TY - GEN
T1 - Diagnosis of ECG data for detecting cardiac disorder using DP-matching and artificial neural network
AU - Sinal, Mohamad Sabri Bin
AU - Kamioka, Eiji
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - Computational Intelligence has made a huge impact on solving many complicated problem particularly in the medical field. With the advancement of computational intelligence where the effectiveness of data analysis is at high stake, the process of classifying and interpreting data accurately based on logical reasoning in decision making is not a big issue. This study discusses the process of diagnosing cardiac disorder using computational intelligence with specific focus on the feature extraction where the attribute of identifying Normal Sinus and Atrial Fibrillation rhythms using Physionet.org database is examined. In this paper, an algorithm to diagnose the cardiac disorder based on DP-Matching will be proposed where the time and frequency domains of ECG signal segments are introduced. At the end of this paper, the performance evaluations of the proposed method will be shown with the analysis by ANN.
AB - Computational Intelligence has made a huge impact on solving many complicated problem particularly in the medical field. With the advancement of computational intelligence where the effectiveness of data analysis is at high stake, the process of classifying and interpreting data accurately based on logical reasoning in decision making is not a big issue. This study discusses the process of diagnosing cardiac disorder using computational intelligence with specific focus on the feature extraction where the attribute of identifying Normal Sinus and Atrial Fibrillation rhythms using Physionet.org database is examined. In this paper, an algorithm to diagnose the cardiac disorder based on DP-Matching will be proposed where the time and frequency domains of ECG signal segments are introduced. At the end of this paper, the performance evaluations of the proposed method will be shown with the analysis by ANN.
KW - Artificial neural network (ANN)
KW - Atrial fibrillation rhythm
KW - Dynamic programming (DP-matching)
KW - Electrocardiogram (ECG)
KW - Normal sinus rhythm
UR - http://www.scopus.com/inward/record.url?scp=84945938420&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84945938420&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-23024-5_15
DO - 10.1007/978-3-319-23024-5_15
M3 - Conference contribution
AN - SCOPUS:84945938420
SN - 9783319230238
T3 - Smart Innovation, Systems and Technologies
SP - 161
EP - 171
BT - Innovation in Medicine and Healthcare, 2015
A2 - Howlett, Robert J.
A2 - Chen, Yen-Wei
A2 - Tanaka, Satoshi
A2 - Torro, Carlos
A2 - Jain, Lakhmi C.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd KES International Conference on Innovation in Medicine and Healthcare, InMed 2015
Y2 - 11 September 2015 through 12 September 2015
ER -