Parallelization of digital wavelet transformation of ECG signals

The advances in electronics and ICT industry for biomedical use have initiated a lot of new possibilities. However, these IoT solutions face the big data challenge where data comes with a certain velocity and huge quantities. In this paper, we analyze a situation where wearable ECG sensors stream continuous data to the servers. A server needs to receive these streams from a lot of sensors and needs to star various digital signal processing techniques initiating huge processing demands. Our focus in this paper is on optimizing the sequential Wavelet Transform filter. Due to the highly dependent structure of the transformation procedure we propose several optimization techniques for efficient parallelization. We set a hypothesis that optimizing the DWT initialization and processing part can yield a faster code. In this paper, we have provided several experiments to test the validity of this hypothesis by using OpenMP for parallelization. Our analysis shows that proposed techniques can optimize the sequential version of the code.