Serious games and in-cloud data analytics for the virtualization and personalization of rehabilitation treatments


IEEE Transactions on Industrial Informatics
doi:10.1109/TII.2018.2856097

During the last years, the significant increase in the number of patients in need of rehabilitation has generated an unsustainable economic impact on healthcare systems, implying a reduction in therapeutic supervision and support for each patient. To address this problem, this paper proposes a tele-rehabilitation system based on serious games and in-cloud data analytics services, in accordance with Industry 4.0 design principles regarding modularity, service orientation, decentralization, virtualization and real-time capability.

Future Generation Computer Systems, Elsevier

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Multimedia data can be easily uploaded, communicated and shared in community portals. These later allow users to manually tag, comment and annotate the digital content, but they lack a general support for fine-grained semantic descriptions and look-up, especially when talking about things “inside” multimedia content, such as an object in a video or a person depicted in a still image.

Linking Multimedia Data is an active and inter-disciplinary research field in multimedia. Turning a distributed repository of images, video, text, and other signal-based objects (such as various radar signatures) into an easily browsable information and knowledge would certainly transform the underlying data into a more satisfying representation for humans to intelligently navigate. The power of this approach results from the mixture of different modalities of data. While linked textual data is being studied by the web semantics and database communities, adding non-textual data is much more satisfying for human interaction, but comes with the price of more complexity.

While in hypermedia, one mainly focuses on languages and synchronization made between information parts in both temporal and spatial dimensions, we mainly focus in this special issue on the (semi) automatic and collaborative methods for fostering semantics in multimedia data by enriching information (so to come up with a knowledge), for visualization and exploration, and for missing (meta)data estimation. The added complexity is due to objects having multiple facets, depending on their use and who or what system is doing the labeling.

This research area is a blending of topics of interest to many disparate research communities. The novelty will reside initially in how to formulate and implement the boundaries between tasks of interest to these different communities. As the field matures and the diverse nature of the data is accepted as a given by researchers in this area, research advances of a more integrative nature will be the norm, treading into areas that we can only dream of today.

Le interviste, pubblicate su Il Sole 24 Ore e sul programma Moebius di Radio24, sul tema dell'olografia cognitiva sviluppata dall'Istituto di calcolo e reti ad alte prestazioni del Cnr e presentata a Futuro Remoto 2017.

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