Papers
7
Total Citations
106
H-Index
3
About
Rinku Roy is a leading researcher in neural engineering and assistive robotics, specializing in brain-computer interfaces (BCI) and myoelectric control systems. Her work focuses on decoding neural signals—from electroencephalography (EEG) to motoneuron firing activities—to restore motor function for individuals with severe disabilities, including ALS and spinal cord injury. Roy’s most cited paper, “Trajectory Path Planning of EEG Controlled Robotic Arm Using GA” (53 citations), pioneered a genetic algorithm-based approach for BCI-driven robotic arm control, directly enhancing quality of life for motor-impaired patients. Her major contributions include the concurrent and continuous prediction of finger kinetics and kinematics from motoneuron activities, a breakthrough detailed in her 2022 paper (26 citations) that enables more intuitive control of robotic hands. She has also developed a generic neural network model to estimate populational neural activity for robust decoding (18 citations) and explored electro-oculogram-based vision systems for grasp assistive devices. Roy’s work bridges the gap between neural decoding and practical assistive technology, with recent studies optimizing model selection for real-time finger movement prediction. Her research has accumulated over 100 citations, establishing her as a key innovator in non-invasive neural interfaces and rehabilitation engineering.
Research Focus
Key Achievements
Top Papers
- 1Trajectory Path Planning of EEG Controlled Robotic Arm Using GA53 citations · 2016
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