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Cardiological Signal Processing

Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks


This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We design a 1D-CNN that directly learns features from raw heart-sound signals, and a 2D-CNN that takes inputs of two-dimensional time-frequency feature maps based on Mel-frequency cepstral coefficients. We further develop a time-frequency CNN ensemble (TF-ECNN) combining the 1D-CNN and 2D-CNN based on score-level fusion of the class probabilities.

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Authors:
Chee-Ming Ting, Sh-Hussain Salleh, Hernando Ombao
Submitted On:
9 May 2019 - 3:40am
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ICASSP19Poster-May7.pdf

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[1] Chee-Ming Ting, Sh-Hussain Salleh, Hernando Ombao, "Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4162. Accessed: Sep. 15, 2019.
@article{4162-19,
url = {http://sigport.org/4162},
author = {Chee-Ming Ting; Sh-Hussain Salleh; Hernando Ombao },
publisher = {IEEE SigPort},
title = {Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks},
year = {2019} }
TY - EJOUR
T1 - Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks
AU - Chee-Ming Ting; Sh-Hussain Salleh; Hernando Ombao
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4162
ER -
Chee-Ming Ting, Sh-Hussain Salleh, Hernando Ombao. (2019). Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks. IEEE SigPort. http://sigport.org/4162
Chee-Ming Ting, Sh-Hussain Salleh, Hernando Ombao, 2019. Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks. Available at: http://sigport.org/4162.
Chee-Ming Ting, Sh-Hussain Salleh, Hernando Ombao. (2019). "Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks." Web.
1. Chee-Ming Ting, Sh-Hussain Salleh, Hernando Ombao. Short-Segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4162

Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach


Electrocardiogram (ECG) signal is a common and powerful tool to study heart function and diagnose several abnormal arrhythmias. While there have been remarkable improvements in cardiac arrhythmia classification methods, they still cannot offer acceptable performance in detecting different heart conditions, especially when dealing with imbalanced datasets. In this paper, we propose a solution to address this limitation of current classification approaches by developing an automatic heartbeat classification method using deep convolutional neural networks and sequence to sequence models.

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Authors:
Sajad Mousavi , Fatemeh Afghah
Submitted On:
7 May 2019 - 3:03pm
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poster_Patient-ECG-Heartbeat_ICASSP19-v1.pdf

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[1] Sajad Mousavi , Fatemeh Afghah, "Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3947. Accessed: Sep. 15, 2019.
@article{3947-19,
url = {http://sigport.org/3947},
author = {Sajad Mousavi ; Fatemeh Afghah },
publisher = {IEEE SigPort},
title = {Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach},
year = {2019} }
TY - EJOUR
T1 - Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach
AU - Sajad Mousavi ; Fatemeh Afghah
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3947
ER -
Sajad Mousavi , Fatemeh Afghah. (2019). Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach. IEEE SigPort. http://sigport.org/3947
Sajad Mousavi , Fatemeh Afghah, 2019. Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach. Available at: http://sigport.org/3947.
Sajad Mousavi , Fatemeh Afghah. (2019). "Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach." Web.
1. Sajad Mousavi , Fatemeh Afghah. Inter- and Intra- Patient ECG Heartbeat Classification For Arrhythmia Detection: a Sequence to Sequence Deep Learning Approach [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3947