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Epileptic Seizure: prediction and prevention

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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  1. Epileptic Seizure: prediction and prevention Dan CoughlinKevin McCabeBob McCarthySteve Moffett

  2. Background • Epilepsy is a brain disease that triggers seizures • Electroencephalograms (EEGs) read electrical impulses from the brain

  3. Prediction

  4. Methods • Artificial Neural Networks (ANNs) • Support Vector Machines (SVM) • Fuzzy Logic

  5. 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

  6. 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

  7. 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

  8. 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.

  9. 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

  10. Fuzzy Logic with HDT • Hierarchical Decision Trees • Greatly reduce miss-classification • Removes unnecessary computations from the system

  11. Accuracy

  12. Prevention

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  21. Market and Products

  22. 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.

  23. Types of Products • Open Loop Implantable devices • Closed Loop Implantable devices • Seizure Detection while sleeping • Electrodermal Activity Sensor • Audio sensors

  24. 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.

  25. 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

  26. 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

  27. 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

  28. Bibliography • Bezobrazova, S.; Golovko, V.; , "Comparative Analysis of Forecasting Neural Networks in the Application for Epilepsy Detection," Intelligent Data Acquisition and Advanced Computing 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 to predict seizures in temporal lobe epilepsy using scalp EEG," Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE , vol., no., pp.228-231, 3-6 Sept. 2009

  29. 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

  30. 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>.

  31. 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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