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Sensors (Basel). 2017 Jun 12;17(6). pii: E1360. doi: 10.3390/s17061360.

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection.

Author information

1
Department of Computer Science, Kennesaw State University, Marietta, GA 30060, USA. json@kennesaw.edu.
2
Sustainable Management Strategy, Korea Expressway Corporation, Gimcheon 39660, Korea. juyoung@ex.co.kr.
3
Department of Computer Science and Engineering, Hanyang University, Ansan 15588, Korea. hkoh@hanyang.ac.kr.
4
Department of Computer and Information Sciences, Fordham University, Bronx, NY 10458, USA. mbhuiyan3@fordham.edu.
5
Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea. jbhur@korea.ac.kr.
6
Department of Computer Science and Engineering, Hanyang University, Ansan 15588, Korea. ktkang@hanyang.ac.kr.

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.

KEYWORDS:

arrhythmia detection; biomedical computing; body sensor networks; communication system security; electrocardiography; privacy of patients

PMID:
28604628
PMCID:
PMC5492002
DOI:
10.3390/s17061360
[Indexed for MEDLINE]
Free PMC Article

Conflict of interest statement

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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