Abstract
Reduced cost and increased proliferation of sensors has resulted in the generation of a large amount of data. To make use of this data effectively, efficient techniques for collecting, storing and managing data are needed. In this paper, we present a health big data indexing technique that allows for the efficient storage, querying and management of tele-rehabilitation related big data collected via health sensors connected to client machines accessing web-based e-Health frameworks. Our novel scheme is based on indexing of rehabilitation data based on the human body joint model. We further index the data based on other parameters that may be of interest to researchers such as ethnicity and geographical location. We have described all components of the system in brief.