In order to provide objective evaluation of the gait pattern, we have developed a sensor system with light and small wireless sensor units, which can be easily mounted on body. These sensor units comprise 3-D inertial sensors (accelerometers and gyroscopes) and force sensing resistors, and our recommended setup includes one sensor unit per each segment of both legs. The main goal of our research is contribution to the methodology for processing of signals from inertial sensors.
Our advanced algorithms for digital signal processing allow objective assessment of the quality of the gait pattern. This methodology is especially important for assessment of the motor deficit, progress of the disease and therapy effectiveness, and effectiveness of performed motor control (functional electrical stimulation).
Our special focus are clinical applications of the developed gait analysis algorithms for patients with parkinsonisms, which required the development of specific algorithms for signal processing that would provide detailed assessment of their gait patterns. For these studies, besides providing the usual gait parameters, we developed the algorithms for recognition of the changes and deformities in gait pattern (e.g. freezing of gait), duration and classification of these episodes.