@article{Pachoulakis_Xilourgos_Papadopoulos_Analyti_2017, title={Enrichment of a Kinect-based Physiotherapy and Assessment Platform for Parkinson’s disease Patients}, volume={5}, url={https://journals.scholarpublishing.org/index.php/AIVP/article/view/2750}, DOI={10.14738/aivp.51.2750}, abstractNote={Our Kinect-based physiotherapy platform tailored to Parkinson’s disease (PD) patients employs a Kinect sensor to extract 3D skeletal data in real-time from an exercising patient. The initial collection of five exercises served by the platform has now been enriched with an additional five exercises which are also based on traditional PD-specific physiotherapy. Each exercise has been implemented in the Unity 3d game engine and employs either a linear or a circular movement pattern with very light-weight processing demands for real-time computations. During each exercise, a trainer demonstrates correct execution and patient-provided 3D joint data obtained via the Kinect sensor are compared to exercise-specific control routines in real time, in order to assess proper posture and body control. Following completion of an exercise, performance metrics appropriate for that exercise are computed and displayed on screen as feedback to the patient. In addition, they are stored to provide a historical progress record to, e.g., enable the attending physiotherapist to fine-tune the exercise to the abilities/needs of an individual patient.}, number={1}, journal={European Journal of Applied Sciences}, author={Pachoulakis, Ioannis and Xilourgos, Nikolaos and Papadopoulos, Nikolaos and Analyti, Anastasia}, year={2017}, month={Mar.}, pages={31} }