IP protection

 

1 Please provide a short description of the state-of-the-art and/or current trends in the field? How does the result fit into it?
Information and communication technologies have grown rapidly during the last decades and are vastly used in every aspect of human activity. 

In healthcare environment like primary care and hospitals, the most visible technological developments of the last thirty years are electronic health records, tele-medicine, bio-signal processing, medical image interpretation, and knowledge processing.

Technological advances in textile, biosensor and electrocardiography domain induced the wide spread use of bio-signal acquisition devices in daily life applications, which in turn, generated and continues to generate large amounts of bio signals. Following the pervasive healthcare directions, access to bio-signals has been diversified and is no longer restricted to the hospital domain. Therefore, research resources are fostered and research community promotes the need to extract new knowledge from bio-signals towards the adoption of new medical procedures.

In the cardiology domain, the recording of the resting 12- lead ECG continues to be the most commonly used laboratory procedure for the diagnosis of cardiac disease. As a record of the electrical activity of the heart, it is a unique technology that provides information not readily obtained by other methods. However, ECG bio-signals are not efficiently managed, mainly due to the diversity and heterogeneity of the various storage formats. ECG devices traditionally record ECGs in binary formats which are mainly proprietary, thus not inter- operable and comprehensible.

Consequently, meaningful ECG data analysis is impeded, also considering that most data formats do not provide the means to store, the equally important, context and content meta-data of the signal. Biosignal context refers to information about patient demographics, diagnosis, recording equipment, researcher/investigator, etc., while annotation and interpretation information constitute part of the bio-signal content. Retrieving biosignal metadata from other sources (if data are available and procedures are feasible) is often a prohibiting factor for important meta-analysis of the bio-signal.

In this scope, the proposed work introduces a new methodology for the unified access to bio-signal databases and the accompanying metadata. It allows decoupling information retrieval from actual underlying datasource structures and enables transparent content and context based searching from multiple data resources with context filtering. The proposed work provides a reconciled view of different ECG repositories through the use of ontolo gies, ECG domain standards and Unified Medical Language System (UMLS).

Our approach is based on the definition of an interactive global ontology which manipulates the similarities and the differences of the underlying sources to either establish similarity mappings or enrich its terminological structure. We also introduce ROISES (Research Oriented Integration System for ECG Signals), for the definition of complex content based queries against the diverse bio-signal data sources.

 

2 What is the problem/need/knowledge gap that the research result is responding to?  How was it addressed before?
As effort has been paid by the biomedical community to overcome the shortcomings of the various vendor proprietary formats, open biosignal standards have been developed. The European standard in electrocardiography domain, SCP-ECG (Standard communication protocol for Computer-assisted electrocardiography), was developed in 1993, which specifies the interchange format and a messaging procedure for ECG cart-to-host communication and for retrieval of SCP-ECG records from the host (to the ECG cart). SCP-ECG standard, as defined by TC251 committee, specifies that information is to be structured in data sections [1]. Besides the actual time-series, and some attached annotations, various types of information regarding the patient and the medical procedure are included, either as mandatory or optional fields (see specs in www.openecg.net). 

PhysioNet (www.physionet.org) is an Internet resource from the NIH (National Institutes of Health) supplying well-characterized physiological datasets and related open-source software to the biomedical research community. PhysioNet, supports WFDB (Waveform Database) format which is mostly used for ECG data, but provides data format conversions from WFDB to text and EDFplus (European Data Format plus). EDFplus is a 16bit data format supporting multiple sampling rates and multiple scaling factors, especially suitable for multichannel recordings. It is broadly accepted in the research community for data exchange and many vendors provide import and export filters [2].

Regarding bio-signal archiving and management systems, technological advancements can be seen mainly in two directions. From one side, biosignal management systems have been developed in the context of homecare systems or integration of care and thus have to deal with patient related metadata, as well as possible temporal issues, i.e. multiple signals per patient [3], as well as multimedia and multi- level patient data integration [4]. In parallel, multicentric studies and disease specific research projects have to deal distributed databases and data heterogeneity [5-7], and therefore semantic integration and semantic web techniques [8] have been deployed. In the latter case, where integration of heterogeneous data is required, automated mapping mechanisms need to be developed [9].

In a wider scale and moving beyond specific applications and domains, PhysioNet consists a very good paradigm of a biomedical resource offering access to bio-signals as a public database, however it is not yet structured in a manner that allows for content based search.

As concerns not only Physionet but the biosignal reosuces overall, mechanisms that would enable the combined access to bio-signals, their features and annotations along with the medical data that describe the context of the bio-signals, would provide a valuable tool, not only for knowledge discovery by the biomedical researcher community, but also for clinical use, in terms of medical evidence and clinical decision support, or even medical error filtering.

In this direction, the proposed work is aiming at facilitating the transparent access to biosignal resources, efficiently managing their content and context.

[1] C. Zywietz, R. Fischer, Integrated content and format checking for processing of SCP ECG records, Comput. Cardiol. 31 (2004) 37–40.

[2] B. Kemp, J. Olivan, European data format ‘plus’ (EDF+), an EDF alike standard format for the exchange of physiological data, Clin. Neurophysiol. 114 (2003) 1755–1761.

[3] S. Yoo, D. Rho, G. Cheon, J. Choi, A central repository for bio-signal data, in: IEEE International Symposium on Bio-Informatics and Biomedical Engineering Proceedings, 2008, pp. 275–277.

[4] P.C.Y. Sheu, B. Cummings, C. Cotman, C. Chubb, L. Hu, T. Wang, J. Johnson, S. Mobley, T. Stitch, Y. Inagaki, An object relational approach to biomedical database, in: IEEE International Symposium on Bio-Informatics and Biomedical Engineering Proceedings, 2000, pp. 91–98.

[5] T. Agorastos, V. Koutkias, M. Falelakis, I. Lekka, T. Mikos, A. Delopoulos, P.A. Mitkas, A. Tantsis, S. Weyers, P. Coorevits, A.M. Kaufmann, R. Kurzeja, N. Maglaveras, Semantic integration of cervical cancer data repositories to facilitate multicenter association studies: the ASSIST Approach, Cancer Inform. 8 (2009) 31–44.

[6] Y. Vadim, R.C. Bichutskiy, K.B. Rainer, H. Richard, Lathrop heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database, Cancer Inform. 2 (2006) 277–287.

[7] L. Marenco, T.Y. Wang, G. Shepherd, P.L. Miller, P. Nadkarni, QIS: a framework for biomedical database federation, J. Am. Med. Inform. Assoc. 11 (2004) 523–534.

[8] M. O’Connor, R. Shankar, S. Tu, Using Semantic Web technologies for knowledge-driven querying of biomedical data, Lect. Notes Artif. Intel. (2007) 267–276.

[9] L. Marenco, R.X. Wang, P. Nadkarni, Automated database mediation using ontological metadata mappings, J. Am. Med. Inform. Assoc. 16 (2009) 723–737.

 

3 What is the potential for further research?
The proposed methodology currently focuses on ECG, and currently two bio-signal data formats (SCP, EDF) and two data structures (relational database, ontology) have been consolidated in ROISES framework. In order to allow for extension to other signals, some alterations in the Global Ontology would be required, which are feasible, as it is a robust and interoperable system, which can be easily extended horizontally or vertically. 

Biosignal context constitutes a challenging issue, as it might involve a very wide medical domain along with its terminology, hierarchy and associations. In the work presented, current state of the art methods for modeling and mapping patient information have been applied. Nevertheless, there is space for improvement and extension.

As far as biosignal content is addressed, up to now, not all formats allow the embodiment of signal interpretation information in the binary file. A prominent paradigm towards this direction is PhysioNet’s annotation scheme which is well designed, easily comprehensible and provides encoded mnemonics for event types. Still, as this is a whole new domain, the enhancement of a bio signal framework with methods for automated calculation of annotations and signal related features, towards an integrated biomedical data and function framework, is seen as one of the interesting future perspectives of this work.

As each resource captures the content and context of the signal in various levels of detail, the definition of one or more criteria induces the exclusion of a particular resource. We therefore plan to provide the minimum and maximum requirements for the structure of the global ontology, guided by the statistical results of the query criteria selections.

ROISES could be further developed to provide the researcher with a flexible and consistent environment to define criteria not only for the queries but also for the kind of parameters to appear in the results.

 

4 What is the proposed method of IPR-protection? (patent, license, trademark etc.)
Given that most of the data used here are open to public, the resulting database cannot be protected by IP laws. Besides, in most regimes, copyright does not apply to datasets. 

However, the code that has been created in order to link these two databases to other public databases and to the web (code that is compatible with the data format and interlinks it) can be only protected by secrecy within the developer’s unit.

 

5 What are the steps that need to be taken in order to secure the IPR-protection? What is the cost of IPR-protection?
No steps need to be taken for IPR protection.

 

6 What is you overall assessment of the scientific maturity of the research result?
ROISES is a work that distils much of the experience in biosignal management and integration of the Lab of Medical Informatics, and therefore addresses in a robust manner many issues in the field and also presents the results for the user in a friendly manner. 

It is considered as a useful and stable product, with many opportunities for further enhancements and expansion of its use.

 

KEYWORDS QUANTITATIVE ASSESSMENT (0-5).

Please put X as appropriate. 1 2 3 4 5
Scientific maturity X
Synergies X
State-of-the-art/innovation X
IPR-potential X

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