  Applications of wavelet transform to the field of health care signals have
paved the way for implementing revolutionary approaches in detecting the
presence of certain abnormalities in human health patterns. There were
extensive studies carried out using primary wavelets in various signals like
Electrocardiogram (ECG), sonogram etc. with a certain amount of success. On the
other hand analysis using secondary wavelets which inherits the characteristics
of a set of variations available in signals like ECG can be a promise to detect
diseases with ease. Here a method to create a generalized adapted wavelet is
presented which contains the information of QRS pattern collected from an
anomaly sample space. The method has been tested and found to be successful in
locating the position of R peak in noise embedded ECG signal.
