In this paper, we describe the Rehab@Home Operational Infrastructure which functioning essentially relies on the acquisition, processing, exchange and interpretation of a large set of heterogeneous data and information. These data are coming from existing clinical data records, rehabilitation workflow structure, user-system interaction, and explicit user feedback, basic information about expected and actual rehabilitation progress, biophysical sensors, ambient and contextual sensors. What in a more precise and detailed way has been described and analyzed is the specification and development of data protocol and data integration devoted to the acquisition, processing, exchange and interpretation of a large set of heterogeneous data and information coming from biophysical sensors, ambient and contextual sensors, existing clinical data records. It has been carried a study of user profiling and personalization, which will be exploited to adapt process and services with the aim of enhancing user satisfaction. Thanks to personalization of the user-system interaction, the explicit user feedback, the basic information about expected and actual rehabilitation progress are made available in the best way. Case-based reasoning further improves the extraction of useful information from a single patient and from compared analysis. Identification of the most relevant risk factors related to the rehabilitation process and the monitoring of the whole rehabilitation process was another field of study.
Infrastructure for data management and user centered rehabilitation in Rehab@Home project
FERRARA, ELISA;NARDOTTO, SONIA;PONTE, SERENA;DELLEPIANE, SILVANA
2014-01-01
Abstract
In this paper, we describe the Rehab@Home Operational Infrastructure which functioning essentially relies on the acquisition, processing, exchange and interpretation of a large set of heterogeneous data and information. These data are coming from existing clinical data records, rehabilitation workflow structure, user-system interaction, and explicit user feedback, basic information about expected and actual rehabilitation progress, biophysical sensors, ambient and contextual sensors. What in a more precise and detailed way has been described and analyzed is the specification and development of data protocol and data integration devoted to the acquisition, processing, exchange and interpretation of a large set of heterogeneous data and information coming from biophysical sensors, ambient and contextual sensors, existing clinical data records. It has been carried a study of user profiling and personalization, which will be exploited to adapt process and services with the aim of enhancing user satisfaction. Thanks to personalization of the user-system interaction, the explicit user feedback, the basic information about expected and actual rehabilitation progress are made available in the best way. Case-based reasoning further improves the extraction of useful information from a single patient and from compared analysis. Identification of the most relevant risk factors related to the rehabilitation process and the monitoring of the whole rehabilitation process was another field of study.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.