mobile medical monitoring presented by david de roure
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Grid-based Medical Devices for Everyday Health. Mobile Medical Monitoring Presented by David De Roure. Overview of talk. Partners Scenario Grid software Demonstration Current activity Closing thoughts. Technical innovation in physical and digital life. - PowerPoint PPT PresentationTRANSCRIPT
Mobile Medical MonitoringPresented by David De Roure
Grid-based Medical Devices for Everyday Health
Overview of talk• Partners• Scenario• Grid software• Demonstration• Current activity• Closing thoughts
Technical innovation in physical and digital lifeHenk Muller (Bristol), Matthew Chalmers (Glasgow), Adrian Friday, Hans Gellerson (Lancaster),Steve Benford, Tom Rodden (Nottingham), Bill Gaver (RCA), David De Roure (Southampton),Geraldine Fitzpatrick (Sussex), Anthony Steed (UCL)
University of NottinghamTom RoddenChris GreenhalghAlastair HampshireJan HumbleJohn CroweBarry Hayes-GillCarl BarrattBen PalethorpeMark Sumner
University of OxfordLionel TarassenkoWilliam R. CobernOliver J. Gibson
University of SouthamptonDavid De RoureDon Cruickshank
University of GlasgowMatthew Chalmers
University of BristolHenk MullerChris Setchell
University of LancasterAdrian FridayOliver StorzNigel Davies
Scenario• Patients are remotely monitored using a series of
small mobile and wearable devices constructed from an arrangement of existing sensors
• Information collected from these remote devices is made available using Grid technology
• Medical professionals have tools to analyse on-line medical information and are able to access these through remote interfaces.
Grid Research Agenda• Making remote data available to the Grid in order
that a wider scientific community can access scientific data as quickly as possible, often across variable bandwidth communication services
• Making Grid facilities available to remote users when these need to be delivered across lower bandwidth communication using devices with significant display and processor limitations
1998 2001 2003 2005
Access StructureMetadata
CapturingActivity and
Process
AdditionalChallenges
ResourcesSecurity
ManagementArchitectures
(e.g P2P,Ad-hoc networs)
AutonomicBehaviour
Semantic Modelling
Remote Sensing
ComputationBroadeningResearch
FocusInformation
KnowledgeMobility
Sensors Devices Ubiquitous
Activity
ModellingSimulation
NewUses
Knowledge Discovery andRecording
Remote Access
EnvironmentalMonitoring
Activity andLab
Monitoring
EnvironmentalScientists
NewScientists
Physics
AstronomyChemistry
Engineering
Pharmacy
BioInformatics
Medical Field Scientists
“Wet” Lab Scientists
The Maturing eScience “Grid”
MIAS - Devices• Exploring the development of mobile medical
technologies that can be remotely connected onto a distributed grid infrastructure– Continuous monitoring of multiple signals via
wearable devices– Periodic monitoring using Java phones and blood
glucose measures• All signals available to a broad community and
can be processed using standard Grid Services
AsynchronousMobile World
Grid Services
Java Phone+
Blood MonitorProxy
Buffers Material for sending on
Grid based
Storage Services
StandardGrid
Service for feature detection
Wearable Devices
ProxyConverts Signalsto database record
Visualisation Services
DisplayGrid
proto
col
Grid protocol
Grid protocol
Grid protocol
Patients
Clinicians
Wearable Device
• Easy Plug and Play of Sensors• Wireless connection using 802.11• Positioning information from GPS• Nine wire sensor bus running
through wearable to allow new sensors
Sensor bus
GPS aerial
Range of different sensors• ECG• Oxygen saturation• Body movement
– Accelerometers– GPS
• All plug and play to standard bus
• Changes reported to the underlying infrastructure
Blood Glucose Monitoring • Exploring medical
devices that rely on self-reporting
• Extends web based system developed by Oxford University and e-San Ltd
• Off-the-shelf GPRS (General Packet Radio Service) mobile phone
• Blood Glucose meter
Self Reporting• Patient takes measurement• Measurement sent via
mobile phone to remote infrastructure
• Series of lifestyle questions asked as part of the clinical trial
• Users promoted for compliance.
• Current trial involves 100+ patients
Deploying on the Grid
JavaPhone Blood sugar meter
Data logger PAR sensor
PAR sensor
Other sensors
Cyberjacket (Bitsy)
ECG sensor
accelerometer
GPS receiver
9-wire bus (pluggable)
JavaPhone proxy
Blood sugar meter proxy
Data logger proxy
PAR sensor proxy
Other sensor proxy
Cyberjacket proxy
ECG sensor proxy
Other sensor proxy
Generic device proxy factory(s)
GPRS
Iridium
802.11
Multicast beacon
DF
D
D
D
S
S
S
S
S
Device Proxy Management Client
Register new device New device
configuration
Sensor data-pump
RDBMS
Sensor Database Service
Sensor data-pump
Sensor data-pump
Trial manager
Add sensor to trial database
S/w module
Live monitoring display
Sensor and device status
display
GPS live map
Ōelipse of normalityÕ
visualisation
Scrolling sensor charts
S
Data chooser/ fetcher
Table views
Graph views
Dataflow user interface
DF
D
S
New GRID Port Types: DeviceProxyFactory Device Sensor
Putting devices on the Grid• Make devices and sensors available as if they were
first class Grid Services • Two new application-independent port types:
– a generic sensor, – a generic device (assumed to host a number of sensors)
• Currently our devices require a proxy to match between these definitions and the sensor
• Project was an early GT3 adopter for prototype – Grid Service model worked– concerns about security
Sensor port type: self-descriptionName # Mutabilit
yModify?
DescriptionIdentifiedAs 1 Constant False Sensor ID, names and type
Description 1 Mutable False Expanded description, e.g. placement, accuracy, etc.
MeasurementTemplate 1 Constant False The format in which measurements are reported
MeasurementDiscard-PolicyExtensibility
1..*
Constant False Acceptable XML schema types for the measurementDiscardPolicy SDE
MeasurementPublication-PolicyExtensibility
1..*
Constant False Acceptable XML Schema types for the measurementPublishingPolicy SDE
ConfigurationExtensibility 1..*
Constant False Acceptable XML Schema types for sensor configuration SDE
ProxyStatus 1 Mutable False Current status, e.g. in contact with proxy or disconnected
Sensor port type: Externally modifiable configurationName # Mutabili
tyModify?
Description
MeasurementDiscard-Policy
1 Mutable True The conditions under which the sensor should discard historical measurements
MeasurementPublishing-Policy
1 Mutable True The conditions under which the sensor (proxy) should make a new measurement public
configuration 0..*
Mutable True Sensor-specific configuration information, e.g. sample rate
Sensor port type: measurementName # Mutability Modify? Description
Measurement 1 Mutable False The most recent measurement made by the sensor
MeasurementCounter 1 Mutable False A running counter of measurements made
MeasurementHistory 1 Mutable False The complete known history of measurements
Demo at All Hands Meeting in Nottingham, 2003
Related activities
• The Antarctic Lake Carbon Cycling project
• The Urban Pollution Monitoring Project
See demonstrationsor www.equator.ac.uk
Advanced Grid Interfaces for Environmental e-Science in the Lab and in the Field
Live clinical record• Readings appear as a live database• Standard queries and interfaces can be used to
manipulate the data• On-line services used to process the data• Exploits existing grid standards for reliability• Presents a range of different interfaces for
clinicians• Provides range of feedback to patients.
Portal for Information Access• Interactive access to live and stored information
(e.g. visualised, excel) collected from wearable devices– For use by clinicians– Could be used by patients– Also needed by “pervasive support desk”
• Accessible via pervasive devices, e.g. phone• Based on spatial model
Patient
Proxy ofMobileclinician
Location ontology
subClassOf
akt:Postal-Address Building
Room
Partitioned-Space
akt:Person
Corridor
Floor-Traversing-
Space
akt:Organisation
Enclosed-Space
Abstract-Space
Stairs Lift
subClassOf
subClassOf
subClassOfFloor
subClassOf
subClassOf
has-postal-address
is-part-of
subClassOf
is-part-of
is-part-of
has-usual-occupant
is-part-of
is-part-of is-part-of
is-adjacent-to
subClassOf
permits-access-to
is-owned-by
permits-access-to
Ian Millard
Pervasive
Semantic
Grid
Pervasive applicationsneed the Grid, e.g. Sensor Networks
Grid applications needPervasive Computinge.g. Smart Laboratory
Grid and Pervasive share issues in large scale distributed systems. e.g. service description, discovery, composition; autonomic computing. These can be aided with semantics.
FundamentallyaboutInteroperability and inference
http://ubigrid.lancs.ac.uk/
Conclusion• We have demonstrated the collection of medical
and contextual data from wearable devices using Grid infrastructure
• We have demonstrated a means of access to that data by a variety of users including use of pervasive devices
• We have provided an illustration of the important relationship between Grid and Pervasive computing
www.equator.ac.uk