A novel classification technique of arteriovenous fistula stenosis evaluation using bilateral PPG analysis

Yi Chun Du, Alphin Stephanus

研究成果: Article同行評審

20 引文 斯高帕斯(Scopus)

摘要

The most common treatment for end-stage renal disease (ESRD) patients is the hemodialysis (HD). For this kind of treatment, the functional vascular access that called arteriovenous fistula (AVF) is done by surgery to connect the vein and artery. Stenosis is considered the major cause of dysfunction of AVF. In this study, a noninvasive approach based on asynchronous analysis of bilateral photoplethysmography (PPG) with error correcting output coding support vector machine one versus rest (ESVM-OVR) for the degree of stenosis (DOS) evaluation is proposed. An artificial neural network (ANN) classifier is also applied to compare the performance with the proposed system. The testing data has been collected from 22 patients at the right and left thumb of the hand. The experimental results indicated that the proposed system could provide positive predictive value (PPV) reaching 91.67% and had higher noise tolerance. The system has the potential for providing diagnostic assistance in a wearable device for evaluation of AVF stenosis.

原文English
期刊Micromachines
7
發行號9
DOIs
出版狀態Published - 2016 8月 23

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 機械工業
  • 電氣與電子工程

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