A Multimedia Big Data E-Therapy Framework

Due to the low cost and high availability of wearable health sensors and motion tracking devices, home based therapy monitoring has come to a reality. In this paper, we propose a gesture controlled e-therapy online framework that can monitor physical and occupational therapy exercises using multimedia data produced by different sensors such as Kinect2, Leap, and Myo. The multimedia therapeutic data is then stored in a big data repository with proper annotation. We have developed analytics to mine therapeutic information from the big data platform, such as finding the most appropriate therapy regime for a patient, based on her age, ethnicity, gender, disability level and geo-spatial location. We will show key queries that can be answered by our developed analytics.