Portable ECG device with Android Mobile Application for continuous and real-time monitoring

Advanced patient monitoring systems are now more important than ever due to the changing healthcare landscape and the increasing requirement for prompt and effective patient care.Conventional approaches frequently fail to provide prompt reactions to significant shifts in a patient's condition.In this regard, the incorporation of Internet of Things (IoT) technology allows for ongoing, real-time data collecting from remote and wearable medical devices, providing a more responsive and dynamic healthcare setting.Machine learning techniques are used in the system to efficiently analyse large streams of health data and to identify minor trends and anomalies that could be early indicators of deterioration.A proactive healthcare approach is supported by this sophisticated anomaly detection, which enables healthcare providers to act quickly and enhance patient outcomes.Ultimately, the combination of machine learning and IoT gives healthcare professionals predictive insights that enable quicker, more intelligent, and more individualised patient treatment.

Publication Details

Journal
IARJSET
Published
2025-05-05
DOI
https://doi.org/10.17148/iarjset.2025.12533
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Portable ECG device with Android Mobile Application for continuous and real-time monitoring

IARJSET
ECG Monitoring and Analysis
article

Portable ECG device with Android Mobile Application for continuous and real-time monitoring

article en

Abstract

Advanced patient monitoring systems are now more important than ever due to the changing healthcare landscape and the increasing requirement for prompt and effective patient care.Conventional approaches frequently fail to provide prompt reactions to significant shifts in a patient's condition.In this regard, the incorporation of Internet of Things (IoT) technology allows for ongoing, real-time data collecting from remote and wearable medical devices, providing a more responsive and dynamic healthcare setting.Machine learning techniques are used in the system to efficiently analyse large streams of health data and to identify minor trends and anomalies that could be early indicators of deterioration.A proactive healthcare approach is supported by this sophisticated anomaly detection, which enables healthcare providers to act quickly and enhance patient outcomes.Ultimately, the combination of machine learning and IoT gives healthcare professionals predictive insights that enable quicker, more intelligent, and more individualised patient treatment.

IARJSETVol. 12(5)
Openalex Percentile: Top 82%
ECG Monitoring and Analysis
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Portable ECG device with Android Mobile Application for continuous and real-time monitoring · IARJSET (2025) | TGRS Research Map | TGRS