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- W802903081 abstract "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 adopt complex discrete fourier transform to get spectra of audio recordings; secondly we use principal component analysis (PCA) for visualization of selected signals, and this makes it easy and intuitive to verify whether a signal contains an embolic component; finally we design 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." @default.
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- W802903081 date "2013-01-01" @default.
- W802903081 modified "2023-09-30" @default.
- W802903081 title "Complex Frequency Features for TCD Signal Analysis" @default.
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- W802903081 doi "https://doi.org/10.1007/978-3-642-29305-4_143" @default.
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