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Session: Poster session I
Session starts: Thursday 24 January, 15:00

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Constantin Ungureanu (HOBO Heeze B.V, the Netherlands and Eindhoven University of Technology, Signal Processing Systems Group, the Netherlands )
Martien van Bussel (HOBO Heeze B.V, the Netherlands; )
Francis Tan (HOBO Heeze B.V, the Netherlands; and Kempenhaeghe, Heeze, the Netherlands)
Ronald Aarts (Eindhoven University of Technology, Signal Processing Systems Group, the Netherlands)
Johan Arends (HOBO Heeze B.V, the Netherlands and Kempenhaeghe, Heeze, the Netherlands and Eindhoven University of Technology, Signal Processing Systems Group, the Netherlands)

Abstract:
Currently there are various techniques that can be used for real-time detection of epileptic seizures. Among them, the ones based on accelerometer, heart rate changes or muscle activity show high potential to be transferred in wearable devices. Each one of these systems have its own advantages and disadvantages. Rapid heart rate increase known as tachycardia was observed to occur in 86.9 % of focal epilepsy [1]. These changes can precede and/or follow an epileptic discharge. Additionally, ECG sensors may provide information to detect medical complications that can lead to SUDEP (Sudden Death in Epilepsy). At Kempenhaeghe an algorithm based on classical CUSUM method [2] was developed to detect rapid increases in heart rate caused by an epileptic seizure. This algorithm was evaluated off-line on heart rate data acquired from 30 patients with more than 40 seizures. Three different sensor configurations were used: one (ShimmerTM Ireland) where ECG is streamed wirelessly to computer, one where ECG data was saved on a SD card inside the sensor node (Holst Center (The Netherlands) and another one where data is saved on a portable recorder (TMSiTM). The results of the analysis show that all nocturnal seizures were detected close to electrographical onset. The principal factors affecting the sensitivity of the algorithm were: lost packages during wireless transmission of ECG data, motion artefacts, time synchronization and electrode lose contact with the skin. The developed algorithm is patient adaptable and relative simple to implement on sensor nodes. Based on these results, we are currently developing a real-time system for detection of epileptic seizures and alarming composed of a portable ECG sensor node and a smart-phone to be used by patients with epilepsy on a daily basis. REFERENCES [1] F. Leutmezer , C. Schernthaner, S. Lurger , K. Pötzelberger , C. Baumgartner “Electrocardiographic changes at the onset of epileptic seizures”. Epilepsia 44: 348-54 (2003) [2] E. S. Page "Continuous Inspection Scheme". Biometrika 41 (1/2): 100–115. (1954).