Nowadays, in order to enable future medical decision making, in the healthcare panorama there is the need of efficient Cloud-systems able to acquire and integrate Big e-health Data, coming from heterogeneous sources, through smart clinical workflows. Indeed, during the treatment at hospital, patients use medical devices generating a huge amount of data that have to be automatically stored into the Cloud storage system. In this paper, we specifically discuss an automated Machine-To-Machine clinical workflow able to manage the migration of Big e-health Data coming from medical devices to a Cloud NoSQL storage system. To validate our solution, we also present and test a real use case in which a clinical workflow is considered to manage big robotic rehabilitation datasets of the IRCCS Messina (Italy) Institute. Experiments prove the goodness of our approach in terms of data acquisition and integration.