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Improving Accessibility of Mobile Gaming Technologies for Rehabilitation
Paul RinneHuman Robotics Group
Department of Bioengineering
Technologies for Motor Rehab
Photo: Kanagawa Institute of Technology
A Big Future for Simple
Mobile Tech
The HRG
Computer controlled wrist
flexion/extension
COMPACT ROBOTIC SYSTEMSHaptic Knob
PASSIVE SENSOR-BASED SOLUTIONSSITAR
HUMAN MOTOR CONTROL
Neuroscience +
Robotics
Going Mobile
Rehabilitation Needs
Time – Repetition – Task-Oriented – Task Specific – Dose!
55% receive less than
45mins per day
Only 4–11 minutes of
upper-limb training
Resource
Limited
High cost + Low availability of
therapistsOnly 32 movements
per session
(Charing Cross Hospital, London)
Why Use Technology?
Complement traditional
therapy
Allows for high repetition
therapy
Improves outcome recording and
feedback
Motivating–31% of patients regularly perform exercises independently (Shaughnessy 2006)
(Limbs Alive - http://www.limbsalive.com/)
Increase therapy dose + Reduce supervision
= Improve cost-benefit profiles
Current Technology Downfalls
Type of Patient Only high functional patients
Accessibility:Portable + Easy to set up?
Too high for Patient / Therapist / Public Healthcare providers
High-costIndependent? (ARMin - Nef 2005)
WHY PASSIVE SENSOR-BASED SOLUTIONS?
“…more intensive rehabilitation would no longer be cost effective if the difference in rehabilitation cost was more than £685”
Cost comparison for commercial systems
Gloreha£6.5 - £10k
Hocoma£30k - >£100k
Music Glove~£900
Tyromotion£2 - £7k
Lack of Devices<£685
(NICE 2013)
Motor Disabilities: Stroke Case Study
UK: 1.2 million stroke survivors
77% have hand-arm weakness
£9 billion on Post Stroke Care
London: ~£55 million on stroke rehab
1st year rehab = £7,432 pp
Developing countries ‘Stroke Epidemic’
India: 1.7 million new strokes each year
2-3% of disabled have access to
rehab centres
(NICE 2013)
(Taylor and S. Kumar. 2012)
PatientSelf Rehabilitation
In Hospital
AtHome
Complimenting Traditional Therapy
In Hospital
CommunityRehab
Target Market = Hospitals - Therapists - Patients (End User)
Designing and Delivering Suitable Therapy Tech
FUNCTIONAL
EFFECTIVE
1990-2010 AFFORDABLE
ACCESSIBLE
BEDSIDE/ HOME
Now
Can we leverage Mobile Tech?
PATIENT-CENTRIC
mHealth App – Tablet + Smart Phone
Speech deficits: Lingraphica
NeuroHero
Motor deficits:
DexteriamindMenderAir Traffic Contorl
Multiple
Very Few
GripAble“Affordable digital handgrip working on
grip flexion and extension”
Connects with mobile technology
Highly Sensitive
Simple
Wireless
Tactile feedback
Adjustable Size
Compliant movement
Jean-Luc
Liardon
Mike
Mace
Paul
Bentley
Conventional vs GripAble
• Severe patients could use GripAble (89%) vs Swipe (0%)
0
20
40
60
80
100
Severe Moderate Mild
Swipe
Thresh 2
Hand-grip
Swipe
Thresh 3
Successfu
l C
ontr
ol (%
)
• 56% could use Swipe vs 94% the Hand-grip
Weakness
(Rinne et al. 2015 - In Review)
GripAble
Patient attempting conventional tablet interaction
(i.e. Swiping, button)
5mins laterPatient interacting with
GripAble
Acute stroke patient with Severe Upper Limb impairment
GameAble
• Interactive games specifically designed to recover handgrip control and strength
• Based on research into attentional effects on motor recovery
• Feedback: Visual, Sound, Vibration, Reward• Track: Performance, Grip strength, Control
(Motivation, Fatigue, Motor outcomes)• Modulate: Difficulty, Reward, Challenge point + Distractions!!!
Current Development
‘From Prototype to Product’
Funding to work with external partners to create a commercial product
Any Questions?
Imperial Neurosciences
Dr Paul Bentley
Dr David Soto
Prof Pankaj Sharma
Mursyida Hassan
Karl Zimmerman
Tagore Nakornchai
Susannah Fayer
Thank you for your Attention!
Human Robotics Group
Prof Etienne Burdet
Dr Michael Mace
Jean-Luc Liardon
Nawal Kinany
Rajinder Lotay
Imperial NHS
Prof Roland Veltkamp
Dr Omid Halse
Jennifer Crow
Kate Williams
Acknowledgments
@StrokePatient