RT info:eu-repo/semantics/conferenceObject
T1 Towards Intelligent and Immersive Healthcare: Edge-AI, IoMT, and Digital Twins in the Metaverse
A1 Marco Detchart, Cédric
A1 Curiel Herrera, Leticia Elena
A1 Urda Muñoz, Daniel
A1 Rincón Arango, Jaime Andrés
K1 Edge-AI
K1 Cognitive assistant
K1 Healthcare
K1 IoMT
K1 Virtual reality
K1 ML
K1 Tecnología médica
K1 Medical technology
K1 Salud
K1 Health
K1 Inteligencia artificial
K1 Artificial intelligence
AB The integration of emerging technologies such as Virtual Reality (VR), Artificial Intelligence (AI), and the Internet of Medical Things (IoMT) is transforming personalized healthcare. This work presents an innovative system that leverages the concept of digital health twins, IoMT devices, and immersive VR environments to enable real-time remote monitoring of biomedical signals (ECG, PPG, blood pressure, oxygen saturation, among others). Captured data is transmitted to centralized servers where neural networks analyze health parameters, allowing early anomaly detection and dynamic adjustment of treatment plans. The system also incorporates a cloud-connected assistant based on embedded hardware, enhancing continuous patient monitoring and interaction within both physical and virtual environments. To safeguard sensitive medical data, robust cybersecurity measures are integrated, including encrypted communications, authentication protocols, and local storage failover in case of connectivity loss. This multi-layered approach ensures patient confidentiality and system resilience. By improving diagnostic accuracy, optimizing patient experiences, and extending healthcare access to remote areas, this solution contributes to reducing overcrowding in medical facilities and enabling more equitable healthcare delivery.
PB Springer
SN 978-3-032-10486-1
YR 2025
FD 2025-11
LK https://hdl.handle.net/10259/11162
UL https://hdl.handle.net/10259/11162
LA eng
NO Trabajo presentado en: International Conference on Intelligent Data Engineering and Automated Learning 2025, realizado del 13 al 15 de noviembre de 2025, en Jaén (España)
NO This work is supported by PID2022-136627NB-I00 project funded by MCIN/AEI/10.13039/501100011033/FEDER and by Fundación Mutua Madrileña through the 2025 Call for Medical Research Grants (AP-22016/2025).
DS Repositorio Institucional de la Universidad de Burgos
RD 28-abr-2026