This paper is in the following e-collection/theme issue:

Wearable Devices and Sensors (903) New Methods (963) Imaging Informatics (200) Machine Learning (1501) Instruments and Questionnaires for Nutrition and Food Intake (169) Evaluation and Research Methodology for mHealth (210) mHealth for Wellness, Behavior Change and Prevention (2922)

Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21926, first published .
Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Authors of this article:

Nooshin Bahador1 Author Orcid Image ;   Denzil Ferreira1 Author Orcid Image ;   Satu Tamminen1 Author Orcid Image ;   Jukka Kortelainen1 Author Orcid Image
Article Authors Cited by (18) Tweetations (4) Metrics

Nooshin Bahador   1 , PhD ;   Denzil Ferreira   1 , PhD ;   Satu Tamminen   1 , DSc ;   Jukka Kortelainen   1 , MD, PhD

1 Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland

Corresponding Author:

  • Nooshin Bahador, PhD
  • Faculty of Information Technology and Electrical Engineering
  • University of Oulu
  • Pentti Kaiteran katu 1
  • Oulu, FIN-90570
  • Finland
  • Phone: 358 417246274
  • Email: nooshin.bahador@oulu.fi