RehabNet: A Distributed Architecture for Motor and Cognitive Neuro-Rehabilitation
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Transcript of RehabNet: A Distributed Architecture for Motor and Cognitive Neuro-Rehabilitation
RehabNet: A Distributed Architecture
for Motor and Cognitive Neuro-
Rehabilitation
Athanasios Vourvopoulos
PhD Student
University of Madeira
Madeira Interactive Technologies Institute
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
• Stroke
• Problem Statement
• RehabNet
• Methods
• Implementation
• Preliminary Assessment
• Conclusions
• Future work
Contents
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Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Ageing Population & Stroke
3
% of the
population
with 60 +
years
2012
2050
~20%
30+%
• Chronic
conditions
• Loss of
independence
• High societal cost
• Unaffordable for
public health
systems
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Limitations of the Current Rehabilitation tools/technics:
• Require patients to have some degree of motor and/or cognitive control*
• We do not know how the brain reacts to a VR treatment
• Is there any functional remapping?
• What is the most efficient way to achieve it
Current Limitations
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K. Laver, S. George, S. Thomas, J. E. Deutsch, and M. Crotty, “Cochrane review: virtual reality for stroke
rehabilitation,” Eur J Phys Rehabil Med, vol. 48, no. 3, pp. 523–530, Sep. 2012
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
RehabNet
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RehabilitationOptimal rehabilitation guidelines (e.g, training
intensity, specificity).
NeuroscienceCortical reorganization, other neural pathways, …
InteractionCustomization, usability, …
Serious Games/VRIndividualization, feedback, motivation,
quantification, …
Interactive
Technologies
for
Motor/Cogniti
ve
Rehabilitation
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Methods
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RehabNet Framework: requirements hierarchy
Why: Broad access to rehabilitation training
to the wider possible range of patients.
How: Off-the-shelf electrophysiological
signal acquisition and position tracking
devices.
Why: Maximizing adherence to treatment to
maximize its effect.
How: Lowering the access threshold (using
low-cost interfaces ; content in the cloud;
social and gamified elements to improve
engagement.
Why: Novel VR therapies need to be based
on clinical guidelines and neuroscientific
hypotheses of recovery.
How: Evaluating improvement in
performance, the correctness of the
rehabilitation approach, and validation of
the neuroscientific hypotheses of recovery.
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Methods
7
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Implementation
8
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Implementation
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Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Quantification
10
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
A proof of concept study has been performed with three patients:
• 2 male and 1 female
• Age: 52, 68 and 72
• Left hemisphere stroke
• Right-sided hemiparesis
Experimental protocol:
• Paper & Pencil
• Mouse
• AnTS
• Kinect
• Keyboard*
Preliminary Assessment
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Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Conclusions
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• RehabNet explores the use of non-invasive ICT for
neuro-rehabilitation post-stroke
• Low-cost novel treatments
• In-home rehabilitation
• Widened inclusion criteria
• Social networking (clinicians-patients-family)
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Future Steps
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• Deploying the RehabNet system to perform a
randomised controlled trial (RCT) to assess
the impact of the motor-and-cognitive training
component.
• Generalize the developed motor-and-
cognitive training paradigm by replacing the
active movement component by a
neurofeedback paradigm.
Athanasios Vourvopoulos
HealthCom’13 - Lisbon August 25, 2014
Thank You
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