Characterization of the Hand Grasping Using Sensor Fusion

Abstract: This master`s thesis explores the possibility of constructing a device capable of classifying human arm movements while performing a set of common tasks. Intended for use on patients undergoing rehabilitation, the device collects data using multiple sensors and applies a convolutional neural network in order to detect different activities of daily living. The sensors used by the device are limited to two inertial measurement units and one radar module. Beyond constructing the device this thesis also attempted to gather its own data set for training and evaluate the systems performance. Finally possible improvements and modifications to the system are proposed.