Model of Software and Hardware Infrastructure for Electrophysiology
Petr Jeˇzek
1
, Jan
ˇ
Stˇebet´ak
2
, Petr Br˚uha
2
and Roman Mouˇcek
2
1
New Technologies for the Information Society, University of West Bohemia,
Univerzitni 8, 306 14, Pilsen, Czech Republic
2
Department of Computer Science and Engineering, University of West Bohemia,
Univerzitni 8, 306 14, Pilsen, Czech Republic
Keywords:
Neuroinformatics, Electrophysiology, Infrastructure, Data Management, Semantic Web, Analytic Tool,
Semantic Framework.
Abstract:
Large amounts of EEG/ERP (electroencephalography, event-related potential) data, various data formats and
non-standardized domain description lead to incompatible results and interpretations of EEG/ ERP experimen-
tal data/metadata and to difficult communication between interested laboratories. Authors’ research group has
solved these problems and has contributed to the building of a neuroinformatics infrastructure by developing
and integrating data management and analytic tools for EEG/ERP research. The model of the software and
hardware infrastructure for electrophysiology, and the context and architecture of the developed EEG/ERP
Portal, serving to manage, share and process EEG/ERP experiments, are presented. Other additional tools are
briefly described.
1 INTRODUCTION
Our research group as a member of the Czech Na-
tional Node of International Neuroinformatics Coor-
dinating Facility (INCF) (INCF, 2012) participates in
definition and development of standardized formats
for electrophysiology research. Our efforts resulted
in the central custom solution - the EEG/ERP (elec-
troencephalography, event-related potential) Portal.
In this paper we briefly present the infrastructure
solutions in neuroscience as they are provided by the
member countries of INCF. Then the basic ideas and
the model of software and hardware infrastructure for
electrophysiology is introduced. In the next sections
the overall concept and architecture of the EEG/ERP
Portal is described. Since we need to register the
Portal as a recognizable data source, we also imple-
mented the Semantic Framework module (Section 5)
that enables users transformation of the common ob-
ject oriented source code into semantic web languages
(Berners-Lee et al., 2001). Semantic gaps between
the object-oriented code and its semantic web rep-
resentation are bridged by extension of the object-
oriented code using Java annotations. The EEG/ERP
Portal is also supposed to be integrated with various
external tools; these are described in Section VI.
2 STATE OF THE ART
The neuroinformatics infrastructure is being built in
several INCF national nodes in parallel. The INCF
portal (INCF, 2012) includes, for example, a soft-
ware center for easy storage and sharing of neuroin-
formatics software tools, a content management sys-
tem for national nodes presentation and provides ac-
cess to supercomputing resources for the neuroinfor-
matics community.
The Neuroscience Information Framework
(NIF) (Gupta et al., 2008) is a dynamic inventory
of registered Web-based neuroscience resources
containing data, materials, and tools. It advances
research in neuroscience by enabling access to public
research data and tools through an open source
environment. Currently more than 4,000 sources are
registered within NIF.
The Carmen portal (Carmen, 2012) provides stor-
age of experimental data, metadata and analysis code.
Users can also analyze their experimental data. Their
analytical tools are implemented as web services.
Within the Japan National Node, neuroinformatics
databases are organized and shared with the public in
platforms. The platforms serve as storages of exper-
imental data and documents; some of them provide
analytic tools.
Semantic web solutions for EEG/ERP data man-
352
Ježek P., Št
ˇ
ebeták J., Br˚uha P. and Mou
ˇ
cek R..
Model of Software and Hardware Infrastructure for Electrophysiology.
DOI: 10.5220/0004245103520356
In Proceedings of the International Conference on Health Informatics (HEALTHINF-2013), pages 352-356
ISBN: 978-989-8565-37-2
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
agement focus mainly on building ontologies. The
ontology built within the NEMO project provides for-
mal semantic definitions of concepts in ERP domain,
including ERP patterns, spatial, temporal, functional
(cognitive/behavioral)attributes of these patterns, and
data acquisition and analytic methods and parameters
(NEMO, 2011).
The fundamental method for obtaining ERP com-
ponents from the EEG signal is averaging. The meth-
ods used for ERP components detection include the
matching pursuit algorithm, wavelet transform and
Hilbert-Huang transform (
ˇ
Rondik et al., 2011).
3 MODEL OF SOFTWARE
AND HARDWARE
INFRASTRUCTURE
The basic idea of the model of the software and hard-
ware infrastructure for electrophysiology comes from
the set of main activities performed by researchers
during electrophysiological experiments.
First of all, researchers present a hypothesis and
design a protocol for a specific experiment. Then they
perform the experiment and collect data and related
metadata. During the experiment they have to syn-
chronize the EEG signal obtained from the scalp of
the tested subject with presented stimuli.
Second, they analyse the data using various pro-
cessing methods, interpret the data and publish re-
sults. In the long term, they do not care about the
data and lose them.
The biggest problemsfor science are the following
ones: since data are not published, conclusions and
interpretations cannot be later reproduced or verified,
the methods used for data analysis are lost or their
detailed parameters are not later traceable.
The basic aim of building the software and hard-
ware infrastructure for electrophysiology is to in-
crease both effectiveness and efficiency of scientific
research in this field. The integrated system is con-
sidered as a service (compare to (Watson et al., 2007))
providing usually the web-based interface. The main
features of this service include a long-term and sus-
tainable storage of data and related metadata collected
from experiments, various methods for data process-
ing, workflows for data processing and sharing of
data, documents, methods and workflows in groups.
The software infrastructure with the central
EEG/ERP portal is shown in Fig. 1. The hardware in-
frastructure includes stimulators for ERP experiments
and complex electronic switches for synchronization
of impulses.
Sharing is very helpful for scientific community.
However, the present organization of science does not
support it entirely. Scientists usually want to be the
first to publish their ideas or results to gain recogni-
tion and money for their future research. Therefore it
is not possible to fully open publication of ideas, data,
or processing methods at every stage of the scientific
process. As the result, sharing of knowledge has to
be limited at least at early stage of the scientific pro-
cess to defined groups of people. These groups can be
gradually enlarged as the scientific process continues.
Finally, after successful publication, the full access to
data and to used methods is possible. It is clear that
some data, for example, personal data of tested sub-
jects have to be secured according to law. Laws or
other privacy issues can even prevent any sharing of
some data. After reading the paper other researchers
can be interested in the data or their processing. For
example, they want to use the same methods or work-
flows, which are applied to their data or they want to
use original data to verify their own methods. Then
new valuable results available for publication can be
produced with adequate effort.
4 EEG/ERP PORTAL
The purpose of the EEG/ERP Portal is to serve as
a managing tool for EEG/ERP experiments. It en-
ables interested laboratories sharing and interchange
of the stored experiments (data, metadata, experimen-
tal scenarios, etc.). The features of the EEG/ERP
Portal also include sharing of knowledge, working
in groups, content management system, and full-text
search.
The data are protected by the system of user ac-
counts with defined user roles. Individual users are
grouped into self-managed groups. On the basis of
activities that the user can perform four user roles are
recognized (Reader, Experimenter, Group Adminis-
trator, and Supervisor).
We prepared a simple wizard that guides the
logged user through the process of adding an exper-
iment. Each experiment contains raw data supple-
mented by related metadata. We defined a set of meta-
data which the user is instructed to fill in through the
prepared forms. These metadata are organized in sev-
eral semantic groups. The experimenter can also de-
cide if the experiment is private or public. Public ex-
periments are downloadable for all registered users
(without personal data of tested subjects), while pri-
vate experiments are downloadable only within the
experimenter’s group.
ModelofSoftwareandHardwareInfrastructureforElectrophysiology
353
Figure 1: Component Model of EEG/ERP Infrastructure.
5 SEMANTIC WEB EXTENSION
Before we started the registration of the EEG/ERP
Portal as a recognizable neuroscience data source
within the NIF (Gupta et al., 2008), we had de-
scribed EEG/ERP experiments by a suitable ontol-
ogy. The Semantic Web uses a triple oriented repre-
sentation described by Resource Description Frame-
work (RDF) and its extension Ontology Web Lan-
guage (OWL). Despite advantages that the Seman-
tic Web (semantic description of stored data) brings,
the EEG/ERP Portal is designed using object oriented
modeling (OOM).
We tested several frameworks to enrich an ob-
ject oriented code by missing semantics. ActiveRDF
(Oren et al., 2007) is a library for accessing RDF data
from Ruby programs. eClass (Liu et al., 2007) is an
extended Java class with changed syntax that contains
additional information about fields and methods. The
Semantic Object Framework (Po-Huan et al., 2009)
adds missing semantics using embedded comments.
The tested frameworks are difficult to use either
because they do not include suitable means for adding
missing semantics, or they require a modification in
common programming syntax.
6 EXTERNAL LIBRARIES
AND TOOLS
Since the EEG/ERP Portal cooperates with a set of
associated submodules we implemented several com-
munication interfaces for external tools. The tools
working with the data stored in the EEG/ERP Por-
tal can be divided into two groups. The first group
includes tools that are accessible through an inter-
net browser. These tools are implemented as stand-
alone libraries integrated within the EEG/ERP Portal
directly. The second group of tools includes desktop
tools that are run locally on the user’s computer. The
desktop tools access data in the EEG/ERP Portal and
manage them locally.
6.1 Libraries of EEG/ERP Portal
The libraries, implemented outside the system, are
gradually added into the EEG/ERP Portal. The li-
braries are simultaneously placed into the open source
repositories where they can be used by the interested
community.
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6.1.1 Semantic Framework
With regards to the difficulties mentioned in Section 5
we decided to implement a custom framework based
on common programming technologies. It resulted
in the development of the Semantic Framework that
uses Java Annotations (Java, 2012). These annota-
tions enable us to add advanced OWL constructs into
the object oriented code. The Semantic Framework
uses the modified JenaBean (Jena, 2011) in combina-
tion with the OWL API (OWL, 2012). The JenaBean
was extended by the set of annotations mapped to ap-
propriate OWL constructs (Mouˇcek and Jeˇzek, 2010).
6.1.2 Waveforms Reader
The data obtained during the EEG/ERP experiments
are stored in the format given by the used analogue-
digital converter. We provide a module for play-
ing the stored signal in the web-based interface of
the EEG/ERP Portal. The Waveforms Reader sepa-
rates individual waveforms that are visualized using
HTML5 and CSS3 technologies. The rendering is
smooth even if the signal is sought or zoomed.
6.1.3 Analytic Methods
EEG/ERP data are supposed to be further processed.
We implemented the methods described in Section 2
as single libraries. When the user executes a method,
this method is running in a separate thread in the back-
ground. When the execution of the method ends, the
results are visualized in a chart. It ensures that a par-
allel work may be done although the execution of the
methods may be time-consuming.
6.2 External Tools
External tools work independently of the EEG/ERP
Portal. The EEG/ERP Portal provides an interface
for accessing stored experiments using Web Services
technology. The Apache CXF service framework is
used. The Web Service interface provides several
methods for accessing users experiments with their
data, metadata and scenarios. The Web Service is se-
cured by user credentials. When any request for other
functionality occurs the provided interface can be ex-
tended. An interested client only implements a Web
Service client.
6.2.1 JERPA
JERPA (Jeˇzek and Moucˇcek, 2011) is a solution for
visualization of EEG/ERP records. We extended the
present solution about the possibility to download ex-
periments from the EEG/ERP Portal. The user can
download data of his/her experiments to the local stor-
age and visualize them. The functionality for upload-
ing a new experiment to the EEG/ERP Portal is also
provided. The local storage is synchronized with the
EEG/ERP Portal in regular intervals.
6.2.2 Analytic Tools
Since processing of analytic methods is a time con-
suming task we designed and implemented the system
running on the separate server. This system imple-
ments analytic methods described in Section 2. The
system contains a simple web-based interface where
the user can list available methods and accessible
server resources. The implemented methods are ac-
cessed using the Web Service as well. When any user
wants to use this system he/she has to register.
6.2.3 Offline EEG/ERP Portal
Since there are many situations in which the Internet
connection is not available during performing experi-
ments, we prepared an offline (simplified) version of
the EEG/ERP Portal as a desktop application. The
performed experiments are stored in the local storage.
If Internet connection is available, the local storage is
synchronized with the EEG/ERP Portal.
6.2.4 Statistical Methods
The library of statistical methods was implemented as
a standalone product that runs on the separate server
as well. Currently we have implemented one way
and two way analysis of variance (ANOVA) and one
way and two way multivariate analysis of variance
(MANOVA).
6.2.5 Annotation Tool
Since we provide the EEG/ERP experiments in the
Semantic Web form using the Semantic Framework,
the domain expert has to prepare a set of annotated
POJO objects. The annotation tool is a standalone
system that allows users to load POJOs from the per-
sistence layer of the EEG/ERP Portal and annotate
them. These annotated POJOs are exported from the
Annotation Tool and integrated within the EEG/ERP
Portal.
7 CONCLUSIONS
The presented software and hardware infrastructure
ModelofSoftwareandHardwareInfrastructureforElectrophysiology
355
combines research in informatics with research in
electrophysiology. Its aim is to help researchers in
their work, which includes especially long-term col-
lection, maintenance, usage and share of EEG/ERP
data and related tools. The set of metadata is defined
reflecting experience from experiments carried out in
our laboratory, medical expertise providedby the Uni-
versity Hospital in Pilsen, INCF recommendations,
and analysis of related books and scientific papers.
The central point of the infrastructure, the EEG/ERP
Portal, is being developed as an open source using
common, basically object oriented technologies.
Since the registration of the EEG/ERP Portal as a
recognizable data source requires providing its onto-
logical description, transformation of the object ori-
ented code into the semantic web technologies is re-
quired. The Semantic Framework provides this trans-
formation and adds missing semantics using Java An-
notations. The integration of the developed frame-
work into the EEG/ERP Portal ensures the online
serialization of the stored experiments into semantic
web languages. Since processing of EEG/ERP exper-
iments includes a usage of a large set of methods, the
ways to run these methods were briefly presented.
Our future work will focus on expansion and im-
provement of the infrastructure. It includes building
of the limited social network within the EEG/ERP
Portal, cooperation of the Portal with social networks
used by the community, the full registration of the
EEG/ERP Portal within NIF, extensive work on the
methods for EEG/ERP signal processing and building
of workflow patterns. An equally important task is to
continue in the standardization of data and metadata
structures.
ACKNOWLEDGEMENTS
The work was supported by the UWB grant SGS-
2010-038 Methods and Applications of Bio- and
Medical Informatics and by the European Regional
Development Fund (ERDF), Project ”NTIS - New
Technologies for Information Society”, European
Centre of Excellence, CZ.1.05/1.1.00/02.0090.
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