Prediction of Parkinson’s
Disease Tremor Onset Using
Artificial Neural Networks
Kevin Warwick
Road Map
 Parkinson’s
Disease (PD) and
Treatments
 Deep
Brain Stimulation (DBS) Treatment
on PD Tremor
 PD
Brain Data Analysis
 Artificial
 Future
Neural Network Prediction
Research
Parkinson’s Disease

What is Parkinson's Disease (PD)?

Symptoms of Parkinson’s Disease

Tremor, Slowness of movement, Rigidity,
Poor balance

How is PD caused in theory

Substantia nigra

Dopamine
Sir William
Richard Gowers
(1886)
Current PD Treatment

Drugs – Various forms of Levodopa (L-dopa)

Advantage – effective for early PD patients, cheap

Disadvantage – kyskinesias, unpredictable on-off switching
Levodopa
and freezing, chemical side effects.

Surgical

Radio frequency Lesioning – non-reversible

Deep Brain Stimulation (DBS) – blocks nerve traffic
PD Patient’s Brain Data Gathering
Road Map
 Parkinson’s
Disease (PD) and
Treatments
 Deep
Brain Stimulation (DBS) Treatment
on PD Tremor
 PD
Brain Data Analysis
 Artificial
 Future
Neural Networks Prediction
Research
DBS Treatment on PD
 What
is Deep Brain Stimulation?
 Electrode,
a connecting cable and
Neurostimulator
 Video
(Dana Centre)
Research Project
 What
is wrong with current DBS?

Large amount of battery usage

Continuous stimulation – overrides brain

Open-Loop

Side Effects?
 Create
an intelligent DBS system which
can predict PD tremor onset using
Artificial Neural Networks (ANNs)
Road Map
 Parkinson’s
Disease (PD) and
Treatments
 Deep
Brain Stimulation (DBS) Treatment
on PD Tremor
 PD
Brain Data Analysis
 Artificial
 Future
Neural Networks Prediction
Research
PD Patients Brain Data Plot
Frequency Domain Analysis
Road Map
 Parkinson’s
Disease (PD) and
Treatments
 Deep
Brain Stimulation (DBS) Treatment
on PD Tremor
 PD
Brain Data Analysis
 Artificial
 Future
Neural Networks Prediction
Research
ANN Design Principles
MLP Results
Road Map
 Parkinson’s
Disease (PD) and
Treatments
 Deep
Brain Stimulation (DBS) Treatment
on PD Tremor
 PD
Brain Data Analysis
 Artificial
Neural Networks Prediction
 Comments
& Future Research
Comments





Aim is to accurately predict tremors and then
apply stimulation in order to stop them
occurring
Only stimulate when prediction indicates
Needs research into nature of stimulation –
frequency/magnitude/time prior for
effect/generality with different people
Doesn’t matter so much if false positive
predictions
Does matter if false negatives
More Comments
 Every
PD case is a little bit different
 Not everyone can benefit from
stimulation
 Probably not everyone will benefit from
our prediction + stimulation (subset)
 Doesn’t have to be neural network
 Hybrid methods probably best
 Neural net good for nonlinearities though
Future Research
 More
Tests on resting data – no false
calls
 Test on a broader range of patients to
assess general results with our current
MLP (male, female, age difference)
 Test on other problems
(Epilepsy/Tourette’s/Emotional)
 Apply feedback loop (MRC project)
Surprise
 Biggest
shock has been the prediction
time
 15/20 seconds seems typical
 But this means we know for sure what
will happen in the human brain 15/20
seconds before it happens
 How long could this time be?
 What else could we predict this way?
Other Points
 Developing
here an AI brain within the
human brain
 Use for other diseases – not just PD
 Could be used for emotional
changes/control
 Ethical concerns:
 What should predictor/stimulator be used
for in humans?
 What about responsibility/murders etc?