TrhOnt: building an ontology to assist rehabilitation processes

Background: One of the current research efforts in the area of biomedicine is the representation of knowledge in a structured way so that reasoning can be performed on it. More precisely, in the field of physiotherapy, information such as the physiotherapy record of a patient or treatment protocols for specific disorders must be adequately modeled, because they play a relevant role in the management of the evolutionary recovery process of a patient. In this scenario, we introduce TRHONT, an application ontology that can assist physiotherapists in the management of the patients' evolution via reasoning supported by semantic technology. Methods: The ontology was developed following the NeOn Methodology. It integrates knowledge from ontological (e.g. FMA ontology) and non-ontological resources (e.g. a database of movements, exercises and treatment protocols) as well as additional physiotherapy-related knowledge. Results: We demonstrate how the ontology fulfills the purpose of providing a reference model for the representation of the physiotherapy-related information that is needed for the whole physiotherapy treatment of patients, since they step for the first time into the physiotherapist's office, until they are discharged. More specifically, we present the results for each of the intended uses of the ontology listed in the document that specifies its requirements, and show how TRHONT can answer the competency questions defined within that document. Moreover, we detail the main steps of the process followed to build the TRHONT ontology in order to facilitate its reproducibility in a similar context. Finally, we show an evaluation of the ontology from different perspectives. Conclusions: TRHONT has achieved the purpose of allowing for a reasoning process that changes over time according to the patient's state and performance.Authors thank Dr. Jon Torres and Dr. Jesus Seco for their help with the physiotherapy-related aspects. Authors thank Dr. Maria Poveda-Villalon for her help with OOPS!. This work was supported by the Spanish Ministry of Economy and Competitiveness [grant number FEDER/TIN2013-46238-C4-1-R] and by the Basque Country Government [grant number IT797-13]

Kires: a data-centric telerehabilitation system based on kinect

185 p.It is widely accepted that the worldwide demand for rehabilitation services. To meet these needs, there will have to be developed systems of telerehabilitation that will bring services to even the most remote locations, through Internet and related technologies.This thesis is addressing the area of remote health care delivery, in particular telerehabilitation. We present KiReS; a Kinect based telerehabilitation system which covers the needs of physiotherapists in the process of designing, managing and evaluating physiotherapy protocols and sessions and also covers the needs of the users providing them an intuitive and encouraging interface and giving useful feedback to enhance the rehabilitation process. As required for multi-disciplinary projects, physiotherapists were consulted and feedback from patients was incorporated at different development stages.KiReS aims to outcome limitations of other telerehabilitation systems and bring some novel features: 1) A friendly and helpful interaction with the system using Kinect and motivational interfaces based on avatars. 2) Provision of smart data that supports physiotherapists in the therapy design process by: assuring the maintenance of appropriate constraints and selecting for them a set of exercises that are recommended for the user. 3) Monitoring of rehabilitation sessions through an algorithm that evaluates online performed exercises and sets if they have been properly executed. 4) Extensibility, KiReS is designed to be loaded with a broad spectrum of exercises and protocols

An ontological modeling approach for abnormal states and its application in the medical domain

Background: Recently, exchanging data and information has become a significant challenge in medicine. Such data include abnormal states. Establishing a unified representation framework of abnormal states can be a difficult task because of the diverse and heterogeneous nature of these states. Furthermore, in the definition of diseases found in several textbooks or dictionaries, abnormal states are not directly associated with the corresponding quantitative values of clinical test data, making the processing of such data by computers difficult. Results: We focused on abnormal states in the definition of diseases and proposed a unified form to describe an abnormal state as a “property,” which can be decomposed into an “attribute” and a “value” in a qualitative representation. We have developed a three-layer ontological model of abnormal states from the generic to disease-specific level. By developing an is-a hierarchy and combining causal chains of diseases, 21,000 abnormal states from 6000 diseases have been captured as generic causal relations and commonalities have been found among diseases across 13 medical departments. Conclusions: Our results showed that our representation framework promotes interoperability and flexibility of the quantitative raw data, qualitative information, and generic/conceptual knowledge of abnormal states. In addition, the results showed that our ontological model have found commonalities in abnormal states among diseases across 13 medical departments