Carlotta Caramia
Papers
1
Total Citations
242
H-Index
1
About
Carlotta Caramia is a leading researcher at the intersection of biomedical engineering and machine learning, with a primary focus on wearable sensor technology for neurological disease assessment. Her work centers on developing non-invasive, data-driven methods to quantify movement disorders, particularly Parkinson’s disease, using inertial measurement units (IMUs). Her most cited paper, “IMU-Based Classification of Parkinson’s Disease From Gait: A Sensitivity Analysis on Sensor Location and Feature Selection” (2018, 242 citations), is a landmark study that systematically evaluates how sensor placement and feature engineering impact the accuracy of gait classification. This work has become a foundational reference for researchers designing portable, real-world monitoring systems for Parkinson’s patients. Caramia’s contributions are notable for bridging clinical practicality with rigorous computational analysis, demonstrating how miniaturized IMUs—traditionally used in navigation and robotics—can be repurposed for precision medicine. Her research has significant implications for remote patient monitoring, early diagnosis, and personalized rehabilitation strategies. Through her methodical approach to sensor optimization and feature selection, Caramia continues to shape the future of wearable health technology, making her a key figure in the growing field of digital biomarkers for neurodegenerative disorders.
Research Focus
Key Achievements
Top Papers
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