The consolidation of telerehabilitation for the treatment of many diseases over the last
decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in
remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to
unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises
and proper corporal movements online should also be mentioned. The focus of this paper is on
a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and
other less accessible locations. A full-stack is presented using big data frameworks that facilitate
communication between the patient and the occupational therapist, the recording of each session,
and real-time skeleton identification using artificial intelligence techniques. Big data technologies are
used to process the numerous videos that are generated during the course of treating simultaneous
patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for
automated evaluation of corporal exercises, which is of immense help to the therapists in charge of
the treatment programs.
