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About

Shyamanta M. Hazarika is a prominent researcher whose work sits at the intersection of human-machine interaction, rehabilitation robotics, and intelligent systems. His research focuses primarily on grasp recognition and classification, prosthetics, exoskeleton design, and cognitive robotics — fields with profound implications for restoring and augmenting human motor function. Hazarika's most influential contribution lies in advancing EMG-based and multisensory grasp recognition. His 2016 work on EMG feature selection for grasp recognition (31 citations) laid important groundwork for decoding hand movements from muscle signals, while more recent studies — including GloveNet (16 citations) and tactile signal-based classification (11 citations) — demonstrate his evolution toward deep learning and multimodal sensing approaches. His development of finger exoskeletons for post-stroke rehabilitation and biomimetic prosthetic hand control further bridges laboratory research with real-world clinical need. Beyond motor rehabilitation, Hazarika has contributed to cognitive robotics through an intelligent wheelchair control architecture (11 citations) and object affordance reasoning via ontology (11 citations), reflecting the breadth of his expertise. His broader survey on robotics history and trends (10 citations) signals his role as both practitioner and educator. With consistent output across over a decade, Hazarika represents a meaningful voice in assistive technology and intelligent robotics research.