Anastasios Tzepkenlis
Papers
2
Total Citations
3
H-Index
1
About
Anastasios Tzepkenlis is a researcher at the forefront of integrating artificial intelligence with robotic rehabilitation, focusing on transforming post-stroke recovery through data-driven precision. His work centers on two key areas: developing machine learning models for clinical outcome prediction and creating robust data management frameworks for AI-driven decision support systems. In his most cited work, Tzepkenlis demonstrates how identifying critical feature groups from kinematic and force interaction data can personalize therapy, enabling clinicians to dynamically adjust treatments based on individual patient needs. His research on systematic data management addresses the challenge of handling the high-resolution, finely grained data generated by robotic rehabilitation setups, ensuring that AI systems can effectively process and leverage this information for actionable clinical insights. With 2 and 1 citations respectively for his 2025 publications, Tzepkenlis is establishing a foundation for next-generation rehabilitation technologies. His contributions are particularly notable for bridging the gap between raw sensor data and practical decision support, promising to enhance therapeutic effectiveness and patient outcomes in post-stroke care.
Research Focus
Key Achievements
Top Papers
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- 2