REMOTE REHABILITATION MONITORING IN HEALTHCARE USING ESP32 AND ARDUINO UNO FOR REAL-TIME PHYSIOLOGICAL PARAMETER ANALYSIS

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Autores principales: Ergashev, Nurmukhammad Ibrokhimjon, Ibragimov, Sanjarbek Salijanovich
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2026
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author Ergashev, Nurmukhammad Ibrokhimjon
Ibragimov, Sanjarbek Salijanovich
author_facet Ergashev, Nurmukhammad Ibrokhimjon
Ibragimov, Sanjarbek Salijanovich
contents <p class="MsoNormal">The rapid growth of Internet of Things (IoT) technologies has significantly transformed the healthcare sector, particularly in remote patient monitoring and rehabilitation systems. Continuous monitoring of physiological parameters such as heart rate and body temperature has become increasingly important in rehabilitation medicine, elderly care, and chronic disease management. Traditional monitoring systems are often expensive, infrastructure-dependent, and inaccessible for small healthcare centers and home-based rehabilitation environments. This study presents the design and implementation of a low-cost IoT-based remote rehabilitation monitoring system using Arduino Uno, ESP32 Wi-Fi module, Pulse Sensor, and DHT11 temperature sensor. The proposed system is capable of collecting physiological data in real time and transmitting it through a local wireless network without reliance on cloud infrastructure. Arduino Uno performs sensor data acquisition and preliminary processing, while ESP32 provides wireless communication and hosts a local web server for data visualization. The experimental results demonstrate stable real-time monitoring with low latency and acceptable accuracy for rehabilitation applications. The proposed architecture offers advantages including affordability, portability, low power consumption, local data security, and ease of deployment in rehabilitation centers and home healthcare environments.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_20383814
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publishDate 2026
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spellingShingle REMOTE REHABILITATION MONITORING IN HEALTHCARE USING ESP32 AND ARDUINO UNO FOR REAL-TIME PHYSIOLOGICAL PARAMETER ANALYSIS
Ergashev, Nurmukhammad Ibrokhimjon
Ibragimov, Sanjarbek Salijanovich
Internet of Things, ESP32, Arduino Uno, rehabilitation monitoring, remote healthcare, Pulse Sensor, DHT11, physiological monitoring, local web server, IoT healthcare..
<p class="MsoNormal">The rapid growth of Internet of Things (IoT) technologies has significantly transformed the healthcare sector, particularly in remote patient monitoring and rehabilitation systems. Continuous monitoring of physiological parameters such as heart rate and body temperature has become increasingly important in rehabilitation medicine, elderly care, and chronic disease management. Traditional monitoring systems are often expensive, infrastructure-dependent, and inaccessible for small healthcare centers and home-based rehabilitation environments. This study presents the design and implementation of a low-cost IoT-based remote rehabilitation monitoring system using Arduino Uno, ESP32 Wi-Fi module, Pulse Sensor, and DHT11 temperature sensor. The proposed system is capable of collecting physiological data in real time and transmitting it through a local wireless network without reliance on cloud infrastructure. Arduino Uno performs sensor data acquisition and preliminary processing, while ESP32 provides wireless communication and hosts a local web server for data visualization. The experimental results demonstrate stable real-time monitoring with low latency and acceptable accuracy for rehabilitation applications. The proposed architecture offers advantages including affordability, portability, low power consumption, local data security, and ease of deployment in rehabilitation centers and home healthcare environments.</p>
title REMOTE REHABILITATION MONITORING IN HEALTHCARE USING ESP32 AND ARDUINO UNO FOR REAL-TIME PHYSIOLOGICAL PARAMETER ANALYSIS
topic Internet of Things, ESP32, Arduino Uno, rehabilitation monitoring, remote healthcare, Pulse Sensor, DHT11, physiological monitoring, local web server, IoT healthcare..
url https://doi.org/10.5281/zenodo.20383814