Giacomo Siri
Papers
2
Total Citations
61
H-Index
2
About
Giacomo Siri is a leading researcher at the intersection of geriatric medicine and robotic rehabilitation, whose work is redefining how we predict and prevent falls in older adults. His primary research areas include fall-risk assessment, multifactorial predictive modeling, and the application of robotic platforms for balance evaluation. Siri’s major contribution is the development and validation of a robotic multifactorial fall-risk predictive model, a groundbreaking tool that integrates clinical, functional, and robotic sensor data to identify high-risk individuals in community-dwelling older populations. This work, published in 2020, has already garnered 57 citations, underscoring its impact on proactive geriatric care. Additionally, his 2018 study on the Hunova robot—which analyzes trunk parameters under static and dynamic balance conditions—pioneers the use of robotic systems for objective, real-time balance assessment. By translating complex biomechanical data into actionable clinical insights, Siri is helping shift fall prevention from reactive to predictive, offering a scalable, technology-driven solution to a pressing public health challenge. His research is essential reading for students and professionals in gerontology, rehabilitation engineering, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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