Papers
3
Total Citations
24
H-Index
2
About
Sauvik Das Gupta is a researcher at the intersection of haptics, biomedical signal processing, and intelligent robotic control. His work focuses on decoding human intent and motion from physiological signals, with a primary emphasis on using surface Electromyography (sEMG) to estimate hand force and arm joint angles through Artificial Neural Networks. These contributions are foundational for advancing applications in rehabilitation robotics, telepresence surgery, virtual reality, and human-robot interaction. His most-cited paper, "Estimation of hand force from surface Electromyography signals using Artificial Neural Network" (2012, 14 citations), proposes a method to translate muscle activity into force feedback, a critical challenge in haptic technology. He further extended this work by estimating arm joint angles from sEMG (2013), offering a non-invasive approach to motion analysis. Beyond biomedical signals, Das Gupta has explored computer vision for embedded systems, developing an image-processing-based object tracking system for robotic control using MATLAB (2016, 8 citations), with applications in smart environments. His research uniquely bridges the gap between human physiology and machine actuation, demonstrating a sustained interest in making robots more responsive to natural human cues.
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