Improved T-wave detection in electrocardiogram signals based non-stationary wavelet transform and QRS complex cancellation with kurtosis analysis.

. The T-wave in electrocardiogram (ECG) signal has the potential to enumerate various cardiac dysfunctions in the cardiovascular system. The primary objective of this research is to develop an efficient method for detecting T-waves in ECG signals, with potential applications in clinical diagnosis and continuous patient monitoring.

Electrocardiography signal compression using non-decimated stationary wavelet transform-based technique.

. In telecardiology, the bio-signal acquisition processing and communication for clinical purposes occupies larger storage and significant bandwidth over a communication channel. Electrocardiograph (ECG) compression with effective reproductivity is highly desired.

QRS complex detection using stationary wavelet transform and adaptive thresholding.

. Electrocardiogram (ECG) signal is a record of the electrical activity of the heart and contains important clinical data about cardiovascular-related misfunctioning. The goal of the present work is to develop an improved QRS detection algorithm for the detection of heart abnormalities.