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. 2014 Mar 7;14(3):4560-84.
doi: 10.3390/s140304560.

Ontological knowledge engine and health screening data enabled ubiquitous personalized physical fitness (UFIT)

Chuan-Jun Su  1 , Chang-Yu Chiang  2 , Meng-Chun Chih  3
Affiliations

Ontological knowledge engine and health screening data enabled ubiquitous personalized physical fitness (UFIT)

Chuan-Jun Su et al. Sensors (Basel). .

Abstract

Good physical fitness generally makes the body less prone to common diseases. A personalized exercise plan that promotes a balanced approach to fitness helps promotes fitness, while inappropriate forms of exercise can have adverse consequences for health. This paper aims to develop an ontology-driven knowledge-based system for generating custom-designed exercise plans based on a user's profile and health status, incorporating international standard Health Level Seven International (HL7) data on physical fitness and health screening. The generated plan exposing Representational State Transfer (REST) style web services which can be accessed from any Internet-enabled device and deployed in cloud computing environments. To ensure the practicality of the generated exercise plans, encapsulated knowledge used as a basis for inference in the system is acquired from domain experts. The proposed Ubiquitous Exercise Plan Generation for Personalized Physical Fitness (UFIT) will not only improve health-related fitness through generating personalized exercise plans, but also aid users in avoiding inappropriate work outs.

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Figures

Figure 1.
Figure 1.
SEMPATH adaptation methodology [24].
Figure 2.
Figure 2.
The partial classes of the “Problem-Oriented Medical Record Ontology” in HL7-sample-plus-owl.
Figure 3.
Figure 3.
Workflow for generating an exercise plan based on a fitness test.
Figure 4.
Figure 4.
UFIT three ontologies-driven knowledge base.
Figure 5.
Figure 5.
Class-Property-Instance example of UFIT.
Figure 6.
Figure 6.
UFIT logical architecture.
Figure 7.
Figure 7.
UFIT physical architecture.
Figure 8.
Figure 8.
The partial model of user profile ontology.
Figure 9.
Figure 9.
The partial model of Exercise ontology.
Figure 10.
Figure 10.
The usage example of REST Service.
Figure 11.
Figure 11.
An example of SPARQL query sentence.
Figure 12.
Figure 12.
An example of SPARQL query result, Jessie's exercise plan.
Figure 13.
Figure 13.
(a) UFIT login page; (b) Customized exercise plan generated; (c) Cardiopulmonary training in the customized exercise plan.
Figure 14.
Figure 14.
UFIT usability/readability evaluation for users.
See this image and copyright information in PMC

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