Breakthrough in Bone Healing Monitoring: How RF Sensing and AI are Revolutionising Fracture Care
Bone fractures are a prevalent musculoskeletal injury, with healing complications posing a significant healthcare burden. Traditional monitoring methods often rely on X-rays, which are ionizing and provide limited information on healing progress. This article explores a novel approach using radiofrequency (RF) sensing and artificial intelligence (AI) for non-invasive and real-time monitoring of bone healing. We discuss the underlying principles of RF sensing for bone assessment, the role of AI in data analysis and image reconstruction, and the potential advantages of this technique over conventional methods. Finally, we address current challenges and future directions for RF sensing and AI in fracture care.
Authors
- Joaquim Bastos (ORCID: https://orcid.org/0000-0001-8182-5087)
- Rami Qahwaji
- Ahmad Aldelemy (ORCID: https://orcid.org/0000-0002-3547-7461)
- John G. Buckley (ORCID: https://orcid.org/0000-0002-4085-4743)
- Raed A. Abd‐Alhameed (ORCID: https://orcid.org/0000-0003-2972-9965)
- Aslan Nouri Moqadam (ORCID: https://orcid.org/0009-0009-4817-9592)
- Prince O. Siaw
- Ebenezer Adjei
- Maryann Hardy
- Peter Twig
Institutions
- University of Bradford (GB)
- University of Tabriz (IR)
- Instituto de Telecomunicações (PT)
Publication Details
- Published
- 2024-10-21
- DOI
- https://doi.org/10.1109/camad62243.2024.10943005
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.12