ArticleSensors (Basel, Switzerland)2018
Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 107 citations in OpenAlex.
- Artificial Intelligence and Sensing Technologies for Vascular Access in Hemodialysis: A Narrative Review.Sensors (Basel, Switzerland) · 2026Review
- Experimental Setup for the Validation of Photoplethysmography Devices for the Evaluation of Arteriovenous Fistulas.Bioengineering (Basel, Switzerland) · 2025Article
- Reliable Stenosis Detection Based on Thrill Waveform Analysis Using Non-Contact Arteriovenous Fistula Imaging.Sensors (Basel, Switzerland) · 2024Article
- A tailored and rapid approach for ozonation catalyst design.Environmental science and ecotechnology · 2023Article
- Development of prediction models to estimate extubation time and midterm recovery time of ophthalmic patients undergoing general anesthesia: a cross-sectional study.BMC anesthesiology · 2023Article
- Article
- Fringe Detection and Displacement Sensing for Variable Optical Feedback-Based Self-Mixing Interferometry by Using Deep Neural Networks.Sensors (Basel, Switzerland) · 2022Article
- Quantification and Visualization of Reliable Hemodynamics Evaluation Based on Non-Contact Arteriovenous Fistula Measurement.Sensors (Basel, Switzerland) · 2022Article
- Improving breast cancer prediction using a pattern recognition network with optimal feature subsets.Croatian medical journal · 2021Article
- Portable Interactive Pulse Tactile Recorder and Player System.Sensors (Basel, Switzerland) · 2021Article
- Development of hydrophobic paper substrates using silane and sol-gel based processes and deriving the best coating technique using machine learning strategies.Scientific reports · 2021Article
- Soft Sensors in the Primary Aluminum Production Process Based on Neural Networks Using Clustering Methods.Sensors (Basel, Switzerland) · 2019Article
- Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device.Sensors (Basel, Switzerland) · 2019Article
- Current progress of photoplethysmography and SPOBiomedical engineering letters · 2019Review
- A Portable, Wireless Photoplethysomography Sensor for Assessing Health of Arteriovenous Fistula Using Class-Weighted Support Vector Machine.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds monitoring patients. The mean and variance of Rising Slope (RS) and Falling Slope (FS) values between before and after HD treatment was used as the major features to classify AVF stenosis. Multilayer perceptron neural networks (MLPN) training algorithms are implemented for this analysis, which are the Levenberg-Marquardt, Scaled Conjugate Gradient, and Resilient Back-propagation, to identify the degree of HD patient stenosis. Eleven patients were recruited with mean age of 77 ± 10.8 years for analysis. The experimental results indicated that the variance of RS in the HD hand between before and after treatment was significant difference statistically to stenosis (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.