interfacing high fidelity mannequins with web- based training rachel ellaway, ph.d. 1,2, david topps...

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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