Model of real time biomedical signal transmission using wavelet based adaptive thresholding

In real time, remote biomedical signal (such as ECG, EEG, etc.) monitoring systems, continuous fast transmission of the signal is of utmost importance. In this paper, we propose a time-efficient algorithm for compression of ECG signal which involves decomposition of signal into coefficients of time-frequency domain. The proposed algorithm uses an adaptive frame positioning technique with an iterative thresholding selection process based on the detailed coefficients of discrete wavelet transform (DWT). Various parameters used in our proposed Vertical Frame Sliding Method (VFSM) algorithm are optimised to yield better performance. The performance of our algorithm have been evaluated in terms of Compression Ratio (CR) and Percentage root mean square deviation (PRD).