Implementation of ECG signal processing and analysis techniques in digital signal processor based system

This work describes the implementation of wavelet-based de noising algorithm on electrocardiogram (ECG) signal and detection of important parameter such as heart rate, amplitude, timings of the ECG, etc. The algorithm is implemented in DSP (TI TMS320C67times) based starter kit (DSK) with a two-electrode ECG preamplifier. The signal from the ECG preamplifier is acquired through the Codec input of the DSP starter kit. The acquired data is subjected to signal processing techniques such as removal of power line frequencies and high frequency component removal using wavelet-denoising technique. ECG component analysis such as QRS peak detection, heart rate calculation, etc is performed using nonlinear filter technique called first order derivative and moving average filter. The performance of the algorithm (such as speed, calculation efficiency, accuracy, etc) is studied in the DSP environment as well as MATLAB environment for comparison. The results of this study reveal the potentiality of the DSP system for routine clinical use.