Internet of Hearts - Large-Scale Stochastic Network Modeling and Analysis of Cardiac Electrical Signals

Chen Kan, Hui Yang

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Scopus citations


Rapid advancement of mobile sensing and Internet-of-Things (IoT) technology provides an unprecedented opportunity to realize smart and connected health. However, large-scale IoT systems lead to big data. Realizing the full potential of big data depends, to a great extent, on the development of new human-centered computing methodologies for real-time health monitoring, on-the-fly disease diagnosis, and timely delivery of life-saving treatments. Thus far, very little has been done to develop advanced IoT technologies for smart monitoring and control of heart health. This chapter presents a new IoT technology of Mobile and E-Network Smart Health (MESH) specific to the heart, also called the Internet of Hearts (IoH), to advance the cardiac mHealth with IoT sensing, stochastic modeling and network analytics. The MESH technology will enable and assist (1) the acquisition of electrocardiogram (ECG) signals pertinent to space-time cardiac dynamics anytime, anywhere; (2) real-time management and compact representation of multilead ECG signals; (3) big data analytics in large-scale IoT contexts. In particular, we first developed a spatiotemporal approach to visualize the real-time motion of 3D VCG cardiac vectors. Then, an optimal model-based representation algorithm was developed to facilitate the compression of ECG signals and the extraction of features pertinent to disease-altered signal patterns. Further, we developed stochastic network models for real-time patient-centered monitoring, modeling, and analysis of stochastic variations between heartbeats from an individual and among human subjects. The MESH technology shows a great potential in providing an indispensable and enabling tool for realizing smart heart health and wellbeing for the population worldwide.

Original languageEnglish (US)
Title of host publicationStochastic Modeling and Analytics in Healthcare Delivery Systems
PublisherWorld Scientific Publishing Co.
Number of pages41
ISBN (Electronic)9789813220850
ISBN (Print)9789813220843
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • General Medicine


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