PhD Dissertation at the University of Basrah Explores Upper Limb Gesture Recognition Using Machine Learning
A PhD dissertation at the College of Engineering, University of Basrah, investigated upper limb gesture recognition using machine learning.
The dissertation, presented by the student Khalid Ali Abbas, aims to recognize hand gestures (HGR), which is a rapidly growing field with wide-ranging applications in human-computer interaction, robotics and assistive technologies, as well as medical sciences. This study proposes a machine learning-based algorithm for hand gesture recognition, utilizing signals from MMG, accelerometers, and gyroscopes.
The dissertation included four chapters, in which the student discussed the value of integrating mechanomyography (MMG) data with inertial data to achieve accurate gesture recognition. It also emphasized the importance of well-curated datasets and highlighted the potential for effectively deploying the proposed models in real-world applications.
Department of Media and Governmental Communication
