Repository logo
  • English
  • Deutsch
  • Français
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. CRIS
  3. Publication
  4. A systematic survey on the application of federated learning in mental state detection and human activity recognition
 

A systematic survey on the application of federated learning in mental state detection and human activity recognition

URI
https://arbor.bfh.ch/handle/arbor/44749
Version
Published
Date Issued
2024-11-27
Author(s)
Grataloup, Albin  
Kurpicz-Briki, Mascha  
Type
Article
Language
English
Abstract
This systematic review investigates the application of federated learning in mental health and human activity recognition. A comprehensive search was conducted to identify studies utilizing federated learning for these domains. The included studies were evaluated based on publication year, task, dataset characteristics, federated learning algorithms, and personalization methods. The aim is to provide an overview of the current state-of-the-art, identify research gaps, and inform future research directions in this emerging field.
DOI
https://doi.org/10.24451/dspace/11533
Publisher DOI
10.3389/fdgth.2024.1495999
Journal or Serie
Frontiers in Digital Health
Journal or Serie
Frontiers in Digital Health
ISSN
2673-253X
Publisher URL
https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2024.1495999/full
Organization
Technik und Informatik  
Institute for Data Applications and Security (IDAS)  
IDAS / Applied Machine Intelligence  
Volume
6
Publisher
Frontiers Media SA
Submitter
Kurpicz-Briki, Mascha
Citation apa
Grataloup, A., & Kurpicz-Briki, M. (2024). A systematic survey on the application of federated learning in mental state detection and human activity recognition. In Frontiers in Digital Health (Vol. 6). Frontiers Media SA. https://doi.org/10.24451/dspace/11533
File(s)
Loading...
Thumbnail Image
Download

open access

Name

fdgth-1-1495999.pdf

License
Attribution 4.0 International
Version
published
Size

2.98 MB

Format

Adobe PDF

Checksum (MD5)

cc273d3fbbfe90bdb8f2b7be4e4c974b

About ARBOR

Built with DSpace-CRIS software - System hosted and mantained by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback
  • Our institution