Kharudin Ali

Papers

Total Citations

H-Index

About

Kharudin Ali is a researcher at the forefront of assistive robotics and human-machine interaction, with a particular focus on leveraging biosignals and the Internet of Things (IoT) for control systems. His pioneering work in facial-muscle controlled robotics, detailed in his 2012 paper "Development of EMG measurement system to control mobile robot using frontalis and zygomaticus major muscles," demonstrates a novel approach to assistive technology. By capturing and interpreting electromyography (EMG) signals from facial muscles, Ali developed a system that allows users to control a mobile robot through voluntary facial expressions, a breakthrough with significant implications for individuals with severe motor disabilities. Building on this foundation, his recent 2024 work, "Control Robotic Arm Workstation Using IoT System for Education," extends his research into modern, connected learning environments. This project integrates robotic arm control with IoT infrastructure, creating an educational platform that makes advanced robotics accessible for training and experimentation. While his citation counts (3 each for these key papers) reflect a focused, emerging body of work, Ali’s contributions are notable for their practical, user-centered design, bridging the gap between biomedical signal processing and real-world robotic applications.