Abstract
Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan–Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities.
Highlights
Cyber physical systems have emerged as a promising paradigm for enriching the interactions between physical and cybernetic components
We have proposed a privacy-preserving intelligent ECG monitoring system for early arrhythmia detection and described its implementation
The major steps required for accurate recognition of arrhythmia are (1) the accurate detection of heartbeats and (2) defining the significant features of those heartbeats and extracting them to recognize various types of heartbeats, which involves leveraging the effectiveness of a machine learning algorithm and employing it for decision making
Summary
Cyber physical systems have emerged as a promising paradigm for enriching the interactions between physical and cybernetic components. Recent advances in sensing technology and smart devices, which are the most important devices facilitating cyber-physical systems, have drastically altered the shape of the current healthcare environment, while presenting numerous opportunities and challenges in patient monitoring and assistance. This novel paradigm enables patients to monitor their physical conditions using smart devices [1], which has been useful for chronic diseases that can become life threatening, such as high blood pressure, hypernatremia and various. Monitoring arrhythmias is of high importance, because they are an extremely common initial symptom of cardiac arrest or myocardial infarction. The position and distance of the PR interval and segment, the ST interval and segment and the QT interval and QRS complex can be used in a diagnosis [3]
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