Embolic detection is very important to the early diagnosis of vessel disease. The Doppler ultrasound technique is one of the common methods to detect the emboli non-invasively. When the emboli pass through the sample ...Embolic detection is very important to the early diagnosis of vessel disease. The Doppler ultrasound technique is one of the common methods to detect the emboli non-invasively. When the emboli pass through the sample volume of the Doppler ultrasound instrument, there exist high intensity transient Doppler signals. Thus the emboli can be detected directly from the variation of Doppler signal amplitude. Since there may be some disturbance in the system, this general detection method has great limitation. To improve the accuracy of emboli auto-detection, several novel methods are studied to obtain the sensitive characteristic of the emboli signals using the new signal processing theories.展开更多
In this paper, we report on using pattern recognition techniques for embolic signal(ES) detection based on transcranial doppler ultrasound(TCD) audio data collected via machine EMS-9(from Shenzhen Delicate Electronics...In this paper, we report on using pattern recognition techniques for embolic signal(ES) detection based on transcranial doppler ultrasound(TCD) audio data collected via machine EMS-9(from Shenzhen Delicate Electronics, Co. Ltd).Firstly, we adopted complex discrete fourier transform to get spectra of audio recordings; secondly, we used principal component analysis(PCA) for the visualization of selected signals, which makes it easy and intuitive to verify whether a signal contains an embolic component; finally we designed the classifier with support vector machines(SVM) for detection. With contrast to traditional methods of ES detection systems, the proposed approach considers two channel signals from the audio data collected by single transducer, and there is no predefined features for classification. The primary experimental results on real data are promising.展开更多
文摘Embolic detection is very important to the early diagnosis of vessel disease. The Doppler ultrasound technique is one of the common methods to detect the emboli non-invasively. When the emboli pass through the sample volume of the Doppler ultrasound instrument, there exist high intensity transient Doppler signals. Thus the emboli can be detected directly from the variation of Doppler signal amplitude. Since there may be some disturbance in the system, this general detection method has great limitation. To improve the accuracy of emboli auto-detection, several novel methods are studied to obtain the sensitive characteristic of the emboli signals using the new signal processing theories.
基金SZU R/D Fundgrant number:201054+3 种基金Natural Science Foundation of Shenzhengrant number:JC201005280685AKey Program of National Natural Science Foundation of Chinagrant number:61031003
文摘In this paper, we report on using pattern recognition techniques for embolic signal(ES) detection based on transcranial doppler ultrasound(TCD) audio data collected via machine EMS-9(from Shenzhen Delicate Electronics, Co. Ltd).Firstly, we adopted complex discrete fourier transform to get spectra of audio recordings; secondly, we used principal component analysis(PCA) for the visualization of selected signals, which makes it easy and intuitive to verify whether a signal contains an embolic component; finally we designed the classifier with support vector machines(SVM) for detection. With contrast to traditional methods of ES detection systems, the proposed approach considers two channel signals from the audio data collected by single transducer, and there is no predefined features for classification. The primary experimental results on real data are promising.
