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 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%.

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