Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals

Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals

This research examines the application of non-invasive acoustic analysis for detecting obstructions in vascular access (fistulas) used by kidney dialysis patients. Obstructions in these fistulas can interrupt essential dialysis treatment. In this study, we utilized a condenser microphone to capture...

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Bibliographic Details
Main Authors: Jia-Jung Wang, Alok Kumar Sharma, Shing-Hong Liu, Hangliang Zhang, Wenxi Chen, Thung-Lip Lee
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Sensors
Subjects:
hemodialysis
vascular access
fistula
deep learning
lightweight convolutional neural network (CNN)
Online Access:https://www.mdpi.com/1424-8220/24/18/5922
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