Prediction of Parkinson’s Disease Tremor Onset Using Artificial Neural Networks Kevin Warwick

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 Neural Network Prediction

• Future 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

Current PD Treatment

• Drugs – Various forms of Levodopa (L-dopa)

• Advantage – effective for early PD patients, cheap
• Disadvantage – kyskinesias, unpredictable on-off switching 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 Neural Networks Prediction

• Future Research

DBS Treatment on PD

• What is Deep Brain Stimulation?

• Electrode, a connecting cable and Neurostimulator

• Video (Dana Centre)

Research Project

Road Map

• Parkinson’s Disease (PD) and Treatments

• Deep Brain Stimulation (DBS) Treatment on PD Tremor

• PD Brain Data Analysis

• Artificial Neural Networks Prediction

• Future 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 Neural Networks Prediction

• Future 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?