Philippa Doherty
Papers
1
Total Citations
9
H-Index
1
About
Philippa Doherty is a pioneering researcher at the intersection of neuroscience, machine learning, and surgical robotics. Her primary research areas include surgical gesture recognition, brain-computer interfaces, and network neuroscience. Doherty's most notable contribution is her innovative work on using electroencephalogram (EEG) signals as input for machine learning and network neuroscience algorithms to detect surgical hand gestures. This approach offers a novel pathway for automated, targeted surgical skill assessment and feedback during robot-assisted surgery (RAS), potentially transforming surgical training by moving beyond traditional video or kinematic data. Her 2021 paper on this topic has garnered 9 citations, establishing a foundation for non-invasive neural monitoring in surgical contexts. By integrating EEG with advanced computational methods, Doherty addresses critical gaps in objective skill evaluation, paving the way for more precise and adaptive training systems. Her work exemplifies how neuroscience and artificial intelligence can converge to enhance human performance in high-stakes medical environments, making her a rising voice in the future of surgical education and human-machine interaction.
Research Focus
Key Achievements
Top Papers
- 1