Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: http://hdl.handle.net/1946/3040
The objective of this study is to investigate the possibility of controlling a prosthetic knee by using a Xsens sensor module that consist of 3D acceleration, gyro and magnetic sensors. The prosthetic knee used for this study is the Rheo knee manufactured by Ossur Inc. Pattern recognition methods are used to classify terrain at each step, i.e. level ground, slope or stairs. A state machine is used to model gait cycle, where phases are represented as states. Events of the gait cycle are found by sensor signals, the events cause transitions between states. Features of sensor signals are used to classify terrain. Gait phases are detected using two acceleration and one gyro sensor. Neural networks calculate an output current based on the Xsens sensor module to match the Rheo output current. The results are that acceleration and gyro sensors can be used for controlling prosthetic knees and the state machine can be used as a part of a control system for lower limb computer controlled prosthetics and orthotics.