Open AccessHeartSearcher: finds patients with similar arrhythmias based on heartbeat classification
Author(s) -
Park Juyoung,
Kang Kyungtae
Publication year - 2015
Publication title -
iet systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 50
eISSN - 1751-8857
pISSN - 1751-8849
DOI - 10.1049/iet-syb.2015.0011
Subject(s) - heartbeat , computer science , abstraction , electrocardiography , artificial intelligence , pattern recognition (psychology) , data mining , medicine , computer security , philosophy , epistemology
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.