Ismail Mohd Khairuddin
Universiti Malaysia Pahang Al-Sultan Abdullah, International Islamic University Malaysia
Papers
12
Total Citations
134
H-Index
6
About
Ismail Mohd Khairuddin is a multidisciplinary researcher whose work sits at the intersection of biomedical engineering, robotics, and machine learning, with a particular focus on rehabilitation technology and human-robot interaction. His most influential contribution, "The Classification of Movement Intention through Machine Learning Models" (2021, 57 citations), established significant advances in electromyography (EMG) signal processing, identifying critical time-domain features that enable accurate prediction of human motor intention — a cornerstone capability for next-generation assistive and rehabilitation robotics. Building on this foundation, his research on lower limb exoskeletons and active force control (2017, 23 citations) has helped address the growing global demand for accessible rehabilitation solutions, particularly for stroke and hemiplegic patients. His earlier k-NN-based motion classification work (2019, 14 citations) further cemented his expertise in pattern recognition applied to human movement. Beyond rehabilitation, Khairuddin has demonstrated notable versatility, contributing to quadrotor aerial vehicle modelling, agricultural object detection using transfer learning for chili plant classification, and wood texture recognition using fuzzy classifiers. Collectively accumulating over 130 citations, his body of work reflects a sustained commitment to translating intelligent systems research into practical, human-centred applications across healthcare, agriculture, and autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 3Classifying Motion Intention from EMG signal: A k-NN Approach14 citations · 2019
- 4Modelling and PID Control of a Quadrotor Aerial Robot11 citations · 2014
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- 10Articulated Robot Arm2 citations · 2021