Kolmogorov–Arnold and Long Short-Term Memory Convolutional Network Models for Supervised Quality Recognition of Photoplethysmogram Signals

Kolmogorov–Arnold and Long Short-Term Memory Convolutional Network Models for Supervised Quality Recognition of Photoplethysmogram Signals

Photoplethysmogram (PPG) signals recover key physiological parameters as pulse, oximetry, and ECG. In this paper, we first employ a hybrid architecture combining the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) for the analysis of PPG signals to enable an automated quality re...

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Bibliographic Details
Main Authors: Aneeqa Mehrab, Michela Lapenna, Ferdinando Zanchetta, Angelica Simonetti, Giovanni Faglioni, Andrea Malagoli, Rita Fioresi
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Entropy
Subjects:
PPG signals
convolutional neural networks
long short-term memory
Kolmogorov–Arnold networks
Online Access:https://www.mdpi.com/1099-4300/27/4/326
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https://www.mdpi.com/1099-4300/27/4/326

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