Detection and classification of human arm movements for physical rehabilitation

In the latest years, the detection of body posture and activity received a significant interest in the field of the physical rehabilitation aimed at providing advanced medical therapies to patients who have suffered a stroke, joint replacements/reconstructions, amputation, or some motor function disability resulting from Parkinson's disease [1,2]. Rehabilitation is a dynamic process and the restoration of patients' functional capability to normal requires every day functional activities that need to be monitored and controlled by specialized medical operators. An effective approach is represented by motion capturing systems where some video cameras follow the movements of a number of markers placed on the human body to reconstruct its activity. However, such systems are complex, expensive and require a large number of constitutive elements (cameras and markers) [3]. © 2010 IEEE.