Study on reconstruction of rectal sensation based on wavelet packet analysis and SVM strategy

Abstract

To control anal incontinence, we have developed an artificial anal sphincter system with sensor feedback. The artificial anal sphincter system is a novel hydraulic-electric muscle which mainly comprises an artificial anal sphincter, a wireless power supply subsystem, and a rectal sensation reconstruction subsystem. To investigate the features of the patients' rectal sensation, we have developed an in vitro experimental platform of artificial anal sphincter. In vitro experiments have been performed, and demonstrate that the traditional threshold method is not suitable for predicting the time for defecation. The traditional threshold method only uses single-dimensional pressure time series which may contain a few interdependent components simultaneously. A wavelet packet analysis algorithm is employed to extract the feature vector of the rectal pressure signal, then the rectal sensation prediction model is constructed based on a support vector machine for defecation pattern recognition. The results show that the proposed method is an effective approach for the reconstruction of patients' rectal sensation.

Artificial Muscle Devices: Innovations and Prospects for Fecal Incontinence Treatment

“… 23 The thresholding, however, needs signal processing of the pressure by filtering and subsequent wavelet package analysis and support vector machine to detect a meaningful indicator for the need to defecate. 62 Besides the pressure sensors, the IR sensor detects the presence of feces in the rectum, which, however, only reliably works in vitro . 23 …”

Prediction method of human defecation based on informer audio data augmentation and improved residual network

“…Therefore, in order to solve the above difficulties, pre-defecation prediction has become a defecation care modality with great potential. Zan et al [ 3 , 4 ] proposed to use an artificial anal sphincter system to extract the feature vectors of rectal pressure signals using a wavelet packet analysis algorithm, and construct a rectal sensory prediction model for defecation pattern recognition based on a support vector mechanism. However, this method requires surgical implantation of the artificial anal sphincter into the human body, and there exists wound infection due to wire connection or pain due to battery replacement during operation, which is highly invasive and not applicable to routine nursing care.…”