Developing and Maintaining an Ontology for Rehabilitation Robotics

Zeynep Dogmus, Gizem Gezici, Volkan Patoglu and Esra Erdem

Faculty of Engineering and Natural Sciences, Sabancı University, Istanbul, Turkey

Keywords:

Rehabilitation Robotics, Ontology Development.

Abstract:

Representing the available information about rehabilitation robots in a structured form, like ontologies, fa-

cilitates access to various kinds of information about the existing robots, and thus it is important both from

the point of view of rehabilitation robotics and from the point of view of physical medicine. Rehabilitation

robotics researchers can learn various properties of the existing robots and access to the related publications

to further improve the state-of-the-art. Physical medicine experts can ﬁnd information about rehabilitation

robots and related publications (possibly including results of clinical studies) to better identify the right robot

for a particular therapy or patient population. Therefore, considering also the advantages of ontologies and

ontological reasoning, such as interoperability of various heterogenous knowledge resources (e.g., patient

databases or disease ontologies), such an ontology provides the underlying mechanisms for translational phys-

ical medicine, from bench-to-bed and back, and personalized rehabilitation robotics. With these motivations,

we have designed and developed the ﬁrst formal rehabilitation robotics ontology, called REHABROBO-ONTO,

in OWL, collaborating with experts in robotics and in physical medicine. We have also built a software (called

REHABROBO-QUERY) with an easy-to-use intelligent user-interface that allows robot designers to add/modify

information about their rehabilitation robots to/from REHABROBO-ONTO.

1 INTRODUCTION

Ontologies (like databases) are formal frameworks for

representing knowledge in a structured form, to aid

access to relevant parts of the knowledge and auto-

mate reasoning over it. An ontology can be viewed as

a graph where nodes denote concepts (e.g., rehabilita-

tion robots, joint movements) and the edges between

the nodes denote relations between the corresponding

concepts. For instance, an edge from a node that de-

notes “Upper Extremity Rehabilitation Robots” to a

node that denotes “Rehabilitation Robots” may char-

acterize the “is-a” hierarchy relation; whereas an edge

from a node that denotes “Rehabilitation Robots” to

a node that denotes “Joint Movements” may char-

acterize “targets” relation. Due to their ﬂexible

graph-like structure, ontologies (unlike databases) al-

low representation of incomplete knowledge, can eas-

ily be extended by new information (e.g., with new

sorts/features of rehabilitation robots). Due to their

formal representations, ontologies developed by dif-

ferent parties at different locations can be integrated,

and reasoning (e.g., query answering) can be auto-

mated over concepts and their relations represented

in these ontologies. Therefore, it is not surprising that

more and more knowledge-intensive systems (includ-

ing Semantic Web (Berners-Lee et al., 2001) that is

planned to provide automated services to Web by giv-

ing meaning to concepts) rely on ontologies to enable

content-based access, interoperability, and communi-

cation across the Web.

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 publi-

cations), which make it harder to access the requested

knowledge (e.g., the ﬂexion/extension range of mo-

tion (RoM) of ASSISTON-WRIST (Erdogan et al.,

2011)) and thus reason about it (e.g., ﬁnding the reha-

bilitation robots that target shoulder movements and

also have at least 60

◦

RoM for the ﬂexion/extension

movements of the wrist). To facilitate access to re-

quested knowledge about rehabilitation robots, we

have designed and developed the ﬁrst formal rehabili-

tation robotics ontology, called REHABROBO-ONTO.

This ontology has been designed in a way that en-

ables integration with other medical ontologies, such

as ontologies that capture rehabilitation protocols,

patient data and disorder details. Considering the

standards of World Wide Web Consortium (W3C),

REHABROBO-ONTO is represented in OWL (Web

Ontology Language) (Horrocks et al., 2003; Antoniou

and van Harmelen, 2004).

389

Dogmus Z., Gezici G., Patoglu V. and Erdem E..

Developing and Maintaining an Ontology for Rehabilitation Robotics.

DOI: 10.5220/0004145303890395

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2012), pages 389-395

ISBN: 978-989-8565-30-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

Our goal is to make this ontology open-source so

that every rehabilitation robotics researcher can eas-

ily add information about his/her robot to it, and ev-

ery rehabilitation robotics researcher and every phys-

ical medicine expert can access information about

all available rehabilitation robots. To facilitate such

modiﬁcations and uses of REHABROBO-ONTO, we

have developed a software (called REHABROBO-

QUERY) with an intelligent user-interface. In this

way, experts do not need to know logic-based repre-

sentation languages of ontologies, like OWL, or Se-

mantic Web technologies, for information entry, re-

trieval and modiﬁcation.

The ontology system consisting of REHABROBO-

ONTO and REHABROBO-QUERY is of great value

to robot designers as well as physical therapists and

medical doctors. On the one hand, robot designers

can beneﬁt from the system, for instance, to identify

robotic devices targeting similar therapeutic exercises

or to determine systems using a particular kind of

actuation-transmission pair to achieve a range of mo-

tion that exceeds some threshold. Availability of such

information may help inspire new designs or may lead

to a better decision making process. The ontology can

also be utilized to group similar robots by quantiﬁable

characteristics and to establish benchmarks for sys-

tem comparisons. Overall, an ontology designed to

speciﬁcally meet the expectations of the overall reha-

bilitation robotics effort has the potential to become

an indispensable tool that helps in the development,

testing, and certiﬁcation of rehabilitation robots. On

the other hand, physical therapists and medical doc-

tors can utilize the ontology to compare rehabilitation

robots and to identify the ones that serve best to cover

their needs, or to evaluate the effects of various de-

vices for targeted joint exercises on patients with spe-

ciﬁc disorders.

It is important to emphasize that the ontology

REHABROBO-ONTO and the tool REHABROBO-

QUERY introduced in this paper have been developed

to initiate efforts in utilizing ontological technologies

for the ﬁeld of rehabilitation robotics. Therefore, by

making REHABROBO-ONTO available open-source

via REHABROBO-QUERY, it is our intention to con-

tinually update and enhance capabilities of these tools

according to the feedback provided by the commu-

nity.

2 RELATED WORK

Although there are some ontologies maintaining in-

formation about objects or environments (Chella

et al., 2002; Yanco and Drury, 2004; Paolucci and

Sycara, 2004; Wang et al., 2005; Suh et al., 2007;

Johnston et al., 2008), developed for the use of robots,

there are only several works in the literature that have

proposed ontologies about robots.

In particular, Amigoni and Neri (Amigoni and

Neri, 2005) introduce two ontologies (in OWL):

one to store general concepts and properties/relations

about the movement capabilities of mobile robots

(e.g., wheels and their properties) and the other to de-

scribe the high level tasks that these robots can per-

form (e.g., move, rotate). The idea is then to allocate

tasks and/or assign roles to mobile robots by means

of querying these two ontologies using a description

logics reasoner.

Schlenoff and Messina (Schlenoff and Messina,

2005) introduce an ontology (in OWL) for urban

search and rescue robots. The ontology captures

structural characteristics (such as size), functional ca-

pabilities (such as locomotion capabilities) and oper-

ational considerations (such as display type) of the

robots with a goal of assisting in the development and

testing of search and rescue robot systems.

Juarez et al. (Juarez et al., 2011) introduce a

database (called ROBODB) for storing physical char-

acteristics of robots; but also note that they plan to

transform the knowledge stored in ROBODB into an

OWL ontology to beneﬁt from this “common” lan-

guage of ontologies and related reasoners.

However, none of these existing robot ontologies

have been designed to target rehabilitation robots and,

without further customization, they fail to capture

many important aspects of rehabilitation robots, in-

cluding the interoperability with the existing ontolo-

gies in physical medicine.

3 DESIGNING AN ONTOLOGY

FOR REHABILITATION

ROBOTS

We have designed the rehabilitation robots ontol-

ogy REHABROBO-ONTO considering suggestions of

the rehabilitation robotics researchers and physical

medicine experts whom we collaborate with. As sug-

gested in (Uschold and King, 1995) about design-

ing an ontology, we have ﬁrst identiﬁed the purpose,

and then identiﬁed and deﬁned the basic concepts and

their thematic classes, and their relationships for the

chosen subject domain.

Our goal of developing an ontology for rehabilita-

tion robotics is mainly to maintain a knowledge repos-

itory containing information about all rehabilitation

robots and relevant references, to facilitate access to

KEOD2012-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

390

Figure 1: REHABROBO-ONTO with main classes.

requested information in this repository for both robot

designers as well as physical medicine experts. In this

way, not only it will be easier for robot designers to

improve the state-of-the-art in rehabilitation robotics

but also it will aid translation from bench-to-bed and

back, and personalized physical medicine by allow-

ing the physical medicine experts to choose the right

rehabilitation robots for speciﬁc patients/therapies.

Along these goals, next comes the question of

what kind of information should be maintained in

such an ontology about rehabilitation robots.

We have designed our ontology (Figure 1) consid-

ering four main concepts (or thematic classes):

• RehabRobots (representing rehabilitation robots

and their properties),

• JointMovements (representing targeted joint

movements and their properties),

• Owners (representing robot designers who

add/modify information in the ontology about

their own robots),

• References (representing publications related to

rehabilitation robots).

These concepts are related to each other by the fol-

lowing relations:

• a rehabilitation robot targets joint movements,

• a rehabilitation robot is ownedBy a robot designer,

• a rehabilitation robot hasReferences to some

publications.

As seen in Figure 1, each class has its own prop-

erties. For instance, RehabRobots has the “func-

tionality” property to be able to describe that a re-

habilitation robot can be used at home or in clinic.

JointMovements has a property to describe the

“RoM type” of the robot: a rehabilitation robot can

be used in active mode, where some effort from the

patient is required while the robot guides the patient,

or in passive mode, where no effort is required from

the patient while the robot guides the patient’s move-

ments. We also keep information about the owners

(e.g., names, institutions) and the related references.

Considering various sorts of rehabilitation robots

and various sorts of joint movements, RehabRobots

and JointMovements classes have subclasses; some

of these subclasses are illustrated in Figures 2 and 3.

Maintaining such a hierarchy aids not only com-

pact representation of knowledge about rehabilitation

robots (by avoiding repetitions) but also efﬁcient rea-

soning about it. Currently there are 93 classes repre-

sented in REHABROBO-ONTO.

DevelopingandMaintaininganOntologyforRehabilitationRobotics

391

Figure 3: Hierarchy of lower extremity joint movements targeted by rehabilitation robots.

Figure 2: Hierarchy of lower extremity rehabilitation

robots.

4 DEVELOPING AND

MAINTAINING

REHABROBO-ONTO

Ontologies represented formally in a language, such

as OWL, are based on variations of Description Log-

ics (DL) (Baader et al., 2008). DL provides the logi-

cal formalism not only for such formal ontologies but

also the Semantic Web.

DL terminology consists of concepts, roles, and

objects. Objects denote entities of our world with

characteristics and attributes; concepts are interpreted

as sets of objects; and roles are interpreted as bi-

nary relations on objects or concepts. According

to a formal ontology terminology (e.g., in OWL),

concepts are called classes, attributes of classes are

called data properties, roles are called object prop-

erties, and objects are called individuals. For in-

stance, a concept/class named RehabRobots may

represent all rehabilitation robots, whereas an ob-

ject/individual named ASSISTON-SE represents the

particular shoulder robot introduced in (Ergin and

Patoglu, 2012; Yalcin and Patoglu, 2012). A

class (e.g., RehabRobots) may have subclasses (e.g.,

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392

ShoulderRobots); then subclasses inherit properties

of classes. Such a possibility of representing hierar-

chical classes allows compact representation as well

as efﬁcient reasoning over it.

Due to the common logic-based formalism that

underlies formal ontologies and Semantic Web,

different ontologies developed by different parties

around the world can be integrated for deep auto-

mated reasoning. In that sense, considering also the

possibilities of integrating information about rehabili-

tation robotics with other information (e.g., patient in-

formation, disease information, genetic information),

maintaining information about rehabilitation robotics

as formal ontologies is well-decided.

Once we identify classes, their properties, sub-

classes, relations between classes, and deﬁne them

precisely as in the previous section, we can repre-

sent the ontology formally using a logic-based ontol-

ogy language. Considering the standards of W3C,

we have decided to represent the ontology in the

logic-based ontology language OWL; then we need

to use description logic reasoners to ﬁnd answers

to experts’ queries. We have represented the OWL

ontologies that describe general concepts and their

properties/relations using the OWL ontology edi-

tor PROT

E (Gennari et al., 2003).

Once we represent general concepts and their

properties/relations about rehabilitation robots in

OWL, we are not done yet. As discussed above as

a part of our goals, we would like the rehabilita-

tion robotics ontology to be shared by researchers

so that robot designers can add/modify information

about their robots, and both rehabilitation robotics ex-

perts and physical medicine experts can ask queries

over it. Therefore, we would like to allow researchers

to add information about speciﬁc rehabilitation robots

by “assertions” (like, “the rehabilitation robot whose

name is ASSISTON-WRIST is a wrist robot and it has

clinic use”) as well.

Such assertions about speciﬁc individuals can

be added to REHABROBO-ONTO using PROT

However, since PROT

E downloads the whole on-

tology to be able to add new information, ensur-

ing that the users add information to REHABROBO-

ONTO without letting them modify other parts of the

ontology may be problematic. Also, assuming that

the existing robotics experts and physical medicine

experts know about DL and logic-based ontology lan-

guages, that they have experience in using DL rea-

soners or Semantic Web technologies, and that they

keep track of the most recent versions of these soft-

ware, may not be reasonable along our goals for an

effective use of the rehabilitation ontology. To facil-

itate the effective use of the rehabilitation ontology

Figure 4: An overview of the system architecture of

REHABROBO-QUERY.

by different users, we have designed a tool (called

REHABROBO-QUERY) with an easy-to-use intelli-

gent user-interface.

REHABROBO-QUERY (Figure 4) is a soft-

ware that allows rehabilitation robotics researchers

to add/modify information to REHABROBO-ONTO

about their robots by following consecutive tabs of

the intelligent user-interface and allow experts to ask

queries about the existing robots, without having to

know about DL or logic-based ontology languages,

and without possessing any experience of using the

existing description logic based reasoners or Seman-

tic Web technologies. Some snapshots of the user

interface of REHABROBO-QUERY for adding new

information to REHABROBO-ONTO ontology about

the rehabilitation robot ASSISTON-WRIST (Erdogan

et al., 2011) are shown in Figures 5 and 6.

As the registered user describes the robot by nav-

igating the tabs, the information is held in the system

in a structured way, as temporary objects. Therefore,

the user has the chance to return to any tab to change

the information. After entering all properties of the

robot, in the End tab, all the information entered by

the user is displayed as a summary for the last time.

After the user checks the information and conﬁrms

its addition to REHABROBO-ONTO, the information

about the rehabilitation robot is transformed into as-

sertions in OWL to be added to REHABROBO-ONTO.

Assertions about each rehabilitation robot is stored

in a separate ﬁle, to make it easy to modify/delete

REHABROBO-ONTO as well as for efﬁcient query an-

swering planned as part of future work.

A user can modify or delete his/her own robots

only. First the relevant robots are found by querying

REHABROBO-ONTO using the DL reasoner HER-

DevelopingandMaintaininganOntologyforRehabilitationRobotics

393

Figure 5: REHABROBO-QUERY: Adding to REHABROBO-ONTO general information about the rehabilitation robot

ASSISTON-WRIST.

Figure 6: REHABROBO-QUERY: Adding to REHABROBO-ONTO information about the RoM of targeted joint movements of

the rehabilitation robot ASSISTON-WRIST.

MIT (Motik et al., 2007) via OWL API, and listed

in a pull-down menu. For modiﬁcation, after the user

chooses a robot from the list, the user interface that we

have seen earlier for adding information appears but

now with tabs ﬁlled with the robot’s properties. The

user can make changes via this interface and the up-

dated information can be saved as a set of assertions in

OWL, in a new ﬁle while keeping the previous version

as “modiﬁed”. For deletion, after the user chooses a

robot from the list, the relevant ﬁle containing asser-

tions about that robot is marked as “deleted”. Note

that in both cases, we keep the information about the

robot before modiﬁcation/deletion as well; these ﬁles

may be needed if the user accidentally deletes his/her

robot from REHABROBO-ONTO, or modiﬁes it incor-

rectly.

5 CONCLUSIONS

We have designed and developed the ﬁrst formal re-

habilitation robotics ontology, called REHABROBO-

ONTO, to represent information about rehabilitation

robots. The beneﬁts of having such an ontology can

be summarized as follows:

• It provides structured formal representation about

rehabilitation robots and their properties. This

further allows easy access to the requested in-

formation, integration with other knowledge re-

sources (e.g., patient databases, or disease ontolo-

gies), as well as reasoning (e.g., answering com-

plex queries) over all these knowledge resources.

• It allows the selection of right rehabilitation

KEOD2012-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

394

robots for a particular patient or a physical ther-

apy. In particular, it helps ﬁnding available re-

sources (e.g., rehabilitation robots and related

publications that may involve results of clinical

studies) that address a speciﬁc need. This further

paves the way for translational physical medicine

(from bench-to-bed and back) and personalized

physical medicine.

• It aids exchange of information across rehabilita-

tion robots researchers over the world, and thus to

improve the state-of-the-art.

• It allows to identify “gaps” in functionality of re-

habilitation robots, that can further improve re-

search efforts.

We have also built a software, REHABROBO-

QUERY, with an easy-to-use intelligent user-interface

that allows robot designers to add/modify information

about their rehabilitation robots.

Along these directions, our ongoing work involves

extending REHABROBO-QUERY with the function-

ality of answering queries over REHABROBO-

ONTO using a DL reasoner. For instance, using

REHABROBO-QUERY, we will be able to ﬁnd

the rehabilitation robots that has targeted pop-

ulation “adult” and that targets “shoulder

scapular elevation/depression movements”.

Our ongoing work also includes making

REHABROBO-QUERY available to researchers by a

web-service, and integration of REHABROBO-ONTO

with the existing related ontologies.

ACKNOWLEDGEMENTS

This work has been partially supported by Sabanci

University IRP Grant and TUBITAK Grant 111M186.

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