Gait impairment is one of the most disabling motor symptoms in movement disorders including the two prototypical neuronal (Parkinson’s disease - PD), and musculoskeletal (Osteoarthrosis - OA) diseases. Gait is also an ideal target for continuous sensor-based assessment: i) its highly stereotype movement enables automated assessment of functional biomechanics, ii) a single sensor position at the foot provides optimal biomechanical gait information, and iii) non-obtrusive and non-stigmatizing integration in shoes improves patient acceptance.

In PD, motor symptoms and gait patterns can fluctuate during the day, which limits the assessment during one-time visits by the neurologist and requires continuous monitoring approaches. In OA, gait impairment is both important as a profound factor limiting mobility and quality of life, but also as a clinical decision support between conservative or invasive treatment options.

The overall goal of the project is to implement an automatic, sensor-based gait analysis system (eGaIT – embedded gait analysis using IT) for supervised diagnostic gait tests in PD and OA patients under laboratory conditions.

http://www.efi.uni-erlangen.org/projects/efimoves/