IoMT Platform for Pervasive Healthcare Data Aggregation, Processing, and Sharing Based on OneM2M and OpenEHR

Abstract

Pervasive healthcare services have undergone a great evolution in recent years. The technological development of communication networks, including the Internet, sensor networks, and M2M (Machine-to-Machine) have given rise to new architectures, applications, and standards related to addressing almost all current e-health challenges. Among the standards, the importance of OpenEHR has been recognized, since it enables the separation of medical semantics from data representation of electronic health records. However, it does not meet the requirements related to interoperability of e-health devices in M2M networks, or in the Internet of Things (IoT) scenarios. Moreover, the lack of interoperability hampers the application of new data-processing techniques, such as data mining and online analytical processing, due to the heterogeneity of the data and the sources. This article proposes an Internet of Medical Things (IoMT) platform for pervasive healthcare that ensures interoperability, quality of the detection process, and scalability in an M2M-based architecture, and provides functionalities for the processing of high volumes of data, knowledge extraction, and common healthcare services. The platform uses the semantics described in OpenEHR for both data quality evaluation and standardization of healthcare data stored by the association of IoMT devices and observations defined in OpenEHR. Moreover, it enables the application of big data techniques and online analytic processing (OLAP) through Hadoop Map/Reduce and content-sharing through fast healthcare interoperability resource (FHIR) application programming interfaces (APIs).

The Internet of Things: Impact and Implications for Health Care Delivery

“…Lack of standardization threatens the development of IoT in the health setting context, as the industry and manufacturers are yet to reach a consensus regarding wireless communication protocols and standards for machine-to-machine communication. Without a unified, standardized, and interoperable system, the adoption of IoT into health care will be greatly hindered and is unlikely to have international reach [95]. Semantic interoperability in IoT is a necessary condition for big data techniques to support decision-making processes [96].…”

Smart Assistive Architecture for the Integration of IoT Devices, Robotic Systems, and Multimodal Interfaces in Healthcare Environments

“…Once devices from different networks are able to communicate with each other, it is necessary to follow high-level protocols such as IEEE 11073-20702 or the Personal Connected Health Alliance that allow interoperability with medical devices. It would be a first step towards the IoMT (Internet of Medical Things) [ 45 ]. It is also important to address the topics of edge computing and fog computing [ 46 , 47 ] in order to improve latency in communications and to reduce bandwidth.…”

Representation of Diagnosis and Nursing Interventions in OpenEHR Archetypes

“…6 The application of the openEHR standard has been reported in several countries such as Sweden, 7 China, 8 Slovenia, 9 and Brazil. 10,11 It is a neutral approach to terminology, enabling the insertion of terminologies such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and Logical Observation Identifiers Names and Codes. Using this approach, domain experts can participate in systems development, modeling archetypes and linking appropriate terminology.…”