Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network
This research proposes a new method to detect R-peaks in electrocardiogram by using the prediction value from adaptive linear neuron (ADALINE) artificial neural network. With this aim, the weights of four input neurons in ADALINE are updated for each encoded ECG vector-segment and the value of an ou...
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EDP Sciences
2016-01-01
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| Series: | MATEC Web of Conferences |
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| Online Access: | http://dx.doi.org/10.1051/matecconf/20165410001 |
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doaj-0ec1bf3e76ca4ef2b3e33bf340267a112021-08-11T14:29:26ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01541000110.1051/matecconf/20165410001matecconf_mimt2016_10001Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural NetworkKim Jeong-HwanPark Sang-EunJeung Gyeo-WunKim Kyeong-SeopThis research proposes a new method to detect R-peaks in electrocardiogram by using the prediction value from adaptive linear neuron (ADALINE) artificial neural network. With this aim, the weights of four input neurons in ADALINE are updated for each encoded ECG vector-segment and the value of an output neuron is compared with the actual ECG followed by applying finite impulse response filter. Our simulated experiments with the MIT-BIH ECG database that represents the long-term recordings from the heart disease patients show that our proposed algorithm can detect R-peaks in ECG data with the accuracy of more than 99%.http://dx.doi.org/10.1051/matecconf/20165410001ecgr-peakneural networkadalinearrhythmiapremature ventricular contractionfinite impulse response filtermit-bit database |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Kim Jeong-Hwan Park Sang-Eun Jeung Gyeo-Wun Kim Kyeong-Seop |
| spellingShingle |
Kim Jeong-Hwan Park Sang-Eun Jeung Gyeo-Wun Kim Kyeong-Seop Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network MATEC Web of Conferences ecg r-peak neural network adaline arrhythmia premature ventricular contraction finite impulse response filter mit-bit database |
| author_facet |
Kim Jeong-Hwan Park Sang-Eun Jeung Gyeo-Wun Kim Kyeong-Seop |
| author_sort |
Kim Jeong-Hwan |
| title |
Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network |
| title_short |
Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network |
| title_full |
Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network |
| title_fullStr |
Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network |
| title_full_unstemmed |
Detection of R-Peaks in ECG Signal by Adaptive Linear Neuron (ADALINE) Artificial Neural Network |
| title_sort |
detection of r-peaks in ecg signal by adaptive linear neuron (adaline) artificial neural network |
| publisher |
EDP Sciences |
| series |
MATEC Web of Conferences |
| issn |
2261-236X |
| publishDate |
2016-01-01 |
| description |
This research proposes a new method to detect R-peaks in electrocardiogram by using the prediction value from adaptive linear neuron (ADALINE) artificial neural network. With this aim, the weights of four input neurons in ADALINE are updated for each encoded ECG vector-segment and the value of an output neuron is compared with the actual ECG followed by applying finite impulse response filter. Our simulated experiments with the MIT-BIH ECG database that represents the long-term recordings from the heart disease patients show that our proposed algorithm can detect R-peaks in ECG data with the accuracy of more than 99%. |
| topic |
ecg r-peak neural network adaline arrhythmia premature ventricular contraction finite impulse response filter mit-bit database |
| url |
http://dx.doi.org/10.1051/matecconf/20165410001 |
| work_keys_str_mv |
AT kimjeonghwan detectionofrpeaksinecgsignalbyadaptivelinearneuronadalineartificialneuralnetwork AT parksangeun detectionofrpeaksinecgsignalbyadaptivelinearneuronadalineartificialneuralnetwork AT jeunggyeowun detectionofrpeaksinecgsignalbyadaptivelinearneuronadalineartificialneuralnetwork AT kimkyeongseop detectionofrpeaksinecgsignalbyadaptivelinearneuronadalineartificialneuralnetwork |
| _version_ |
1721210900972568576 |