TY - GEN
T1 - Investigation Reinforcement Learning Method for R-Wave Detection on Electrocardiogram Signal
AU - Insani, Asep
AU - Jatmiko, Wisnu
AU - Sugiarto, Anto Tri
AU - Jati, Grafika
AU - Wibowo, Suryo Adhi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - One of the essential things in recording electrocardiography (ECG) signals is R-wave detection. R-wave is a main component in the QRS wave, where it used for the diagnosis of heart rhythm irregularities and to calculate heart rate variability. On the other hand, Reinforcement Learning (RL) method has been proved that gives an excellent performance for games, network and stock market prediction. Based on this fact, in this paper, we want to investigate the RL for R-wave detection on the ECG signal. For the detection, the lower frequency is removed then we calculate the candidate of the peak, initialize Q-State-Action (QSA) table, peak detection, calculate reward and update the QSA table, respectively. Based on the experiment using the MIT-BIH dataset, the best accuracy of the proposed method is 86.8%, which calculated from alpha and gamma parameters are 0.1 and 0.9, respectively.
AB - One of the essential things in recording electrocardiography (ECG) signals is R-wave detection. R-wave is a main component in the QRS wave, where it used for the diagnosis of heart rhythm irregularities and to calculate heart rate variability. On the other hand, Reinforcement Learning (RL) method has been proved that gives an excellent performance for games, network and stock market prediction. Based on this fact, in this paper, we want to investigate the RL for R-wave detection on the ECG signal. For the detection, the lower frequency is removed then we calculate the candidate of the peak, initialize Q-State-Action (QSA) table, peak detection, calculate reward and update the QSA table, respectively. Based on the experiment using the MIT-BIH dataset, the best accuracy of the proposed method is 86.8%, which calculated from alpha and gamma parameters are 0.1 and 0.9, respectively.
KW - Electrocardiography (ECG)
KW - MIT-BIH Data
KW - R-Wave Detection
KW - Reinforcement Learning
UR - http://www.scopus.com/inward/record.url?scp=85083328082&partnerID=8YFLogxK
U2 - 10.1109/ISRITI48646.2019.9034649
DO - 10.1109/ISRITI48646.2019.9034649
M3 - Conference contribution
AN - SCOPUS:85083328082
T3 - 2019 2nd International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2019
SP - 420
EP - 423
BT - 2019 2nd International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2019
A2 - Wibowo, Ferry Wahyu
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2019
Y2 - 5 December 2019 through 6 December 2019
ER -