interfacing high fidelity mannequins with web- based training rachel ellaway, ph.d. 1,2, david topps...
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Interfacing High Fidelity Mannequins with Web- Based Training
Rachel Ellaway, Ph.D.1,2, David Topps MD1
1Northern Ontario School of Medicine, 2St George’s University of London
Context
• Simulation in med-ed increasingly multi-modal and
multifaceted
• wealth of devices such as mannequins and task trainers
• actors play simulated patients
• increased use of screen-based simulations, ranging from
narratives to immersive worlds like Second Life
• Despite richness of simulation modes, each modality stands
alone, unable to connect or interoperate with any other
Reasons for doing this
• Limitations of independent modes
• Poor ROI, poor breadth of POV
• Needs, creativity, mash-up age
• Preparation for practice still arbitrary
Dimensions of the Continuum
• Continuum of experience – sequence and cluster
• Continuum of mechanics – physical integration
• Continuum of data – aggregate and exchange
• Continuum of modeling – parallax and triangulation
Dimensions of Integration
• Technical Integration – connectivity, exchange, control
• Presentational integration – real world, synthetic, hybrid
• Narrative integration
• Evaluation integration
• Rules systems
• Activity systems
Growing integration
• Simulation labs – integration by proximity
• Roger Kneebone – Part Task Sims + Std Patients
• SGUL &Daden – Second Life and MVP
• Mannequins + EHRs
• Jacobson imaging as simulation
VERSE
VERSE (Virtual Educational Research Services Environment)
Remote telemetrics tracking and database
Second Life, haptics (Omni), OpenLabyrinth, Mitsubishi light surfaces
Requires generic data tracking model
Requires major storage and parsing
Creates new opportunities for metrics development and modeling
VERSE
HSVO (Health Services Virtual Organization)
NEPs: Network enabled platforms
CANARIE and HSVO
Edge services = device + wrapper
Heterogenous devices: virtual patients (OpenLabyrinth), mannequins (LaerdalSimMan 3G), light fields (virtualised cameras), 3D visualization (RSV and Volseg), multiple data sources (CMA, Medline)
Integrated service model for connecting, controlling and intertwining devices (physical, online, endpoint, model, source, renderer, aggregator)
Edge Infrastructure
shared control and messaging layer
edge devices are added to a shared environment as edge services
basis for the middleware layer is the SAVOIR control layer developed by NRC in Fredericton NB
SAVOIR: Service-oriented
Architecture for a Virtual Organization’s
Infrastructure and Resources
SAVOIR2
Control: Eye (session manager, resource manager, threshold manager, user manager, credential manager, authoring, logging, runtime)
Transport: Bus – common connector for all aspects of the HSVO NEP – services, Eye – currently planning on using MULE (an open source light-weight Enterprise Service Bus (ESB))
SAVOIR: Service-oriented
Architecture for a Virtual Organization’s
Infrastructure and Resources
Scenarios and Activities
Activity: end user affordances of an edge device, may be active or passive
Scenario: HSVO aggregate of activities connected through Eye-based rules
Session: instance of a scenario
Eye: Author
Create scenario from:• available edge services, • activities on services• parameters within activities
Create rules to: • change focus; • exchange data; • start, pause, stop • based on parameter values
Save as (re)playableHSVO NEP scenario file
SAVOIR: Service-oriented
Architecture for a Virtual Organization’s
Infrastructure and Resources
Eye: Run
Create session context
Select and load scenario, check and load component services
Start, stop, pause
Receive and process messages from services
Send messages to services
Record all messages from the bus, tagged with session ID and timestamp
SAVOIR: Service-oriented
Architecture for a Virtual Organization’s
Infrastructure and Resources
Edge Wrapper
Edge Service = Edge Device + Wrapper
Wrappers have two sides:
Messaging
Service specification based on messaging and edge service behaviours:
<message sessionID=”ABC” deviceID=”123” action=”sessionStatus”><configuration ID=”456” value=”act1” type=”cdata” /><parameter ID=”456” value=”0” type=”int” /><parameter ID=”789” value=”60” type=”mmHg” /></configuration></message>
<message sessionID=”ABC” deviceID=”123” action=”transferData”><parameter ID=”456” value=”10” type=”int” /><parameter ID=”789” value=”50” type=”mmHg” /></message>
Service Specification
Components:
• Messaging – to and from the Eye
•Behaviours – in response to messages
Defines how a service works
Defines wrapper:wrapper = service – device capability
Allows for any future device or variant to be added to the HSVO NEP framework
Service Architecture
HSVONEP: SimMan
UI
runtime
scenarioAPI
HSVONEP: OpenLabyrinth
route, time counters
topography
Edge Service Paths
NEP STEP
• Services for Telemetrics & Evaluation of Performance
• Builds on HSVO to include:– Extended services
– New services
– Platforms as services – ONE-ITS, CBRAIN
• Telemetrics streaming• Telemetrics coding• Telemetrics modeling• Savoir3
SISTER
• SISTER: Simulation Integration Specification for Technology Enhanced Research
• an integration specification for simulation platforms
• simple, extensible, open
• still in R&D but looking to implement soon
• ? Candidate (Canadadidate?) for future spec process
Challenges
• Profound heterogeneity
• Black boxes – commercial implementation
• Endpoints, APIs and their complete absence
• Benefits of implementation – still in R&D
• SISTER is a research spec at present
• Levels of integration and control
• Exchange – semantics, flow, emergence
• Defining conceptual as well as technical spaces
Ways Forward
• Paths of intention demonstrate need and potential
• Many ways to implement simulation continua
• Classic opportunity for standards activity
• Key role in bridging safely and confidently into practice
Interfacing High Fidelity Mannequins with Web- Based Training
Rachel Ellaway, Ph.D.1,2, David Topps MD1
1Northern Ontario School of Medicine, 2St George’s University of London
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