Papers
3
Total Citations
11
H-Index
2
About
Dr. Sriparna Saha is a rising researcher in the interdisciplinary field of brain-computer interfaces (BCI) and rehabilitation robotics, with a focused expertise in decoding electroencephalogram (EEG) signals for assistive technology. Her primary contributions lie in developing non-invasive, EEG-driven control systems that enable individuals with motor impairments—particularly those requiring wheelchair mobility—to navigate their environments using thought alone. In her most cited work (2022, 7 citations), she pioneered an automatic approach to control wheelchair movement for rehabilitation, demonstrating how modern BCI systems can translate brain signals into robotic commands. She has further advanced this domain by introducing hybrid EEG-induced robot navigation (2023, 2 citations) and a novel rehabilitation framework that employs motor imagery and fuzzy vector quantization to refine wheelchair control (2023, 2 citations). Dr. Saha’s work is notable for its practical, user-centered design, aiming to enhance quality of life for disabled individuals. With a growing citation footprint, she is establishing herself as a key contributor to the intersection of neural engineering and rehabilitative robotics, offering promising pathways toward more intuitive and accessible assistive technologies.
Research Focus
Key Achievements
Top Papers
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