Mobile Medical Monitoring Presented by David De Roure

1. Grid-based Medical Devices for Everyday Health Mobile Medical MonitoringPresented by David De Roure

2. Overview of talk • Partners • Scenario • Grid software • Demonstration • Current activity • Closing thoughts

3. Technical innovation in physical and digital life Henk 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)

5. University of SouthamptonDavid De RoureDon Cruickshank University of GlasgowMatthew Chalmers University of BristolHenk MullerChris Setchell University of LancasterAdrian FridayOliver StorzNigel Davies University of NottinghamTom RoddenChris GreenhalghAlastair HampshireJan HumbleJohn CroweBarry Hayes-GillCarl BarrattBen PalethorpeMark Sumner University of OxfordLionel TarassenkoWilliam R. CobernOliver J. Gibson

6. 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.

7. 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

8. Broadening ResearchFocus Activity Computation Knowledge Sensors Devices Mobility Information Semantic Modelling AutonomicBehaviour Ubiquitous ResourcesSecurityManagement Capturing Activity and Process Access Structure Metadata Additional Challenges Remote Sensing Architectures (e.g P2P, Ad-hoc networs) Modelling Simulation Knowledge Discovery and Recording Remote Access Activity andLab Monitoring NewUses Environmental Monitoring Physics Pharmacy Medical Field Scientists NewScientists Chemistry Astronomy BioInformatics “Wet” Lab Scientists Engineering EnvironmentalScientists The Maturing eScience “Grid” 1998 2001 2003 2005

9. 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

10. Asynchronous Mobile World Grid Services Grid protocol Java Phone +Blood Monitor StandardGrid Service for feature detection Proxy Buffers Material for sending on Grid based Storage Services Grid protocol Grid protocol Patients Visualisation Services Proxy Converts Signals to database record Wearable Devices Grid protocol Display Clinicians

11. 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

12. Range of different sensors • ECG • Oxygen saturation • Body movement • Accelerometers • GPS • All plug and play to standard bus • Changes reported to the underlying infrastructure

13. 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

14. 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

15. Deploying on the Grid

16. 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

17. Sensor port type: self-description Name # Mutability Modify? Description IdentifiedAs 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 Name # Mutability Modify? 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 Name # 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 Sensor port type: Externally modifiable configuration Sensor port type: measurement

18. Demo at All Hands Meeting in Nottingham, 2003

22. Related activities Advanced Grid Interfaces for Environmental e-Science in the Lab and in the Field • The Antarctic Lake Carbon Cycling project • The Urban Pollution Monitoring Project See demonstrationsorwww.equator.ac.uk

23. 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.

24. 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

25. Patient Proxy of Mobile clinician

27. Location ontology Ian Millard

28. Semantic Pervasive Grid

29. Fundamentally about Interoperability and inference Grid and Pervasive share issues in large scale distributed systems. e.g. service description, discovery, composition; autonomic computing. These can be aided with semantics. Pervasive applications need the Grid, e.g. Sensor Networks Grid applications need Pervasive Computing e.g. Smart Laboratory

30. http://ubigrid.lancs.ac.uk/

31. 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

32. www.equator.ac.uk