Key result
T-wave detection algorithm using mean and median filters demonstrates satisfactory sensitivity and predictivity on standard ECGs.
Why the study?
Accurate detection of the T-wave in ECG signals is essential for diagnosing heart activity, but existing methods require improvement.
A new algorithm utilizing mean and median filters demonstrates satisfactory performance in detecting T-waves in ECG signals.
The electrocardiogram (ECG) is one of the most used signals in the diagnosis of heart disease. It contains different waves which directly correlate to heart activity. Different methods have been used in order to detect these waves and consequently lead to heart activity diagnosis. This paper is interested more particularly to the detection of the T-wave. Such a wave represents the re-polarization state of the heart activity. The proposed approach is based on the algorithm procedure which allows the detection of the T-wave using a lot of filter including mean and median filter. The proposed algorithm is implemented and tested on a set of ECG recordings taken from, respectively, the European STT, MITBIH and MITBIH ST databases. The results are found to be very satisfactory in terms of sensitivity, predictivity and error compared to other works in the field.
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Kholkhal et al. (2014) studied Heart disease (ECG signal analysis). T-wave detection algorithm based on median filter vs. Other works in the field was evaluated on Sensitivity, predictivity and error. A proposed T-wave detection algorithm using mean and median filters demonstrated satisfactory sensitivity, predictivity, and error rates when tested on standard ECG databases.
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