The patient-centric mobile healthcare system enhancing sensor connectivity and data interoperability

Choi, Jongseok; Ha, Minkeun; Im, Jungho; Byun, Jaewook; Kwon, Kiwoong; Yoon, Wondeuk; Kim, Dong-Soo; Heo, Sehyeon; Kim, Dae-Young

doi:10.1109/riot.2015.7104911

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…The semantic ontology approach introduces flexibility in data integration, maximizes different granular of data and copes with temporal changes in data definition (Liyanage, Krause and de Lusignan, 2015). An understanding of the meaning of a piece of data is crucial to solving the problem of heterogeneity (Jirkovský, Obitko and Mařík, 2016) in sensor data. With a standard definition of the contexts and meaning, metadata and provenance can be improved.…”

Section: Semantic Ontologymentioning

confidence: 99%

Wireless Body Area Network and Sensor Data Interoperability

Alatta¹

2021

Preprint

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The monitoring of maternal and child health, using wearable devices made with wireless sensor technologies, is expected to reduce maternal and child death rates. Wireless sensor technologies have been used in wireless sensor networks to enable the acquisition of data for monitoring machines, smart cities, transportation, asset tracking, and tracking of human activity. Applications based on wireless body area network (WBAN) have been used in healthcare for measuring and monitoring of patient health and activity through integration with wearable devices. Wireless sensors used in WBAN can be cost-effective, enable remote availability, and can be integrated with electronic health record (EHR) management systems. Interoperability of WBAN sensor data with other linked data has the potential to improve health for all, including maternal and child health through the improvement of data access, data quality and healthcare access. This paper presents a survey of the state-of-the-art techniques for managing WBAN sensor data interoperability. The findings in this study will provide reliable support to enable policymakers and health care providers to take action to enhance the use of e-health to improve maternal-child health and reduce the mortality rates of women and children.

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Section: Semantic Ontologymentioning

confidence: 99%

Wireless Body Area Network and Sensor Data Interoperability

Alatta¹

2021

Preprint

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“…It was achieved by an Android application they developed with third-party partners to connect with wearable devices, EHR systems, and other applications. A patient-centric mobile healthcare system that integrates data from body sensors was presented in [31]. The integration was implemented by leveraging a RESTful Web service on the application layer of the system to enable data sharing among applications.…”

Section: Related Workmentioning

confidence: 99%

Meaningful Integration of Data from Heterogeneous Health Services and Home Environment Based on Ontology

Peng

Goswami

2019

Sensors

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The development of electronic health records, wearable devices, health applications and Internet of Things (IoT)-empowered smart homes is promoting various applications. It also makes health self-management much more feasible, which can partially mitigate one of the challenges that the current healthcare system is facing. Effective and convenient self-management of health requires the collaborative use of health data and home environment data from different services, devices, and even open data on the Web. Although health data interoperability standards including HL7 Fast Healthcare Interoperability Resources (FHIR) and IoT ontology including Semantic Sensor Network (SSN) have been developed and promoted, it is impossible for all the different categories of services to adopt the same standard in the near future. This study presents a method that applies Semantic Web technologies to integrate the health data and home environment data from heterogeneously built services and devices. We propose a Web Ontology Language (OWL)-based integration ontology that models health data from HL7 FHIR standard implemented services, normal Web services and Web of Things (WoT) services and Linked Data together with home environment data from formal ontology-described WoT services. It works on the resource integration layer of the layered integration architecture. An example use case with a prototype implementation shows that the proposed method successfully integrates the health data and home environment data into a resource graph. The integrated data are annotated with semantics and ontological links, which make them machine-understandable and cross-system reusable.

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