Electrocardiogram compression and optimal filtering algorithm
Mihaela Ruxandra Lascu, Dan Lascu · International Conference on Signal Processing · 2007
In this paper novel compression techniques are developed for portable heart-monitoring equipment that could also form the basis for more intelligent diagnostic systems thanks to the way the compression algorithms depend on signal classification. There are two main categories of compression which are employed for electrocardiogram signals: lossless and lossy. Design of an optimal Wiener filter is implemented to remove noise from a signal, considering that the signal is statistically stationary and the noise is a stationary random process that is statistically independent of the signal. Two programs for compression and Wiener optimal filtering are realised in MATLAB.