Sameer Shahnewaz

Nanjing University of Science and Technology

Papers

Total Citations

H-Index

About

Sameer Shahnewaz is a researcher at the forefront of assistive and rehabilitation robotics, with a primary focus on developing intuitive, wearable hand robots for post-stroke recovery. His most-cited work, "Toward Hand Pattern Recognition in Assistive and Rehabilitation Robotics Using EMG and Kinematics" (2021, 32 citations), tackles a critical bottleneck in the field: reliable pattern recognition. By integrating electromyography (EMG) signals with kinematic data, Shahnewaz has advanced the ability to decode user intent, enabling more natural and responsive control of robotic hands for daily living assistance and rehabilitation exercises. This dual-sensor approach significantly improves the accuracy of gesture classification, a key step toward making wearable hand robots practical for patients. His contributions are helping bridge the gap between human physiology and machine control, directly impacting the development of smarter, more adaptive neurorehabilitation technologies. With his work gaining traction in the robotics community, Shahnewaz is establishing himself as a promising voice in human-robot interaction and motor recovery.