Mohammed Z. Al-Faiz
Nahrain University, Al-Farahidi University, Mustansiriyah University, Alsalam University College
Papers
11
Total Citations
136
H-Index
6
About
Mohammed Z. Al-Faiz is a prominent researcher specializing in human-robot interaction, biomedical signal processing, and humanoid robotics, with a particular focus on bridging neural and muscular signals with robotic control systems. His work spans two decades of sustained contribution to the field of assistive and rehabilitative robotics, making him a notable figure in the intersection of bioengineering and artificial intelligence. Al-Faiz's most influential contributions began with his pioneering application of k-Nearest Neighbor algorithms to classify human arm movements from electromyography (EMG) signals, work that has accumulated over 33 citations and laid groundwork for intuitive human-robot interfaces. He further advanced the field through brain-computer interface (BCI) research, developing systems capable of translating EEG signals into real-time control of humanoid robotic hands across five motion classes. His Kinect-based humanoid manipulator for upper limb tracking, cited 20 times, demonstrated his versatility across sensing modalities. More recently, his 2023 review on EMG/EEG-based rehabilitation robotics for stroke patients, already garnering 31 citations, reflects his growing influence in clinical applications. His work on inverse kinematics optimization using swarm intelligence algorithms further showcases his multidisciplinary approach, combining computational intelligence with robotic design to address complex real-world challenges in assistive technology.
Research Focus
Key Achievements
Top Papers
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- 10DESIGN OF OPTIMAL INVERSE KINEMATIC SOLUTION FOR HUMANOID ROBOTIC ARMS2 citations · 2021