Rectal Perception Function Rebuilding Based on Wavelet Packet Analysis and Support Vector Machine
Received date: 2011-12-01
Revised date: 2012-05-16
Online published: 2012-09-25
To solve the problem of rectal perception loss caused by anal incontinence, a rectal perception function rebuilding method is proposed based on wavelet packet analysis and support vector machine (SVM). By analyzing the characteristics of human rectum, high-amplitude propagated contractions (HAPC) in rectal contractions are used to indicate an urge to defecate. Feature extraction of rectal pressure is done using wavelet packet analysis, and take L2 norm and standard deviation of decomposition nodes as eigenvector. A rectal perception prediction model is trained using SVM. By extracting eigenvector from rectal pressure signal, penalty factors and slack variables are cross validated and optimized. Then the trained model is used to predict the urge to defecate. Prediction accuracy of the feed-forward neural network and SVM with different kernel functions is compared. Experiment results show that the proposed method is effective to rebuild patients’ rectal perception function.
JIANG En-Yu, Zan-Feng, Shu-Xiao-Jin, Shao-Yong, Wang-Xiao-Hua . Rectal Perception Function Rebuilding Based on Wavelet Packet Analysis and Support Vector Machine[J]. Journal of Applied Sciences, 2012 , 30(5) : 538 -544 . DOI: 10.3969/j.issn.0255-8297.2012.05.016
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