1. Improving Accessibility of Mobile Gaming
Technologies for Rehabilitation
Paul Rinne
Human Robotics Group
Department of Bioengineering

2. Technologies for Motor Rehab
Photo: Kanagawa Institute
of Technology
A Big Future
for Simple
Mobile Tech

3. The HRG
Computer
controlled wrist
flexion/extension
COMPACT ROBOTIC SYSTEMS
Haptic Knob
PASSIVE SENSOR-BASED SOLUTIONS
SITAR
HUMAN MOTOR
CONTROL
Neuroscience
+
Robotics
Going Mobile

4. 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
therapists
Only 32 movements
per session
(Charing Cross Hospital, London)

5. 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

6. 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)

7. 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)

8. 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)

9. Devices to
deliver rehab to
the largest
population at
the lowest cost
Common Global Problem

10. Patient
Self Rehabilitation
In
Hospital
At
Home
Complimenting Traditional Therapy
In
Hospital
Community
Rehab
Target Market = Hospitals - Therapists - Patients (End User)

11. Designing and Delivering Suitable
Therapy Tech
FUNCTIONAL
EFFECTIVE
1990-2010 AFFORDABLE
ACCESSIBLE
BEDSIDE/ HOME
Now
Can we leverage Mobile Tech?
PATIENT-CENTRIC

12. Rehab and mHealth
(Imperial NHS)
Low cost – Vast Uptake – Intuitive

13. mHealth App – Tablet + Smart Phone
Speech deficits:
Lingraphica
NeuroHero
Motor deficits:
DexteriamindMender
Air Traffic Contorl
Multiple
Very Few

14. 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

15. 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
SuccessfulControl(%)
• 56% could use Swipe vs 94% the Hand-grip
Weakness
(Rinne et al. 2015 - In Review)

16. GripAble
Patient attempting conventional
tablet interaction
(i.e. Swiping, button)
5mins later
Patient interacting with
GripAble
Acute stroke patient with Severe Upper Limb
impairment

17. 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!!!

18. Making Rehab Tech Globally Accessible
Christian Medical College, Vellore – India
India

19. Current Development
‘From Prototype to Product’
Funding to work with external partners
to create a commercial product

20. The Future is…
We are actively seeking….

21. 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
paul.rinne@imperial.ac.uk
@StrokePatient