of patients with PD using deep recurrent neural networks, trained on data measured using mobile phones. The data was received in two modes: background (data from the phone’s sensors) and interactive (data directly entered by the user). For the classification of the patient’s condition, we built various models of the neural network. Testing of these models showed that the most efficient was a recurrent network with two layers. The results of the experiment show that with a sufficient amount of the training sample, it is possible to build a neural network that determines the condition of the patient according to the data from the mobile phone sensors with a high probability. |
format | Online Article Text |
id | pubmed-7235735 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72357352020-05-22 Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors Shichkina, Yulia Stanevich, Elizaveta Irishina, Yulia Diagnostics (Basel) Article Parkinson’s disease (PD) is one of the most common chronic neurological diseases and one of the significant causes of disability for middle-aged and elderly people. Monitoring the patient’s condition and its compliance is the key to the success of the correction of the main clinical manifestations of PD, including the almost inevitable modification of the clinical picture of the disease against the background of prolonged dopaminergic therapy. In this article, we proposed an approach to assessing the condition of patients with PD using deep recurrent neural networks, trained on data measured using mobile phones. The data was received in two modes: background (data from the phone’s sensors) and interactive (data directly entered by the user). For the classification of the patient’s condition, we built various models of the neural network. Testing of these models showed that the most efficient was a recurrent network with two layers. The results of the experiment show that with a sufficient amount of the training sample, it is possible to build a neural network that determines the condition of the patient according to the data from the mobile phone sensors with a high probability. MDPI 2020-04-12 /pmc/articles/PMC7235735/ /pubmed/32290633 http://dx.doi.org/10.3390/diagnostics10040214 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shichkina, Yulia Stanevich, Elizaveta Irishina, Yulia Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors |
title | Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors |
title_full | Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors |
title_fullStr | Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors |
title_full_unstemmed | Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors |
title_short | Assessment of the Status of Patients with Parkinson’s Disease Using Neural Networks and Mobile Phone Sensors |
title_sort | assessment of the status of patients with parkinson’s disease using neural networks and mobile phone sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235735/ https://www.ncbi.nlm.nih.gov/pubmed/32290633 http://dx.doi.org/10.3390/diagnostics10040214 |
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