Machine Learning to Determine Upper Extremity Motion from Inertial Measurement Unit Signals

Within the medical field and more specialized focus on the therapeutic part, the anatomical analysis of human limbs is a highly important issue, to improve the way in which ailments are treated at the movement level. For these reasons, part of the technological studies has focused on the detection of human movements and activities, to obtain an accurate interpretation within a computational system. The present project has a technological approach in the detection of characteristic movements of the human upper extremity with the use of positioning sensors; and with the information obtained from these, could make use of machine learning to detect such movements. Finally, these information and results from the machine learning will be displayed through the use of a graphical interface.