Micro EMG: Imaging the Inner Structure of the Human Muscle Guided by a Deep Learning Approach to Muscle Fiber Localization
The presentation will discuss our latest development of a multi-channel Electromyography needle. Using flexible electrodes technology, 64 electrodes are placed in a custom design pattern to maximize the information available for the localization of muscle fibres in human. After the motor units are isolated, an unsupervised stacked denoising auto-encoder is employed to further decompose the motor unit into its constituent muscle fibres leading to localization of fibres with 100 micro meter accuracy of over 50 fibres simultaneously. This will potentially revolutionize neurophysiology and the diagnosis of neuromuscular disease.
Dr. Awwad Shiekh Hasan is a senior research associate in computational neuroscience at Newcastle University. His research is focused on the use of computational modelling to expand our understanding of the fundamental neural mechanisms of cognition and perception, and how that understanding can be translated into action. He worked in several interdisciplinary areas including Brain-Computer Interfaces, neural imaging, and most recently the development of medical devices. He has a British patent and has published extensively in leading scientific outlets in neuroscience, and machine learning.