The convolutional neural network as a tool to classify electroencephalography data resulting from the consumption of juice sweetened with caloric or non-caloric sweeteners

The convolutional neural network as a tool to classify electroencephalography data resulting from the consumption of juice sweetened with caloric or non-caloric sweeteners

Sweetener type can influence sensory properties and consumer’s acceptance and preference for low-calorie products. An ideal sweetener does not exist, and each sweetener must be used in situations to which it is best suited. Aspartame and sucralose can be good substitutes for sucrose in passion fruit...

Full description

Bibliographic Details
Main Authors: Gustavo Voltani von Atzingen, Hubert Arteaga, Amanda Rodrigues da Silva, Nathalia Fontanari Ortega, Ernane Jose Xavier Costa, Ana Carolina de Sousa Silva
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Nutrition
Subjects:
sucrose
sucralose
aspartame
electroencephalography (EEG)
convolutional neural network (CNN)
Online Access:https://www.frontiersin.org/articles/10.3389/fnut.2022.901333/full

Internet

https://www.frontiersin.org/articles/10.3389/fnut.2022.901333/full

Similar Items