Interfacing High Fidelity Mannequins with Web- Based Training

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 (Virtual Educational Research Services Environment) Remote telemetrics tracking and database Second Life, haptics (Omni), Open. Labyrinth, 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 (Open. Labyrinth), mannequins (Laerdal. Sim. Man 3 G), light fields (virtualised cameras), 3 D 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 SAVOIR: Service-oriented Architecture for a Virtual Organization’s Infrastructure and Resources basis for the middleware layer is the SAVOIR control layer developed by NRC in Fredericton NB

SAVOIR 2 Control: Eye (session manager, resource manager, threshold manager, user manager, credential manager, authoring, logging, runtime) SAVOIR: Service-oriented Architecture for a Virtual Organization’s Infrastructure and Resources Transport: Bus – common connector for all aspects of the HSVO NEP – services, Eye – currently planning on using MULE (an open source lightweight Enterprise Service Bus (ESB))

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 SAVOIR: Service-oriented Architecture for a Virtual Organization’s Infrastructure and Resources 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)playable. HSVO NEP scenario file

Eye: Run Create session context Select and load scenario, check and load component services SAVOIR: Service-oriented Architecture for a Virtual Organization’s Infrastructure and Resources 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

Edge Wrapper Edge Service = Edge Device + Wrappers have two sides:

Messaging Service specification based on messaging and edge service behaviours: <message session. ID=”ABC” device. ID=” 123” action=”session. Status”> <configuration ID=” 456” value=”act 1” type=”cdata” /> <parameter ID=” 456” value=” 0” type=”int” /> <parameter ID=” 789” value=” 60” type=”mm. Hg” /> </configuration> </message> <message session. ID=”ABC” device. ID=” 123” action=”transfer. Data”> <parameter ID=” 456” value=” 10” type=”int” /> <parameter ID=” 789” value=” 50” type=”mm. Hg” /> </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: Sim. Man UI runtime scenario API

HSVONEP: Open. Labyrinth topography route, time counters

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 Savoir 3

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