Cristian Iglesias-Iglesias

Papers

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About

Cristian Iglesias-Iglesias is a leading researcher in assistive robotics and computer vision, with a focused expertise in developing autonomous systems for elderly care and fall detection. His major contributions center on creating low-cost, mobile robotic platforms that integrate RGB camera-based fallen person detection, addressing the critical need for rapid response to injuries in unsupervised elderly populations. His work demonstrates how assistive robots can autonomously patrol environments, detect falls, and even incorporate facial recognition to identify individuals, significantly reducing response times that are crucial for survival. With his most-cited paper, "Fallen People Detection Capabilities Using Assistive Robot" (2019), garnering 61 citations, and a follow-up study in 2022 receiving 35 citations, Iglesias-Iglesias has established a strong impact in the field. His research bridges the gap between affordable hardware and sophisticated monitoring systems, offering practical solutions for functional disabilities and aging populations. By combining mobile robotics with real-time vision-based detection, he has advanced the frontier of assistive technology, making autonomous care more accessible and effective.