Smart Vital Signs Monitoring with Defibrillator and Paralyzed Patient Movement Detection Using IoT

In modern healthcare, continuous monitoring of vital signs is crucial for early detection of critical health conditions. This paper presents an IoT-driven health monitoring system that integrates the ESP32 microcontroller to collect and transmit real-time physiological data such as heart rate, blood pressure, and body temperature. The system also incorporates a defibrillator for emergency response to cardiac arrests and an innovative movement detection mechanism to monitor residual movements in paralyzed patients, addressing the risk of bedsores and immobility-related complications. The collected data is transmitted to a cloud-based platform, enabling real-time access for healthcare providers and automated alerts for abnormal conditions. Experimental results demonstrate 95% accuracy in vital signs monitoring and an average response time of 500 ms for emergency alerts. By combining IoT, edge computing, and cloud computing, this system enhances patient monitoring, improves emergency response efficiency, and ensures timely medical interventions, making it a comprehensive solution for modern healthcare challenges.

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Publication Details

Published
2025-05-24
DOI
https://doi.org/10.38124/ijisrt/25may417
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
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article

Smart Vital Signs Monitoring with Defibrillator and Paralyzed Patient Movement Detection Using IoT

Rajalakshmi Arjun, Arul Prakash A, T. Sivaranjani, S. J. Sivaprrasath et al.
EEG and Brain-Computer Interfaces
article

Smart Vital Signs Monitoring with Defibrillator and Paralyzed Patient Movement Detection Using IoT

Rajalakshmi Arjun, Arul Prakash A, T. Sivaranjani, S. J. Sivaprrasath, D. Harshavardhan
article en

Abstract

In modern healthcare, continuous monitoring of vital signs is crucial for early detection of critical health conditions. This paper presents an IoT-driven health monitoring system that integrates the ESP32 microcontroller to collect and transmit real-time physiological data such as heart rate, blood pressure, and body temperature. The system also incorporates a defibrillator for emergency response to cardiac arrests and an innovative movement detection mechanism to monitor residual movements in paralyzed patients, addressing the risk of bedsores and immobility-related complications. The collected data is transmitted to a cloud-based platform, enabling real-time access for healthcare providers and automated alerts for abnormal conditions. Experimental results demonstrate 95% accuracy in vital signs monitoring and an average response time of 500 ms for emergency alerts. By combining IoT, edge computing, and cloud computing, this system enhances patient monitoring, improves emergency response efficiency, and ensures timely medical interventions, making it a comprehensive solution for modern healthcare challenges.

Openalex Percentile: Top 89%
EEG and Brain-Computer Interfaces
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Smart Vital Signs Monitoring with Defibrillator and Paralyzed Patient Movement Detection Using IoT — Rajalakshmi Arjun, Arul Prakash A, et al. · (2025) | TGRS Research Map | TGRS