Interfacing High Fidelity Mannequins with Web- Based Training Rachel Ellaway, Ph.D. 1,2, David Topps MD 1 1 Northern Ontario School of Medicine, 2 St 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:

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 scenario API

HSVONEP: OpenLabyrinth route, timecounters 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 MD 1 1 Northern Ontario School of Medicine, 2 St George’s University of London ?