MediVerse: A Secure and Scalable IoT-MR Framework for Real-Time Health and Performance Monitoring

Pedro H. Regalado, Tao Han

Research output: Contribution to journalArticlepeer-review

Abstract

Recent advancements in wearable and Internet of Things (IoT) technologies have yet to be fully realized in combination with Mixed Reality (MR) for comprehensive real-time health monitoring systems. This paper introduces MediVerse, a secure and scalable IoT-MR framework designed to enhance proactive health management through immersive, context-aware data visualization and real-time feedback. MediVerse employs a three-tiered architecture integrating intelligent sensors, wearable technologies, and MR interfaces to facilitate dynamic prediction and decision-making during critical healthcare scenarios. The framework addresses key challenges in latency, data throughput, interoperability, and user engagement by leveraging edge computing, adaptive compression, and AI-driven analytics. Extensive evaluations demonstrate MediVerse’s superiority, achieving a 70% latency reduction, 51% higher data throughput, and 69% lower error rates compared to conventional systems. Additionally, usability studies highlight significant improvements in user satisfaction and interaction clarity. These findings position MediVerse as a transformative solution for next-generation real-time healthcare monitoring, with adaptability to domains such as sports and education.

Original languageEnglish (US)
Pages (from-to)97511-97528
Number of pages18
JournalIEEE Access
Volume13
DOIs
StatePublished - 2025

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering

Keywords

  • EHR interoperability
  • health wearables
  • intelligent sensors
  • Internet of Things
  • latency reduction
  • mixed reality
  • network architecture
  • performance monitoring
  • real-time monitoring

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