Key result
An electrocardiogram feature extraction algorithm achieved an average variance of 0.0020 and a percentage error of 1.88% for wave peak height computation when validated with mit-db and ptb-db data.
A novel time-domain ECG feature extraction algorithm demonstrates high accuracy for wave peak height computation with low variance and percentage error.
Supports ECG algorithm development; leaves open prospective clinical validation before practice adoption.
In this work, an electrocardiogram feature extraction algorithm is developed by analysing ECG signal in time domain. At first all R peaks are determined using amplitude and slope based criteria. Base line modulation was removed from ECG signal by making the midpoint of successive R to R regions to lie on the same horizontal line and thereby adjusting the values of all intermediate points proportionately. With respect to detected QRS peak positions, other wave peaks are determined based on slope and then amplitude based search in the respective searching zone. P, Q, R, S and T wave peak positions, their onset and offset points and their heights w.r.t. the baseline are calculated. The algorithm is validated with mit-db and ptb-db ECG data files over a number of class of abnormalities, and achieved an average variance and percentage error of 0.0020 and 1.88% for wave peak height computation.
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Chatterjee et al. (2013) studied ECG abnormalities. ECG feature extraction algorithm was evaluated on Wave peak height computation (average variance and percentage error). An electrocardiogram feature extraction algorithm achieved an average variance of 0.0020 and a percentage error of 1.88% for wave peak height computation when validated with mit-db and ptb-db data.
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