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Bilateral photoplethysmography analysis for arteriovenous fistula dysfunction screening with fractional‐order feature and cooperative game‐based embedded detector
Author(s) -
Wu JianXing,
Lin ChiaHung,
Wu MingJui,
Li ChienMing,
Lim BeeYen,
Du YiChun
Publication year - 2015
Publication title -
healthcare technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.45
H-Index - 19
ISSN - 2053-3713
DOI - 10.1049/htl.2014.0090
Subject(s) - photoplethysmogram , arteriovenous fistula , detector , feature extraction , feature (linguistics) , medicine , stenosis , computer science , cardiology , artificial intelligence , biomedical engineering , radiology , computer vision , filter (signal processing) , telecommunications , linguistics , philosophy
The bilateral photoplethysmography (PPG) analysis for arteriovenous fistula (AVF) dysfunction screening with a fractional‐order feature and a cooperative game (CG)‐based embedded detector is proposed. The proposed detector uses a feature extraction method and a CG to evaluate the risk level for AVF dysfunction for patients undergoing haemodialysis treatment. A Sprott system is used to design a self‐synchronisation error formulation to quantify the differences in the changes of blood volume for the sinister and dexter thumbs’ PPG signals. Bilateral PPGs exhibit a significant difference in rise time and amplitude, which is proportional to the degree of stenosis. A less parameterised CG model is then used to evaluate the risk level. The proposed detector is also studied using an embedded system and bilateral optical measurements. The experimental results show that the risk of AVF stenosis during haemodialysis treatment is detected earlier.

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