Classifying Food Items During an Eating Occasion: A Machine Learning Approach with Slope Dynamics for Windowed Kinetic Data

Classifying Food Items During an Eating Occasion: A Machine Learning Approach with Slope Dynamics for Windowed Kinetic Data

Background: Wearable devices equipped with a range of sensors have emerged as promising tools for monitoring and improving individuals’ health and lifestyle. Objectives: Contribute to the investigation and development of effective and reliable methods for dietary monitoring based on raw kinetic data...

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Bibliographic Details
Main Authors: Ileana Baldi, Corrado Lanera, Mohammad Junayed Bhuyan, Paola Berchialla, Luca Vedovelli, Dario Gregori
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Foods
Subjects:
wearable devices
dietary monitoring
acceleration data
kinetic data
random forest
food recognition
Online Access:https://www.mdpi.com/2304-8158/14/2/276
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