Asha Vijayan
Papers
7
Total Citations
73
H-Index
6
About
Asha Vijayan is a pioneering researcher at the intersection of neuroscience, machine learning, and affordable robotics. Her work centers on developing brain-computer interfaces (BCI) and neuro-inspired control algorithms to make robotic prosthetics and educational tools accessible, particularly in developing economies. Her most cited paper (19 citations) demonstrates how non-invasive EEG signals can control low-cost prosthetic arms, a breakthrough for humanitarian applications. Vijayan has also advanced robotic control by replacing traditional kinematics with machine learning classifiers like SVM and Naïve Bayes, and by modeling cerebellar spiking neural networks for precise trajectory prediction. Her open-source, remotely controlled robotic articulator (12 citations) serves as an online education platform, bridging the gap in hands-on robotics training where hardware is scarce. With over 70 cumulative citations across her publications, Vijayan’s contributions are notable for their dual impact: advancing fundamental neuro-robotic theory while delivering practical, low-cost solutions for the physically challenged and for STEM education in resource-limited settings.
Research Focus
Key Achievements
Top Papers
- 1Neural Control using EEG as a BCI Technique for Low Cost Prosthetic Arms19 citations · 2014
- 2Classifying Movement Articulation for Robotic Arms via Machine Learning12 citations · 2013
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