Exploring coordination patterns in vr-based rehabilitation for stroke using the kinect sensor

According to the World Health Organization (WHO), acute cerebrovascular diseases represent the third cause of death in the Western world. Access to rehabilitation therapies is very limited and often not very personalized due to its high cost. In recent decades, the use of information and communication technologies (ICT) has become popular as a solution to extend the use of complementary therapies in people with stroke. Particularly, the use of systems that use exercise videogames (Exergames) with motion capture sensors (e.g., Kinect) and virtual reality (VR) headsets has proven to be a feasible and efficient option to promote greater interactivity with the participants and progress quantification. Although the cost of this type of motion capture sensors is low, the type of analysis carried out is often limited to isolated joints and determined by time-series analysis. This paper explores the use of non-linear analysis techniques to investigate the patterns of motor coordination recorded during the interaction with Exergames. A methodology to create phase plane and relative phase diagrams from data captured with the Kinect sensor using both off-the-shelf and VR Exergames is presented. We expose two different rehabilitation scenarios where the coordination analysis could be potentially useful, detailing the multi-joint analysis carried out as well as showing the diagrams and their interpretation. We conclude by reinforcing the need for a more comprehensive and extended analysis of human-body coordination as an important mechanism to validate the use of interactive and virtual technologies in rehabilitation.