Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Electrophysiologi-cal data recordings, such as electroencephalogram (EEG), are the gold standard for diagnosis and pre-surgical evaluation in epilepsy patients. The increasing trend towards multi-center clinical studies require signal visualization and analysis tools to support real time interaction with signal data in a collabora-tive environment, which are cannot be supported by traditional desktop-based standalone applications. As part of the Preven-tion and Risk Identification of SUDEP Mortality (PRISM) project, we have developed a Web-based electrophysiology data visualization and analysis platform called Cloudwave using highly scalable open source cloud computing infrastruc-ture. Cloudwave is integrated with the PRISM patient cohort identification tool called MEDCIS (Multi-modality Epilepsy Data Capture and Integration System). The Epilepsy and Sei-zure Ontology (EpSO) underpins both Cloudwave and MEDCIS to support query composition and result retrieval. Cloudwave is being used by clinicians and research staff at the University Hospital - Case Medical Center (UH-CMC) Epi-lepsy Monitoring Unit (EMU) and will be progressively de-ployed at four EMUs in the United States and the United Kingdom as part of the PRISM project.

1. Catherine
Jayapandian
Case
Western
Reserve
University,
Ohio,
USA

2.
o Background:
Electrophysiological
Data
Management
o Challenges:
Big
Data,
Mul;center
studies
o Cloudwave
Framework:
Features,
Components
o Current
Results
o Future
Direc;ons

3. o What
is
Epilepsy?
n Most
common
neurological
disorder
affec;ng
60
million
worldwide
o How
is
Epilepsy
detected?
n Mul;-­‐modal
Electrophysiological
evalua;ons
like
EEG,
EKG,
BP,
O2
and
CO2,
Sleep
data,
video
n Electroencephalogram
(EEG)
is
the
gold
standard
for
diagnosis
and
pre-­‐surgical
evalua;on

4. o Mul;-­‐center
Clinical
Study
for
Preven;on
and
Iden;fica;on
of
Risks
in
SUDEP
Pa;ents
o Key
Components
n MEDCIS
Mul$modality
Epilepsy
Data
Capture
and
Integra$on
System
n OPIC
Online
Pa$ent
Informa$on
Capture
n EpiDEA
Epilepsy
Data
Extrac$on
and
Annota$on
n Cloudwave
Electrophysiological
Signal
“Big
Data”
on
the
Cloud

5. o Ontology-­‐driven
Web-­‐
based
Electrophysiological
Epilepsy
Signal
Query,
Visualiza;on
and
Analysis
Framework
o Provides
High
Performance
Cloud
CompuBng
Infrastructure
for
handling
Electrophysiological
“Big
Data”

6. o PaBents
Cohorts
are
selected
using
the
MEDCIS
Query
Builder
o PaBent
ID
is
linked
to
Cloudwave
Signal
Viewer
All
studies
and
the
related
seizure
events
for
the
pa;ent
can
be
viewed
using
Cloudwave
interface

7. o SelecBon
of
PaBent
Study,
Montage,
Signal/
Channels
for
display
o Facilitate
creaBon
of
new
montages
(referenBal
and
bipolar)

8. o SelecBon
of
Seizure
Events/AnnotaBons
Mouse
zooming
to
;me-­‐
range
of
interest
Expor;ng
as
image
and
prin;ng
Visually
navigate
using
scroll
to
select
;me-­‐range

9. o SelecBon
of
Filters
–
SensiBvity,
HF
Filter
and
Time
Constant

10. o Electrophysiological
“Big”
Signal
Data
Storage
on
HDFS
by
collec$ng
similar
signals
for
correla$on
and
quan$ta$ve
signal
analysis
using
MapReduce
distributed
processing
n Cloudwave:
Distributed
Processing
of
“Big
Data”
from
Electrophysiological
Recordings
for
Epilepsy
Clinical
Research
Using
Hadoop,
AMIA
2013
(accepted)
o Computa;on
of
complex
Signal
Processing
algorithms
–
Cardiac
Arrhythmia,
Respiratory
Arrhythmia
and
related
measurements
for
real-­‐;me
rendering
on
Cloudwave
web
interface
(work
in
progress)

11. o PRISM
is
NIH
funded,
mul--­‐disciplinary
and
mul--­‐
center
(4
par;cipa;ng
centers)
–
recrui;ng
1200
pa;ents
o Cloudwave
establishes
the
capability
for
comprehensive
comparaBve
studies
of
SUDEP
and
near-­‐SUDEP
cases
vs.
cohort
survivors
o Cloudwave
is
a
key
component
of
PRISM
project–
facilitate
the
management
of
Electrophysiological
“Big”
Data
and
Real
Time
Web
Rendering
of
Mul-modal
signals
o For
more
details,
please
visit:
hap://prism.case.edu
o Contact:
Catherine
Jayapandian
(cpj3@case.edu)