This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
The leading cause of permanent disability in developed countries is due to neurological injuries, such as stroke. While physical rehabilitation therapy is indispensable for treating neurological disabilities, repetitive and high intensity therapies place high physical burden on the therapist and significantly increase the cost of such treatments. These challenges have led to design and development of various robot-assisted rehabilitation devices.
As the number of rehabilitation robots increase, the information about them also increases, but most of the time in unstructured forms (e.g., as text in publications), which make it harder to access the requested knowledge and reason about it. Also, due to interdisciplinary nature of rehabilitation robotics, sometimes requested knowledge requires integration of further knowledge from related disciplines (e.g., physical medicine). Motivated by these challenges, we have designed and developed the first formal rehabilitation robotics ontology, called RehabRobo-Onto, to represent knowledge about rehabilitation robotics in the structured form of OWL.
In this abstract, we continue our studies on RehabRobo-Onto by discussing its interoperability with the available knowledge resources, such as Foundational Model of Anatomy (FMA) and Human Disease Ontology (DO), towards personalized physical rehabilitation therapies.
This is an abstract which has been accepted for the NETTAB 2017 Workshop.
Pellet's output and a note on future work are added.