Mantoo Kaiborta

Papers

Total Citations

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About

Mantoo Kaiborta is a researcher in the field of biomedical robotics and human-machine interfaces, with a primary focus on electromyographic (EMG) signal processing for prosthetic and robotic hand control. His key research areas include grasp recognition, machine learning classification, and neural signal decoding. Kaiborta’s major contribution is the development of an EMG-based grasp recognition system for a five-fingered robotic hand, where he applied a radial basis function kernel support vector machine to classify grasp types using wavelet decomposition coefficients. In a study involving six subjects, his method achieved high average recognition accuracy, demonstrating the potential for intuitive, non-invasive control of dexterous prosthetics. His most cited work, "Electromyographic Grasp Recognition for a Five Fingered Robotic Hand" (2012), has garnered 6 citations, reflecting early interest in this approach. Although his citation count is modest, his work represents a foundational step in integrating machine learning with bio-signal processing for assistive technology. Kaiborta’s research contributes to advancing human-robot interaction, particularly in restoring hand function for individuals with limb loss.