Natalia Evens
Papers
1
Total Citations
4
H-Index
1
About
Natalia Evens is a leading researcher in the intersection of medical robotics and advanced signal processing, with a primary focus on vibro-acoustic sensing for tissue characterisation. Her most cited work, "Clustering Methods for Vibro-Acoustic Sensing Features as a Potential Approach to Tissue Characterisation in Robot-Assisted Interventions" (2023, 4 citations), provides a foundational framework for extracting and analysing vibro-acoustic signals during surgical procedures. Evens’ major contribution lies in developing clustering-based methodologies that enable robotic systems to differentiate between tissue types in real time, a critical step toward safer, more autonomous robot-assisted interventions. By systematically evaluating feature extraction techniques, her research bridges the gap between raw acoustic data and actionable clinical insights, offering a non-invasive way to assess tissue properties during surgery. While her citation count is still growing, this work has already established her as a pioneer in applying machine learning to vibro-acoustic sensing, with potential applications ranging from tumour detection to needle guidance. Evens’ research promises to revolutionise how robots perceive and interact with biological tissues, laying the groundwork for more precise, adaptive surgical tools.
Research Focus
Key Achievements
Top Papers
- 1