Abstract
After long-term exploration, it has been well established for the mechanisms of electrocardiogram (ECG) in health monitoring of cardiovascular system. Within the frame of an intelligent home healthcare system, our research group is devoted to researching/developing various mobile health monitoring systems, including the smart ECG interpreter. Hence, in this paper, we introduce an adaptive fuzzy ECG classifier with orientation to smart ECG interpreters. It can parameterize the incoming ECG signals and then classify them into four major types for health reference: Normal (N), Premature Atria Contraction (PAC), Right Bundle Block Beat (RBBB), and Left Bundle Block Beat (LBBB).
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Lei, W.K., Li, B.N., Dong, M.C., Vai, M.I. (2007). AFC-ECG: An Adaptive Fuzzy ECG Classifier. In: Saad, A., Dahal, K., Sarfraz, M., Roy, R. (eds) Soft Computing in Industrial Applications. Advances in Soft Computing, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70706-6_18
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DOI: https://doi.org/10.1007/978-3-540-70706-6_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70704-2
Online ISBN: 978-3-540-70706-6
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