scholarly journals Interoperable Internet of Medical Things platform for e-Health applications

2020 ◽  
Vol 16 (1) ◽  
pp. 155014771988959 ◽  
Author(s):  
Jesús Noel Sárez Rubí ◽  
Paulo Roberto de Lira Gondim
Keyword(s):  
Sensor Network ◽  
Health Data ◽  
Machine To Machine ◽  
Semantic Level ◽  
Data Formats ◽  
Internet Of Medical Things ◽  
Definition Of ◽  
Processing Techniques ◽  
Machine Standards ◽  
Health Applications

The development of information and telecommunication technologies has given rise to new platforms for e-Health. However, some difficulties have been detected since each manufacturer implements its communication protocols and defines their data formats. A semantic incongruence is observed between platforms since no common healthcare domain vocabulary is shared between manufacturers and stakeholders. Despite the existence of standards for semantic and platform interoperability (e.g. openEHR for healthcare, Semantic Sensor Network for Internet of Medical Things platforms, and machine-to-machine standards), no approach has combined them for granting interoperability or considered the whole integration of legacy Electronic Health Record Systems currently used worldwide. Moreover, the heterogeneity in the large volume of health data generated by Internet of Medical Things platforms must be attenuated for the proper application of big data processing techniques. This article proposes the joint use of openEHR and Semantic Sensor Network semantics for the achievement of interoperability at the semantic level and use of a machine-to-machine architecture for the definition of an interoperable Internet of Medical Things platform.

scholarly journals Quaternion Processing Techniques for Color Synthesized NDT Thermography

2021 ◽  
Vol 11 (2) ◽  
pp. 790
Author(s):  
Pablo Venegas ◽  
Rubén Usamentiaga ◽  
Juan Perán ◽  
Idurre Sáez de Ocáriz
Keyword(s):  
Signal To Noise Ratio ◽  
High Capacity ◽  
Synthetic Data ◽  
Relevant Information ◽  
Color Images ◽  
Destructive Testing ◽  
Application Procedure ◽  
Definition Of ◽  
Characterization Procedure ◽  
Processing Techniques

Infrared thermography is a widely used technology that has been successfully applied to many and varied applications. These applications include the use as a non-destructive testing tool to assess the integrity state of materials. The current level of development of this application is high and its effectiveness is widely verified. There are application protocols and methodologies that have demonstrated a high capacity to extract relevant information from the captured thermal signals and guarantee the detection of anomalies in the inspected materials. However, there is still room for improvement in certain aspects, such as the increase of the detection capacity and the definition of a detailed characterization procedure of indications, that must be investigated further to reduce uncertainties and optimize this technology. In this work, an innovative thermographic data analysis methodology is proposed that extracts a greater amount of information from the recorded sequences by applying advanced processing techniques to the results. The extracted information is synthesized into three channels that may be represented through real color images and processed by quaternion algebra techniques to improve the detection level and facilitate the classification of defects. To validate the proposed methodology, synthetic data and actual experimental sequences have been analyzed. Seven different definitions of signal-to-noise ratio (SNR) have been used to assess the increment in the detection capacity, and a generalized application procedure has been proposed to extend their use to color images. The results verify the capacity of this methodology, showing significant increments in the SNR compared to conventional processing techniques in thermographic NDT.

Problems and Barriers related to the Use of Digital Health Applications: A Scoping Review Protocol (Preprint)

2021 ◽  
Author(s):  
Godwin Denk Giebel ◽  
Christian Speckemeier ◽  
Carina Abels ◽  
Kirstin Börchers ◽  
Jürgen Wasem ◽  
...  
Keyword(s):  
Scoping Review ◽  
Digital Health ◽  
Health Care Systems ◽  
Grey Literature ◽  
Screening Process ◽  
Care Systems ◽  
Research Findings ◽  
Review Protocol ◽  
Definition Of ◽  
Health Applications

BACKGROUND Usage of digital health applications (DHA) is increasing internationally. More and more regulatory bodies develop regulations and guidelines to enable an evidence-based and safe use. In Germany, DHA fulfilling predefined criteria (Digitale Gesundheitsanwendungen (="DiGA")) can be prescribed and are reimbursable by the German statutory health insurance scheme. Due to the increasing distribution of DHA problems and barriers should receive special attention. OBJECTIVE This study aims to identify relevant problems and barriers related to the use of DHA fulfilling the criteria of DiGA. The research done in this area will be mapped and research findings will be summarized. METHODS Conduct of the scoping review will follow published methodological frameworks and PRISMA-Scr criteria. Electronic databases (MEDLINE, EMBASE, and PsycINFO), reference lists of relevant articles and grey literature sources will be searched. Two reviewers will assess eligibility of articles by a two-stage (title/abstract and full-text) screening process. Only problems and barriers related to DHA fulfilling the criteria of DiGA are included for this research. RESULTS This scoping review serves to give an overview about the available evidence and to identify research gaps with regards to problems and barriers related to DiGA. Results are planned to be submitted to an indexed, peer-reviewed journal in the fourth quarter of 2021. CONCLUSIONS This is the first review identifying problems and barriers specifically to the use of the German definition of DiGA. Nevertheless, our findings can presumably be applied to other contexts and health care systems as well.

Privacy and Security in e-Health Applications

2012 ◽  
pp. 1141-1166
Author(s):  
Milan Petkovic ◽  
Luan Ibraimi
Keyword(s):  
Digital Technologies ◽  
Health Data ◽  
Security Requirements ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Privacy And Security ◽  
Security Technologies ◽  
Technological Means ◽  
The Individual ◽  
Health Applications

The introduction of e-Health and extramural applications in the personal healthcare domain has raised serious concerns about security and privacy of health data. Novel digital technologies require other security approaches in addition to the traditional “purely physical” approach. Furthermore, privacy is becoming an increasing concern in domains that deal with sensitive information such as healthcare, which cannot absorb the costs of security abuses in the system. Once sensitive information about an individual’s health is uncovered and social damage is done, there is no way to revoke the information or to restitute the individual. Therefore, in addition to legal means, it is very important to provide and enforce privacy and security in healthcare by technological means. In this chapter, the authors analyze privacy and security requirements in healthcare, explain their importance and review both classical and novel security technologies that could fulfill these requirements.

From Healthcare Services to E-Health Applications

2017 ◽  
pp. 909-940
Author(s):  
Riccardo Spinelli ◽  
Clara Benevolo
Keyword(s):  
Delivery System ◽  
Healthcare Services ◽  
Structural Features ◽  
Innovative Approach ◽  
Physical Interaction ◽  
Service Provisioning ◽  
New Approach ◽  
Healthcare Practice ◽  
Definition Of ◽  
Health Applications

The increasing adoption of ICT – and especially Internet-based technologies – in healthcare has been very fruitful and has led to the innovative approach to healthcare practice commonly known as e-health. However, the boundaries of this new approach to healthcare are not clear, as it is reflected by the various properties and taxonomies of e-health applications which have been proposed. In this chapter, we first review the definition of e-health and the main taxonomies for its constituents. Then we propose an original taxonomy for e-health applications, based on the structural features of the delivery system of the services which are digitalized: the need for a physical interaction between the subjects involved in the service provisioning and the possibility of delivering the services through Internet-based technology.

Big Data Analytics in Healthcare

2021 ◽  
pp. 85-98
Author(s):  
Sam Goundar ◽  
Karpagam Masilamani ◽  
Akashdeep Bhardwaj ◽  
Chandramohan Dhasarathan
Keyword(s):  
Big Data ◽  
Big Data Analytics ◽  
Health Data ◽  
Massive Data ◽  
Healthcare Industry ◽  
Health Records ◽  
Healthcare Data ◽  
Data Formats ◽  
Analytical Tools ◽  
Different Sources

This chapter provides better understanding and use-cases of big data in healthcare. The healthcare industry generates lot of data every day, and without proper analytical tools, it is quite difficult to extract meaningful data. It is essential to understand big data tools since the traditional devices don't maintain this vast data, and big data solves the major issue in handling massive healthcare data. Health data from numerous health records are collected from various sources, and this massive data is put together to form the big data. Conventional database cannot be used in this purpose due to the diversity in data formats, so it is difficult to merge, and so it is quite impossible to process. With the use of big data this problem is solved, and it can process highly variable data from different sources.

Ontologies in the Health Field

2011 ◽  
pp. 37-56 ◽  
Author(s):  
Michel Simonet ◽  
Radja Messai ◽  
Gayo Diallo
Keyword(s):  
Data Mining ◽  
Information Retrieval ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Health Data ◽  
Efficient Manner ◽  
Common Definition ◽  
Ontology Design ◽  
Definition Of ◽  
Health Field

Health data and knowledge had been structured through medical classifications and taxonomies long before ontologies had acquired their pivot status of the Semantic Web. Although there is no consensus on a common definition of an ontology, it is necessary to understand their main features to be able to use them in a pertinent and efficient manner for data mining purposes. This chapter introduces the basic notions about ontologies, presents a survey of their use in medicine and explores some related issues: knowledge bases, terminology, and information retrieval. It also addresses the issues of ontology design, ontology representation, and the possible interaction between data mining and ontologies.

A multi-modal health data fusion and analysis method based on body sensor network

2019 ◽  
Vol 25 (5/6) ◽  
pp. 474
Author(s):  
Lei Wang ◽  
Yibo Chen ◽  
Zhenying Zhao ◽  
Lingxiao Zhao ◽  
Jin Li ◽  
...  
Keyword(s):  
Data Fusion ◽  
Sensor Network ◽  
Health Data ◽  
Analysis Method ◽  
Body Sensor Network

The Data Fusion Survivability Analysis Technology of Wireless Sensor Network

2013 ◽  
Vol 427-429 ◽  
pp. 2630-2635
Author(s):  
Le Jun Zhang ◽  
Xin Deng ◽  
Lin Guo ◽  
Jian Pei Zhang ◽  
Hong Bo Li
Keyword(s):  
Wireless Sensor Network ◽  
Data Fusion ◽  
Sensor Network ◽  
Petri Net ◽  
Theoretical Basis ◽  
Simulation Experiment ◽  
Wireless Sensor ◽  
Analysis Model ◽  
Fusion Model ◽  
Definition Of

This paper presents the data fusion survivability analysis model of wireless sensor network (WSN) based on stochastic Petri net (SPN). First, the definition of data fusion survivability is put forward, and the data fusion model of WSN is constructed. Second, the SPN modeling method of security events, which influences the WSN, is described. Lastly, simulation experiment proves the correctness and effectiveness of the modeling of WSN data fusion survivability analysis based on SPN. This model can provide the theoretical basis and guide for designing a survivable WSN.

Sign in / Sign up

Export Citation Format

Share Document