Complex Frequency Features for TCD Signal Analysis
LIU Wei-xiang
WANG Tian-fu
CHEN Si-ping
LUO Laurence
WANG Xiao-yi
摘要：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.
机标关键词：
分类号：R743(神经病学与精神病学)
论文发表日期：2017-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：7( 17-23 )
英文信息