Embolic Doppler ultrasound signal detection based on the principal component analysis

The Principal Component Analysis (PCA) algorithm is proposed to detect the embolic Doppler ultrasound signal. This method was applied to extract the main component of the Doppler ultrasound signal and calculate characteristic parameters. Together with the time domain method, the PCA method was used to distinguish emboli, noises and blood flow signals. Comparison experiments with 300 simulated Doppler ultrasound signals and 168 clinical cere-brovascular Doppler ultrasound signals showed that the accuracy of the emboli detection was greatly improved with the PCA approach. The minimum error rates of this detection were 2% and 5%, respectively for the simulated and clinical signals. It is concluded that the PCA method achieves a better detection performance and overcomes the limitations of common signal analysis methods in time and/or frequency domain due to the interference noise and the tradeoff between the time and frequency resolution in the spectrogram analysis. Thus the PCA method may be applied to the automated emboli detection system in the clinical environment.