Ekaterini Zigoura
Papers
3
Total Citations
96
H-Index
3
About
Ekaterini Zigoura is a leading researcher in geriatric rehabilitation and fall prevention, specializing in the intersection of robotics and clinical assessment. Her work focuses on developing objective, technology-driven methods to evaluate and predict fall risk in community-dwelling older adults. Zigoura’s major contribution is the creation and validation of a robotic multifactorial fall-risk predictive model, which integrates dynamic balance parameters measured by the hunova robot. This model, detailed in her most-cited paper (57 citations), offers a significant advancement over traditional subjective assessments by providing precise, quantifiable data on trunk control and postural stability. Her subsequent studies (35 citations) further demonstrate how robotic balance assessment can differentiate between older adults with varying degrees of physical impairment, enabling targeted interventions. By pioneering the use of robotic platforms for fall-risk evaluation, Zigoura has laid critical groundwork for early, personalized preventive care. Her work not only enhances clinical accuracy but also empowers older adults to maintain independence, making her a key figure in the evolution of smart, data-driven geriatric healthcare.
Research Focus
Key Achievements
Top Papers
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