This paper presents the design and implementation of a real-time epilepsy detection filter that is suitable for closed-loop seizure suppression. The design aims to minimize the detection delay, while a reasonable average detection rate is obtained. The filter is based on a complex Morlet wavelet and uses an adaptive thresholding strategy for the seizure discrimination. This relatively simple configuration allows the algorithm to run on a cheap and readily available microprocessor prototyping platform. The performance of the filter is verified using both in vivo real-time measurements as well as simulations over a pre-recorded EEG dataset (29.75 hours with 1914 seizures). An average detection delay of 492 ms is achieved with a sensitivity of 96.03% and a specificity of 93.60%.
|Title of host publication||IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||4|
|Publication status||Published - 9 Dec 2014|
|Event||10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014 - Lausanne, Switzerland|
Duration: 22 Oct 2014 → 24 Oct 2014
|Series||IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings|
|Conference||10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014|
|Period||22/10/14 → 24/10/14|
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© 2014 IEEE.