Meisa Kurnia
Papers
1
Total Citations
2
H-Index
1
About
Meisa Kurnia’s research lies at the intersection of machine learning and healthcare, with a focused commitment to advancing rehabilitation technologies for stroke survivors. Her most-cited work, a 2019 review on machine learning applications in assisted treadmill systems for stroke rehabilitation, critically examines how intelligent devices can harness classification and automated decision-making to improve therapeutic outcomes. Although early in her career, this contribution has garnered attention for its timely synthesis of IoT-driven innovations and clinical needs, laying groundwork for more adaptive, patient-centered rehabilitation tools. Kurnia’s scholarship reflects a deep understanding of how computational models can transform traditional physiotherapy, offering new pathways for personalized recovery. As the demand for smart healthcare solutions grows, her work signals a promising trajectory in integrating machine learning with assistive technologies, positioning her as a rising voice in the field of rehabilitation engineering and human-centered AI.
Research Focus
Key Achievements
Top Papers
- 1