IoT-Enabled Remote Patient Monitoring Systems for Cardiac Health

Authors

  • Prof. Alejandro Ramirez Dean of AI and Healthcare Research, Universidad de Buenos Aires, Argentina Author

Keywords:

IoT, remote patient monitoring, cardiac health, sensors

Abstract

The advent of Internet of Things (IoT) technology has revolutionized the healthcare industry, particularly in the realm of remote patient monitoring. This study delves into the implementation of IoT-enabled systems for remote monitoring of cardiac health parameters. By leveraging IoT devices and sensors, healthcare providers can remotely monitor crucial cardiac health metrics, such as heart rate, blood pressure, and ECG signals, in real-time. This not only enhances the quality of care but also allows for early detection of potential cardiac issues, leading to timely interventions and improved patient outcomes.

The paper begins by discussing the current landscape of cardiac health monitoring and the limitations of traditional methods. It then explores the benefits and challenges associated with IoT-enabled remote patient monitoring systems for cardiac health. The technical aspects of IoT implementation, including sensor technologies, data transmission protocols, and data security measures, are examined in detail. Additionally, the paper discusses the role of artificial intelligence (AI) and machine learning (ML) algorithms in analyzing the vast amounts of data generated by IoT devices to derive meaningful insights for healthcare providers.

Furthermore, the study investigates the regulatory and ethical considerations surrounding the implementation of IoT-enabled remote patient monitoring systems for cardiac health. It also explores the cost-effectiveness of such systems and their 

potential impact on healthcare delivery and patient outcomes. Finally, the paper concludes with a discussion on future trends and challenges in the field of IoT-enabled remote patient monitoring for cardiac health, emphasizing the need for continued research and innovation in this area.

Downloads

Download data is not yet available.

References

Reddy, Byrapu, and Surendranadha Reddy. "Evaluating The Data Analytics For Finance And Insurance Sectors For Industry 4.0." Tuijin Jishu/Journal of Propulsion Technology 44.4 (2023): 3871-3877.

Venigandla, Kamala, et al. "Leveraging AI-Enhanced Robotic Process Automation for Retail Pricing Optimization: A Comprehensive Analysis." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 361-370.

Reddy, Surendranadha Reddy Byrapu. "Big Data Analytics-Unleashing Insights through Advanced AI Techniques." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 1-10.

Downloads

Published

16-04-2023

How to Cite

[1]
Prof. Alejandro Ramirez, “IoT-Enabled Remote Patient Monitoring Systems for Cardiac Health”, Australian Journal of Machine Learning Research & Applications, vol. 3, no. 1, pp. 21–32, Apr. 2023, Accessed: Nov. 07, 2024. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/3

Similar Articles

11-20 of 47

You may also start an advanced similarity search for this article.