Validation of an optimized algorithm to use Kinect in a non-structured environment for Sit-to-Stand analysis.

The aim of this work is to obtain reliable kinematic measures relative to the execution of the Sit-to-Stand functional evaluation test, by low-cost and widely diffused instrumentation, that even non-experienced users can adopt in non-structured environments, like ambulatory or domestic settings. In particular, the paper refers to a low cost RGB-Depth sensor widely used in the gaming scenario like the Microsoft Kinect sensor. An algorithm is proposed that allows a reliable measure of human motion in a sagittal view. The performance of the proposed algorithm is compared to other two classic commercial algorithms. Results obtained by all the three algorithms have been compared to kinematic results obtained by the use of a stereophotogrammetric system that represents the gold-standard for kinematic measurement of human movement. Average errors of about 4 degrees, both for the trunk/leg angle and for the knee flexion/extension angle, have been obtained by the proposed algorithm and open the way to its possible adoption in non-clinical environments and further applications.