Digital Twin System for Realistic Radar Optimization in Healthcare Monitoring

This paper presents a digital twin system for radarbased healthcare monitoring applications. Unlike traditional simulations that focus on individual components, this system replicates the complete radar setup, including antenna designs, circuits, environmental factors, and human movements. By simulating real-world scenarios, such as people moving in healthcare spaces, it offers valuable insights for optimizing radar parameters. The results demonstrate improved performance in applications like fall detection and people counting, while reducing deployment risks and costs. This approach supports scalable and adaptable radar solutions for complex healthcare environments.

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Publication Details

Published
2025-07-20
DOI
https://doi.org/10.1109/antem64578.2025.11114146
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
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article

Digital Twin System for Realistic Radar Optimization in Healthcare Monitoring

Arien Sligar, Omar M. Ramahi, George Shaker, Ahmed N. Sayed et al.
Healthcare Systems and Public Health
article

Digital Twin System for Realistic Radar Optimization in Healthcare Monitoring

Arien Sligar, Omar M. Ramahi, George Shaker, Ahmed N. Sayed, ABDELRAHMAN ELBADRAWY, Sebastian Ratto
article en

Abstract

This paper presents a digital twin system for radarbased healthcare monitoring applications. Unlike traditional simulations that focus on individual components, this system replicates the complete radar setup, including antenna designs, circuits, environmental factors, and human movements. By simulating real-world scenarios, such as people moving in healthcare spaces, it offers valuable insights for optimizing radar parameters. The results demonstrate improved performance in applications like fall detection and people counting, while reducing deployment risks and costs. This approach supports scalable and adaptable radar solutions for complex healthcare environments.

University of Waterloo (CA), Ansys (United States) (US)
Openalex Percentile: Top 71%
Healthcare Systems and Public Health
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Digital Twin System for Realistic Radar Optimization in Healthcare Monitoring — Arien Sligar, Omar M. Ramahi, et al. · (2025) | TGRS Research Map | TGRS