Online electrophysiological spike discrimination with wavelet-fractal signatures

作     者：易东 严中红 郑永丽 李辉智 

作者机构：Department of Health Statistics Third Military Medical University Institute of Biotechnology University of Chongqing Technology and Industry Southwest University of Political Science and Law 

出 版 物：《Journal of Medical Colleges of PLA(China)》 (中国人民解放军军医大学学报（英文版）)

年 卷 期：2006年第21卷第6期

页      面：383-387页

学科分类：1002[医学-临床医学] 100204[医学-神经病学] 10[医学] 

基　　金：Supported by the National Natural Science Foundation of China (No. 60371034) 

主　　题：electrophysiological spike wavelet transform fractal 

摘      要：Objective: To study extracellular multi-neuron activity in the nervous system based on wavelet-fractal technique. Methods: The wavelet transform was employed to decompose the original signal and obtain 4 sub-patterns. The dividing fractal dimensions of these sub-patterns were computed. A knn-classier was used to classify feature vectors. Results: Not all the elements in feature vector DimDC were very powerful for this pattern recognition problem through the empirical study of noise signals. The most effective feature vector was defined as DimDC= (d3:d4) above. Conclusion:Wavelet fractal algorithm has high accuracy and provides a powerful tool for clinical application.