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HeartSearcher: finds patients with similar arrhythmias based on heartbeat classification
- Authors
- Park, Juyoung; Kang, Kyungtae
- Issue Date
- Dec-2015
- Publisher
- INST ENGINEERING TECHNOLOGY-IET
- Keywords
- electrocardiography; medical information systems; medical signal detection; medical signal processing; signal classification; pattern matching; diseases; patient monitoring; decision making; data mining; sorting; abstracting; clinical decision support; heartbeat classification volume reduction; abstraction; MIT-BIH arrhythmia database; heartbeat pattern similarity ranking; patient ranking; regular expression; patient typical heartbeat pattern summarisation; similar arrhythmia patient identification; arrhythmia detection; mobile phone; Holter monitor; long-term electrocardiogram data acquisition; similar arrhythmia patient search; HeartSearcher
- Citation
- IET SYSTEMS BIOLOGY, v.9, no.6, pp 303 - 308
- Pages
- 6
- Indexed
- SCIE
SCOPUS
- Journal Title
- IET SYSTEMS BIOLOGY
- Volume
- 9
- Number
- 6
- Start Page
- 303
- End Page
- 308
- ISSN
- 1751-8849
1751-8857
- Abstract
- Long-term electrocardiogram data can be acquired by linking a Holter monitor to a mobile phone. However, most systems of this variety are simply designed to detect arrhythmia through heartbeat classification, and do not provide any additional support for clinical decisions. HeartSearcher identifies patients with similar arrhythmias from heartbeat classifications, by summarising each patient's typical heartbeat pattern in the form of a regular expression, and then ranking patients according to the similarities of their patterns. Results obtained using electrocardiogram data from the MIT-BIH arrhythmia database show that this abstraction reduces the volume of heartbeat classifications by 98% on average, offering great potential to support clinical decisions.
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Related Researcher
- Kang, Kyung tae
- ERICA 소프트웨어융합대학 (DEPARTMENT OF ARTIFICIAL INTELLIGENCE)