1. EPILEPTIC SEIZURE: PREDICTION AND PREVENTION Dan Coughlin Kevin McCabe Bob McCarthy Steve 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 Rectangles: weighted average aggregations Circles: MAX/MIN decisions

11. Wave Packet Transform (WPT) Wavelet-based algorithm for real-time detection of seizures using scalp EEG Patient specific Algorithm uses index based on rhythmicity and relative energy of EEG From these, a combined seizure index (CSI) is formed from every channel/frequency of the EEG One-sided cumulative sum tests of the CSI generate the seizure warnings

12. Accuracy MethodBest Accuracy Artificial Neural Networks (ANNs) 84.7% Support Vector Machines (SVMs) 100% Fuzzy Logic97.5% Wavelet Packet Transform 90.5%

13. PREVENTION

14. 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

15. 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

16. 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 PREVENTION

17. 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

18. VNS Side Effects Paresis of the vocal fold Hoarseness Cough Symptoms were reported as very low and mild and were weakened with decreasing current Tingling in the neck Problems s Most common times these side effects occur is when the nerve is being stimulated PREVENTION

19. VNS Risks – Functional/Placement Injury to the Vagus nerve Blood vessels nearby, including the carotid artery and jugular vein Risks – Surgery Infection Bleeding Allergic reaction to the anesthesia PREVENTION

20. 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 PREVENTION

21. 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

22. 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 PREVENTION

23. 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 PREVENTION

24. MARKET AND PRODUCTS

25. 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.

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

27. 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.

28. 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

29. Available Prevention/Detection Products http://www.medpage-ltd.com/MEDPAGE%20MANUAL%20MP2%20REV-01-01.04-09.pdf Bed Sensor with Microphone to detect audible sounds sometimes associated with seizures

30. 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

31. Available Prevention/Detection Products SHIMMER uses kinematic sensors placed on the body, transmits shaking movements to a Nokia device.

32. Conclusion Prediction: All methods are viable still; SVM have proven to be 100% accurate Prevention: VNS is the most effective way to control epilepsy when medication won’t Overall: The VNS could be combined with the SVM to more accurately stop seizures; Improvements needed to provide a prevention system Still looking for a non-invasive prevention method Market is there

33. 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

34. 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

35. 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.. 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..

36. 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