Abu Saleh Musa Miah
University of Aizu, Bangladesh University of Engineering and Technology
Papers
3
Total Citations
52
H-Index
3
About
Abu Saleh Musa Miah is an emerging researcher whose work sits at the dynamic intersection of human-computer interaction, biomedical signal processing, and intelligent systems. His research focuses primarily on surface electromyography (sEMG)-based gesture recognition, sensor-driven human activity recognition (HAR), and applied machine learning for assistive technologies — areas with profound implications for rehabilitation engineering, prosthetics, and accessible computing. Miah's most notable contribution, "Hand Gesture Recognition Using sEMG Signals with a Multi-Stream Time-Varying Feature Enhancement Approach" (2024), has already garnered 25 citations, demonstrating rapid community uptake for his innovative framework that addresses the persistent challenge of deploying sparse multichannel sEMG systems as practical muscle-computer interfaces. Complementing this, his HAR work incorporating ECA-Net dimensionality reduction has attracted 18 citations, showcasing his ability to advance recognition performance in privacy-sensitive, portable sensor environments. Earlier in his career, Miah demonstrated a flair for practical innovation through the development of "Metacarpus," a cost-efficient voice-controlled personal assistant robot combining Arduino hardware with machine learning — a project earning 9 citations that signals his longstanding commitment to accessible, real-world intelligent systems. Collectively, his growing citation record marks him as a promising voice in human-centered AI research.
Research Focus
Key Achievements
Top Papers
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