Institute of Digital Healthcare: Getting Active with the Data

B62d2fb1b594adea59af817a85c2757b?s=47 Iain Mansell
September 23, 2019

Institute of Digital Healthcare: Getting Active with the Data

B62d2fb1b594adea59af817a85c2757b?s=128

Iain Mansell

September 23, 2019
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  1. 1.

    Getting active with the data Using movement analytics for digital

    health innovation Dr Mark Elliott Assistant Professor of Healthcare Technologies and Behaviour Change Institute of Digital Healthcare, WMG University of Warwick
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    THE DRIVE TOWARDS DIGITAL HEALTHCARE “Digitally-enabled care will go mainstream

    across the NHS” “People will be empowered… by the ability to access, manage and contribute to digital tools, information and services” “Support for people with long-term conditions will be improved by interoperability of data, mobile monitoring devices and the use of connected home technologies” “Supporting moves towards prevention and support… all staff working in the community to have access to mobile digital services” Electronic Health Records Apps for managing conditions Online access Requires integration of data from many sources
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    THE DRIVE TOWARDS DIGITAL HEALTHCARE Integrated records Imaging Samples/Tests Consumer

    Technologies Variables Movement Variables Variables for inferring health status
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    FACILITATORS OF MOVEMENT ANALYSIS: WHY NOW? • Historically: § In

    the lab/clinic: 3D motion capture video § Out the lab: self-reported subjective measures • Potential for [near] continuous, unobtrusive monitoring of movement: § Inertial measurement § Marker-less video tracking § Fabric sensors § Smartphone/watch integration
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    THE RESEARCH CHALLENGES • Sensor technologies rapidly evolving: § Smaller

    (less obtrusive) § Low power § More variables/measures • Leads to a challenge on the data side: § Data can be ’abstract’ – e.g. acceleration, pressure, bend angle § Lacks context – no observations § Data translated to clinically (or behaviourally) meaningful measures Movement Analytics: Overcoming these challenges to Monitor, Measure and Model Movement
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    KEY AREAS IMPACTING HEALTHCARE • Orthopaedics • Physiotherapy / Rehabilitation

    • Wellbeing and related Behavioural Change • Case study research projects…
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    OSTEOARTHRITIS: BACKGROUND • Around 1/3 of people aged over 45

    in the UK have osteoarthritis [Versus Arthritis]. • Over 250,000 joint replacements are performed each year, primarily hip and knee [National Joint Registry]. Research projects: 1. OATech Network Data scoping project: Barriers and Opportunities for data sharing 2. Measuring compensatory movements using smartphone sensors (PhD project) 3. Pre-surgical planning for Total Hip Replacement.
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    Optimised positioning system: reduces edge-loading risk Can we pre-screen patients

    with high pelvic rotations? Pelvis motion capture system for pre-screening -35 -15 5 25 45 -30 -20 -10 0 10 20 30 40 50 X-Ray Measured Angle (deg) IMU Measured Angle (deg) High correlation to XR result (R2 = 87.6%; n=24) PRE-SURGICAL PLANNING OF TOTAL HIP REPLACEMENTS
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    SUPPORTING PHYSIOTHERAPY IN THE COMMUNITY Lack of guidance and support

    for physiotherapy outside the clinic Investigating technology driven solutions to support community based physiotherapy: 1. Provision of guidance and support 2. Measuring movement using low-cost devices Poor Adherence Longer Recovery
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    VIRTUAL AVATARS FOR PHYSIOTHERAPY • Design of 3D virtual avatars

    and environments which act as exercise cues to help adherence to exercise • Use motion capture to map real movements onto an avatar • Biomechanical modelling that will adapt the exercise based on patient performance • Initial study: How accurately can people follow an avatar’s movements • Used step-timing and synchronisation.
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    MEASURING MOVEMENT OUT OF THE LAB 15 Fabric sensors Ultimate

    non-intrusive sensing – embedded into clothing Commercial partner use electrically conductive yarn to form a sensor network. Identifying gait measures using ‘smart socks’ Home and community based gait assessment, captures walking in usual environments.
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    PHYSICAL ACTIVITY BEHAVIOUR CHANGE • Convert steps to virtual currency

    • Buy products on Sweatcoin marketplace 19% increase in daily step count, over 6-months Highest increase in overweight and sedentary individuals Sweatcoin
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    Researchers Felicia Eck Jill Evans Arnab Palit Breize Read Chris

    Richardson Xueyang Wang Rachel Wright PhD/Clinical Foundation Students Omar Khan Christian Kempton Arhem Qureshi Usama Rahman Amelia Thompson Abhinav Vepa Collaborators Prof. Theo Arvanitis Prof. Richard King Dr. Sakari Lemola Prof. Anu Realo Dr. Lukasz Walasek Prof. Mark Williams Commercial Collaborators: Corin Group Footfalls and Heartbeats Ltd Sweatco Ltd University Hospital Coventry & Warks NHS Trust THE TEAM
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    THANK YOU Dr Mark Elliott Assistant Professor, Healthcare Technologies &

    Behaviour Change Email: M.T.Elliott@warwick.ac.uk Web: http://go.warwick.ac.uk/markelliott Twitter: @dr_mte LinkedIn: https://www.linkedin.com/in/marktelliott