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Nocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure monitoring with the standard method of video/EEG-monitoring. We propose a method for hypermotor seizure detection based on accelerometers attached to the extremities. From the acceleration signals, multiple temporal, frequency and wavelet based features are extracted. After determining the features with the highest discriminative power, we classify movement events in epileptic anddoi:10.1109/jbhi.2013.2285015 pmid:24122607 fatcat:xhflswl72bgo7jrnnck5haue54