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Epileptic Seizure: prediction and prevention. Dan Coughlin Kevin McCabe Bob McCarthy Steve Moffett. Background. Epilepsy is a brain disease that triggers seizures Electroencephalograms (EEGs) read electrical impulses from the brain. Prediction. Methods. Artificial Neural Networks (ANNs)

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Epileptic Seizure: prediction and prevention

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Epileptic seizure prediction and prevention l.jpg

Epileptic Seizure: prediction and prevention

Dan CoughlinKevin McCabeBob McCarthySteve Moffett


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Background

  • Epilepsy is a brain disease that triggers seizures

  • Electroencephalograms (EEGs) read electrical impulses from the brain


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Prediction


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Methods

  • Artificial Neural Networks (ANNs)

  • Support Vector Machines (SVM)

  • Fuzzy Logic


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ANNs – Lyapunov’s Constant

  • Impending epileptic epoch will lower chaos of brain waves

  • Lyapunov’s exponent can model the amount of chaos.

  • Exponent (normally positive) will decrease when seizure is coming


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ANNs

  • Zandi - correlation between the time intervals between positive zero crossings in the signal and an oncoming seizure

  • Use the probability density function, p(x), to model entropy and predict seizure


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SVMs

  • Represent the examples as points in space, mapped so the examples of the categories are as wide as possible

  • Use Cao’s method to classify each data series


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Fuzzy Logic

  • Creates states in between 0 and 1.

  • Eg. “very low”, “low”, “medium”, “high”, “very high”.

  • This creates a better way to classify the risk of an epileptic seizure

Ex. Cold = 0, 1; Hot = 0, 1; Warm can be interpreted as Cold = 0, Hot = 0.


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Fuzzy Logic

  • Basic Structure

    • A fuzzifier, which converts crisp values (real time values) into fuzzy values.

    • An interference engine, that applies a fuzzy reasoning mechanism to obtain a fuzzy output

    • A defuzzifier, which translates this new output into crisp values

    • A knowledge base which contains both an ensemble of fuzzy rules known as rule base and an ensemble of membership functions know as database


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Fuzzy Logic with HDT

  • Hierarchical Decision Trees

  • Greatly reduce miss-classification

  • Removes unnecessary computations from the system


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Accuracy


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Prevention


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PREVENTION

  • Prevention of epileptic seizures through medications

  • Prevention of epileptic seizures through surgery and common practices

  • Preventing a seizure with the use of Biosensors

    • Vagus Nerve Stimulation

    • Purdue University – Nanotech Sensor

    • Glutamine-Glutamate Transfer

    • Electrical Pulses on Rats

  • Most Viable Method


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PREVENTION

  • Prevention using medications

    • Most Common Medications

      • Tegretol or Carbatrol (carbamazepine)

      • Zarontin (ethosuximide)

      • Valium and similar tranquilizers such as Klonopin or Tranxene

      • Anti-convulsion – Phenytoin also known as Dilantin

    • Common Side Effects

      • Slurred Speech

      • Nausea and Vomiting

      • Rash

      • Depression

      • Headache

      • Light Headed


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PREVENTION

  • Surgery

    • Not 100% effective

    • Can be effective if taken with medication

  • Common Practices

    • Ketogenic Diet

      • Low carbohydrate, high-fat diet

      • Get plenty of sleep

      • Avoid bright, flashing lights and other visual stimuli

      • Avoid video games, watching TV, drugs and alcohol


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PREVENTION

  • VNS – Vagus Nerve Stimulation (passes thru neck to brain)

    • Designed to prevent seizures by sending regular, mild pulses of electrical energy to the brain via the vagus nerve

    • Pulses supplied by a device similar to a pacemaker

    • Works for 30 seconds of stimulation followed by 5 minutes of no stimulation

      • Holding magnetic near devices activates it outside of its programmed interval

    • Stimulation Parameters

      • Stimulation amplitude, frequency, pulse width

      • Relieves side effects (pain) and controls seizure


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PREVENTION

  • Purdue University – Nanotech Sensor

    • Transmitter and battery implanted in the brain

    • Detects the signs of an epileptic seizure before it occurs

    • Data will be picked up by an external receiver not implanted under the scalp

    • Collect data specifically related to epileptic seizures from one thousand channels or locations in the brain

      • The more channels, the more parts of the brain to look at simultaneously

    • The electrodes that will get the data are inserted in the brain through holes made in the skull and are connected directly to the transmitter by the use of wires

    • Prevents an epileptic focal seizure

      • Researchers are creating a neuroprosthesis that dispenses a neurotransmitter called GABA that calms the brain once a seizure is detected

    • Electrode is coated with engineered neurons and once they are stimulated, will release the neurotransmitter to inhibit the seizure


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PREVENTION

  • Molecular Imaging Biosensor

    • Identifies excess amounts of neurotransmitter glutamate build up in brain tissue

    • Excess levels thought to be produced by dysfunctional “glutamate-glutamine shuttle”

    • Biological sensors being developed to detect glutamate levels from shuttle process

    • Using FRET (fluorescence resonance energy transfer) imaging and electrical signals to detect evidence of alterations

    • If technology is feasible and shows that epileptic seizures occur from this imbalance, this will be a potential new therapeutic way to control epilepsy


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PREVENTION

  • Electric pulses used on rats

    • Supported by the Canadian Institutes of Health Research (CIHR) and The Natural Sciences and Engineering Council of Canada

    • Electrical stimuli are applied to the neurons and in the Mossy Fibers of the rat

    • Early results show that this technique can prevent the upcoming electrical event

    • Successful suppression of these events is achieved using an extra cellular field stimulating electrode


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PREVENTION

  • Most Viable Method

    • VNS – Vagus Nerve Stimulation

      • Most reviews from patients say it has stopped their seizures all together

      • Those that have not stopped have experienced seizures less frequent and are mild compared to before implantation of the device

      • Some patients experience side effects such as a hoarse voice or speech impediments

      • In little cases, the device has not worked at all


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Market and Products


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Overview of Market/Products

  • Most epilepsy detection/prevention devices are not yet products, and lack marketable features such as mobility, and battery life.

  • Most effective devices are for stationary patients hooked up while in a bed or a lab

  • Tradeoff in available products, processing power versus battery life.

  • Prevention devices require implantable sensors, whereas detection devices can be found out of body.


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Types of Products

  • Open Loop Implantable devices

  • Closed Loop Implantable devices

  • Seizure Detection while sleeping

  • Electrodermal Activity Sensor

  • Audio sensors


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Open Loop vs Closed Loop Devices

  • Open Loop constantly provides electrical stimulus (usually to a particular nerve or brain region) to stave off seizures.

  • Open Loop are more mobile with less hardware required, less power requirements.

  • Closed Loop read in data from the body, and react with appropriate feedback response.

  • Closed Loop require more processing power/hardware, so primarily used at stationary locations.


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Available Prevention/Detection Products

  • Emfit detects shaking movements/hyperventilation typical of seizures while sleeping

  • Placed on bed underneath sleeper, triggers alarm

http://www.tunstall.co.uk/assets/Literature/477-Epilepsy_product_datasheet.pdf


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Available Prevention/Detection Products

  • Bed Sensor with Microphone to detect audible sounds sometimes associated with seizures

http://www.medpage-ltd.com/MEDPAGE%20MANUAL%20MP2%20REV-01-01.04-09.pdf


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Available Prevention/Detection Products

Electrodermal Activity Sensor measures skin conductance.

Electrodes sense change when seizure occurs .

http://affect.media.mit.edu/pdfs/10.Poh-etal-EMBC2010.pdf


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Bibliography

  • Bezobrazova, S.; Golovko, V.; , "Comparative Analysis of Forecasting Neural Networks in the Application for Epilepsy Detection," Intelligent Data Acquisition and AdvancedComputing Systems: Technology and Applications, 2007. IDAACS 2007. 4th IEEE Workshop on , vol., no., pp.202-206, 6-8 Sept. 2007

  • Zandi, A.S.; Dumont, G.A.; Javidan, M.; Tafreshi, R.; , "An entropy-based approach topredict seizures in temporal lobe epilepsy using scalp EEG," Engineering in Medicineand Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE ,vol., no., pp.228-231, 3-6 Sept. 2009


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Bibliography

  • Ye Yuan; , "Detection of epileptic seizure based on EEG signals," Image and Signal Processing (CISP), 2010 3rd International Congress on , vol.9, no., pp.4209-4211, 16-18 Oct. 2010

  • Sukanesh, R.; Harikumar, R.; , "Fuzzy techniques and hierarchical aggregation functions decision trees for the classification of epilepsy risk levels from EEG signals," TENCON 2008 - 2008 IEEE Region 10 Conference , vol., no., pp.1-6, 19-21 Nov. 2008


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Bibliography

  • "Vagus Nerve Stimulation | Epilepsy.com." Epilepsy and Seizure Information for Patients and Health Professionals | Epilepsy.com. Ed. Steven C. Schachter. 15 Dec. 2006. Web. 03 Apr. 2011. <http://www.epilepsy.com/epilepsy/vns>.

  • Reimer, Richard J. "Real-time Imaging of the Glutamine-Glutamate Shuttle in Epilepsy - Dana Foundation." Brain and Brain Research Information - Dana Foundation. Dec. 2006. Web. 03 Apr. 2011. <http://www.dana.org/grants/imaging/detail.aspx?id=11182>.


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Bibliography

  • Dalton, Anthony; "Detecting Epileptic Seizure Using Wearable Sensor Technologies"

  • http://ama-ieee.embs.org/wp-content/themes/ieee/papers/March%2023%20-%20PM/Dalton%20Abstract%2085.pdf

  • Hively, L.M.,Kruse, K.L., Munro, N.B., Protopopescu, V.A.; "Epilepsy Forewarning Using a Hand Held Device" Febrary 2005, http://www.ornl.gov/~webworks/cppr/y2005/rpt/122819.pdf


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