The President of Northern Technical University attends a master’s thesis discussion at the Mosul Technical Engineering College, which discussed the prediction of muscle fatigue based on electromyography signals and deep learning algorithms.

As a support of graduate students, the President of Northern Technical University, Prof. Dr. Alia Abbas Ali Al-Attar, attended the discussion of the technical master’s thesis, specializing in medical device engineering technology, entitled:
(Prediction of Muscle Fatigue Based on Electromyography Signals and Deep Learning Algorithms)
The thesis, presented by researcher Zainab Mahmoud Tariq, presented a comprehensive study on processing and analyzing electromyography (sEMG) signals to detect and predict muscle fatigue in real time. It also utilized the capabilities of artificial intelligence and deep learning algorithms by using the MOMENT model, which is designed to process time series and is characterized by its ability to handle limited data sets. The thesis aimed to build a system based on sEMG signal analysis to instantly predict muscle fatigue. This would contribute to several areas, including supporting prosthetic limb stability, reducing sports injuries, and accelerating treatment by improving medical rehabilitation protocols. The results also demonstrated that combining RMS and MNF is effective in tracking changes associated with fatigue.
The thesis recommended increasing the number of participants and studying features to expand the database, adopting lightweight electronic components to make the system more wearable, and testing the algorithms with various types of sEMG sensors. It also recommended continuing to develop the algorithms used to improve their accuracy and efficiency.
The discussion committee consisted of:
– Asst. Prof. Dr. Firas Mahmoud Mustafa, Chairman
– Asst. Prof. Mazen Nazir Farhan, Member
– Asst. Dr. Sinan Salem Muhammad Sheet, Member
– Asst. Prof. Dr. Muhammad Sabah Jarjis, Member and Supervisor