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



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tarix26.03.2018
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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

  • 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



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?



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