MetaQ: A knowledge-driven framework for context-aware activity recognition combining SPARQL and OWL 2 activity patterns

Meditskos, Georgios; Dasiopoulou, Stamatia; Kompatsiaris, Ioannis

doi:10.1016/j.pmcj.2015.01.007

Cited by 46 publications

(38 citation statements)

References 42 publications

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“…In addition, the rule template can be used for explaining the missing resources that need to be gathered for further analysis. This approach is similar to SPARQL template in [47]. However, our approach attempts to describe the functionality facet of algorithm and apply into generic use-cases.…”

Section: Discussionmentioning

confidence: 99%

Ontology Based Framework for Interactive Self-Assessment of e-Health Applications

Passornpakorn

Kamolphiwong

2016

IEICE Trans. Inf. & Syst.

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SUMMARYPersonal e-healthcare service is growing significantly. A large number of personal e-health measuring and monitoring devices are now in the market. However, to achieve better health outcome, various devices or services need to work together. This coordination among services remains challenge, due to their variations and complexities. To address this issue, we have proposed an ontology-based framework for interactive selfassessment of RESTful e-health services. Unlike existing e-health service frameworks where they had tightly coupling between services, as well as their data schemas were difficult to change and extend in the future. In our work, the loosely coupling among services and flexibility of each service are achieved through the design and implementation based on HYDRA vocabulary and REST principles. We have implemented clinical knowledge through the combination of OWL-DL and SPARQL rules. All of these services evolve independently; their interfaces are based on REST principles, especially HATEOAS constraints. We have demonstrated how to apply our framework for interactive self-assessment in e-health applications. We have shown that it allows the medical knowledge to drive the system workflow according to the event-driven principles. New data schema can be maintained during run-time. This is the essential feature to support arriving of IoT (Internet of Things) based medical devices, which have their own data schema and evolve overtime. key words: ontology-based knowledge model, ontology-based health information, ontology-based application programming interface, RESTful service composition, HATEOAS

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Section: Discussionmentioning

confidence: 99%

Ontology Based Framework for Interactive Self-Assessment of e-Health Applications

Passornpakorn

Kamolphiwong

2016

IEICE Trans. Inf. & Syst.

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“…More complex domain models which consist of information such as user profile, routines, habits, and behavioral aspects are supported. Many existing patterns and ontologies have been reused and extended, like modelling patterns for smart homes [42] and descriptions and situations pattern of the DolceUltralite ontology [43], e.g., for modelling physiotherapy exercises. Figure 3 shows a higher-level representation, offering behavioural aspects as instances of the aspect class and detailed information as instances of the view class.…”

Section: Multimodal Knowledge Representationmentioning

confidence: 99%

A Context-Aware Conversational Agent in the Rehabilitation Domain

et al. 2019

Self Cite

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Conversational agents are reshaping our communication environment and have the potential to inform and persuade in new and effective ways. In this paper, we present the underlying technologies and the theoretical background behind a health-care platform dedicated to supporting medical stuff and individuals with movement disabilities and to providing advanced monitoring functionalities in hospital and home surroundings. The framework implements an intelligent combination of two research areas: (1) sensor- and camera-based monitoring to collect, analyse, and interpret people behaviour and (2) natural machine–human interaction through an apprehensive virtual assistant benefiting ailing patients. In addition, the framework serves as an important assistant to caregivers and clinical experts to obtain information about the patients in an intuitive manner. The proposed approach capitalises on latest breakthroughs in computer vision, sensor management, speech recognition, natural language processing, knowledge representation, dialogue management, semantic reasoning, and speech synthesis, combining medical expertise and patient history.

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“…AR which is a classification problem is known as an increasingly important determinant to the success of CA and personalised pervasive applications Chao et al, 2010;Ramesh et al, 2014). In Figures 6(a)-6(b), some of the publications employed AR by collecting data in real time using different choice of number of participant (student) to investigate ARAC Chao et al, 2010;Ramesh et al, 2014;Meditsko et al, 2015). However, Ramesh et al (2014) employs the AR using 20 participants to mitigate crowd disaster whenever an emergency is sensed thus predict at what time would stampede occur using CA framework with the CAC-WSN.…”

Section: Investigation Of Aracmentioning

confidence: 99%

A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters

Sadiq

Selamat²,

Ibrahim

2018

IJDET

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This paper presents a systematic literature review on context-awareness using activity recognition for mitigation of disasters. Disaster preparedness and the method of mitigating it or reduction of causalities are very important in order to save human lives. The review process went through four phases which are: planning, collation, filtration of dataset to get the most relevant materials, exploration and the description based on findings was carried out. The problem with the existing studies are: technology used lack the capacity to give feedback to potential victims, inability to move 178 F.I. Sadiq et al.the technology around, high false negative alarm, low sensor quality for crowd behaviour monitoring. This study used smartphones which is handy and has potential of being carried about. The analysis of the result was presented under three major headings which are publication by year, techniques, results and findings. The result shows the research gap in the area of disaster mitigation and the further study suggests the need to extend context-aware framework for stampede prediction based on activity recognition accuracy used in the previous study.

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MetaQ: A knowledge-driven framework for context-aware activity recognition combining SPARQL and OWL 2 activity patterns

Cited by 46 publications

References 42 publications

Ontology Based Framework for Interactive Self-Assessment of e-Health Applications

Ontology Based Framework for Interactive Self-Assessment of e-Health Applications

A Context-Aware Conversational Agent in the Rehabilitation Domain

A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters

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