PERSPECTIVE article
Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1569887
This article is part of the Research TopicExtracting Insights from Digital Public Health Data using Artificial Intelligence, Volume IIIView all 13 articles
Harnessing Artificial Intelligence of Things (AIoT) for Cardiac Sensing: Current Advances and Network-Based Perspectives
Provisionally accepted
- 1the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- 2Faculty of Data Science, City University of Macau, Taipa, Macao, SAR China
- 3Wuhan University, Wuhan, Hubei Province, China
- 4Shanghai Jiao Tong University, Shanghai, Shanghai Municipality, China
- 5The University of Hong Kong, Pokfulam, Hong Kong, SAR China
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Background: With the rapid advancements in science and technology, artificial intelligence (AI) has become increasingly integral to various medical applications, including medical devices and assistive healthcare tools. Extensive research highlights the significant potential of AI in the development of Internet of Things (IoT)-enabled medical devices, particularly in the field of cardiac sensing.Methods: This study explores and synthesizes current advancements and future directions of AIdriven IoT applications in cardiac sensing, highlighting their significance. Utilizing a bibliometric approach, we visualize key focus areas, emerging trends, and the evolutionary trajectory of this interdisciplinary field.Results: As of December 2024, relevant literature at the intersection of IoT, cardiac sensors, and AI was systematically retrieved from the SCIE and ESCI indices. Using CiteSpace, we conducted a comprehensive visualization analysis of countries/regions, academic publications, organizations, authors, citations, and key terminologies. A total of 2,128 papers were included in the analysis.From our perspective, current advancements in AI-powered IoT cardiac sensors primarily focus on optimizing AI algorithms, such as deep learning techniques, and enhancing the functionality of smart wearable devices for precision medicine. Looking ahead, we anticipate that this field will increasingly prioritize data privacy protection, particularly in the era of large language models, to address emerging challenges and ensure sustainable growth. In summary, we need to continue harnessing the power of AI-powered IoT for cardiac sensing as part of public health strategies to enable early detection of heart diseases.
Keywords: Artificial intelligence of things (AIoT), Cardiac sensing, Edge computing, Deep learning techniques, precision medicine, scientometrics, data privacy protection, Large language models
Received: 02 Feb 2025; Accepted: 16 Jun 2025.
Copyright: © 2025 Ren, JING, Ma, Wang, He, Wang, Zhou and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Fengshi JING, Faculty of Data Science, City University of Macau, Taipa, Macao, SAR China
Yu Sun, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.