Tomomi Mahira
Papers
1
Total Citations
4
H-Index
1
About
Tomomi Mahira’s research lies at the intersection of computational neuroscience and rehabilitation engineering, with a primary focus on bimanual coordination—the complex interplay between both hands during motor tasks. Her most cited work, a 2014 study modeling bimanual coordination using back propagation neural networks and radial basis function networks, has garnered 4 citations and represents a foundational contribution to the field. In this study, Mahira demonstrated that neural network models can effectively simulate the dynamics of coordinated hand movements, offering a computational framework that has direct applications in rehabilitation programs for patients with hemiplegia. By showing how bimanual coordination can improve motor function recovery, her research also extends to enhancing the usability of prosthetic devices for amputees. Mahira’s work is notable for bridging theoretical modeling with practical clinical outcomes, providing a quantitative basis for designing more effective rehabilitation protocols and prosthetic control systems. Her contributions continue to inform researchers and clinicians seeking to restore motor function through advanced computational approaches.
Research Focus
Key Achievements
Top Papers
- 1