Juan Carlos Miangolarra‐Page

Universidad Rey Juan Carlos

Papers

2

Total Citations

6

H-Index

2

About

Juan Carlos Miangolarra-Page is a leading figure in the intersection of robotics and human movement science, with a primary focus on gait analysis and neurological rehabilitation. His work bridges the gap between controlled laboratory settings and real-world environments, demonstrating that corridor-based gait assessments can yield more ecologically valid data than traditional in-lab studies. In his most-cited 2024 paper, he validated the Azure Kinect sensor for robotics-driven gait analysis, achieving 4 citations—a strong start for a recent publication. This work highlights his commitment to making quantitative movement analysis more accessible and practical for clinical settings. Earlier, in 2015, he explored robotic therapy for gait rehabilitation in neurological conditions, laying foundational insights that continue to inform his current research. Miangolarra-Page’s contributions are pivotal for students and researchers seeking to understand how robotic tools can enhance diagnostic precision and therapeutic outcomes in human locomotion, particularly for patients with neurological impairments. His work underscores the importance of translating lab-based findings into real-world applications, advancing both the science and practice of rehabilitation engineering.

Research Focus

Key Achievements

2
H-Index
2
Papers
6
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Robotics‐driven gait analysis: Assessing Azure Kinect's performance in in‐lab versus in‐corridor environments
4 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Universidad Rey Juan Carlos

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago