Smart Bracelet to Monitor Hospital Patients

This research presents the development of an IoT-based smart bracelet designed to enhance healthcare monitoring by collecting real-time health data and precise 3D location (latitude, longitude, altitude) of patients. By transmitting this data to a central server, the bracelet enables the creation of a machine learning model capable of predicting patient outcomes, specifically recovery or mortality within a 28-day period. The model leverages advanced algorithms to process physiological and spatial data, providing healthcare providers with timely insights and enabling proactive care interventions. This study demonstrates the potential of IoT and machine learning to improve patient management, especially in critical care, by offering a predictive tool that supports informed clinical decision-making.

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Publication Details

Published
2025-01-28
DOI
https://doi.org/10.1109/isnib64820.2025.10982721
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
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article

Smart Bracelet to Monitor Hospital Patients

Yousra Ben Aissa, Mohamed Nafae Saoudi, Nourelhouda Zerarka, Bouthina Rechachi
Non-Invasive Vital Sign Monitoring
article

Smart Bracelet to Monitor Hospital Patients

Yousra Ben Aissa, Mohamed Nafae Saoudi, Nourelhouda Zerarka, Bouthina Rechachi
article en

Abstract

This research presents the development of an IoT-based smart bracelet designed to enhance healthcare monitoring by collecting real-time health data and precise 3D location (latitude, longitude, altitude) of patients. By transmitting this data to a central server, the bracelet enables the creation of a machine learning model capable of predicting patient outcomes, specifically recovery or mortality within a 28-day period. The model leverages advanced algorithms to process physiological and spatial data, providing healthcare providers with timely insights and enabling proactive care interventions. This study demonstrates the potential of IoT and machine learning to improve patient management, especially in critical care, by offering a predictive tool that supports informed clinical decision-making.

University of Biskra (DZ)
Openalex Percentile: Top 91%
Non-Invasive Vital Sign Monitoring
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