LiteFallNet: A lightweight deep learning model for efficient real-time fall detection
LiteFallNet offers a privacy-preserving and real-time solution for fall detection. Its accuracy, transparency, and lightweight design make it suitable for smart homes, eldercare facilities, and wearable health technologies.
Authors
- Isaac Acquah (ORCID: https://orcid.org/0000-0002-2539-7361)
- Emmanuel Owusu (ORCID: https://orcid.org/0009-0004-0591-9531)
- Michael Asare
- Benjamin Appiah Yeboah (ORCID: https://orcid.org/0009-0002-4925-7547)
Institutions
- Kwame Nkrumah University of Science and Technology (GH)
- Kwame Nkrumah University (ZM)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251386698
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00