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)

Devices to deliver rehab to

the largest population at

the lowest cost

Common Global Problem

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

Rehab and mHealth

(Imperial NHS)

Low cost – Vast Uptake – Intuitive

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!!!

Making Rehab Tech Globally Accessible

Christian Medical College, Vellore – India

India

Current Development

‘From Prototype to Product’

Funding to work with external partners to create a commercial product

The Future is…

We are actively seeking….

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