bsuirДоклады БГУИРDoklady BGUIR1729-76482708-0382БГУИР10.35596/1729-7648-2024-22-5-104-112bsuir-3988Research ArticleСтатьиРазработка и моделирование сети интернета вещей для IT-диагностики пациентовDevelopment and Modeling of the Internet of Things Network for Patients IT DiagnosticsВишняковВ. А.VishniakouU. A.

Вишняков Владимир Анатольевич, д-р техн. наук, проф. каф. инфокоммуникационных технологий

220013, г. Минск, ул. П. Бровки, 6

Тел.: +375 44 486-71-82

Vishniakou Uladzimir Anatol’evich, Dr. of Sci. (Tech.), Professor at the Department of Infocommunication Technologies

20013, Minsk, P. Brovki St., 6

Tel.: +375 44 486-71-82

vish@bsuir.byЮэЮй ЧуYueYu Chu

Юй Чу Юэ, асп. каф. инфокоммуникационных технологий

г. Минск

Yu Chu Yue, Postgraduate at the Department of Infocommunication Technologies

Minsk

Белорусский государственный университет информатики и радиоэлектроникиBelarusian State University of Informatics and Radioelectronics202425102024225104112Copyright © Вишняков В.А., Юэ Ю.Ч., 20242024Вишняков В.А., Юэ Ю.Ч.Vishniakou U.A., Yue Y.C.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://doklady.bsuir.by/jour/article/view/3988

Разработана и смоделирована работа сети, которая реализует алгоритмы IT-диагностики неврологических заболеваний на базе технологии интернета вещей. Сеть включает смартфон, платформу, нейронную сеть и приложения. Сначала со смартфона вводятся голоса заболевших пациентов для обучения нейронной сети, а потом – обследуемых пациентов для IT-диагностики. Передача данных между смартфоном и платформой (ThingSpeak) происходит по протоколу MQTT. Мобильное приложение смартфона извлекает голосовые функции обследуемых пациентов и записывает их на платформу сети интернета вещей. Распознавание происходит с использованием обученной нейронной сети. Представлены структура и алгоритм работы платформы ThingSpeak. Показатели IT-диагностики отображаются в приложении на смартфоне. Данные пациентов, использованные в исследовании, взяты из программы ADReSS 2020 Challenge, которая содержит речевые данные пациентов с болезнью Альцгеймера и здоровых людей. 

The work of a network that implements algorithms for IT diagnostics of neurological diseases based on the Internet of Things technology has been developed and modeled. The network includes a smartphone, a platform, a neural network, and applications. First, the voices of sick patients are entered from the smartphone to train the neural network, and then the examined patients for IT diagnostics. Data is transferred between the smartphone and the platform (ThingSpeak) via the MQTT protocol. The smartphone’s mobile application extracts the voice functions of the examined patients and records them on the Internet of Things network platform. Recognition is performed using the trained neural network. The structure and algorithm of the ThingSpeak platform are presented. IT diagnostics data are displayed in the application on the smartphone. The patient data used in the study are taken from the ADReSS 2020 Challenge program, which contains speech data of patients with Alzheimer’s disease and healthy people.

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The authors declare that there are no conflicts of interest present.