Signal processing approach for breath prediction pattern recognition
Michał Twardochleb, Tomasz Król
M. Twardochleb, T. Król, "Signal processing approach for breath prediction pattern recognition", Journal of Theoretical and Applied Computer Science, vol. 7, no. 3, pp. 51-60, 2013.
pattern recognition, signal processing, neural network
In this paper, a new approach of signal processing for breath prediction pattern recognition is proposed and further analyses are presented. In order to extract key values from raw data, a shift from time domain to phase space has been utilized. It helped to achieve clearer peak-to-peak measurements which are crucial for breath prediction pattern recognition. Based on a special software tool for breath prediction pattern recognition several different algorithms have been compared. As a result, a reduction in error rate can be achieved when applying a new signal processing approach in comparison to the previous designs.