In this paper, a large scale evaluation of time-domain and frequency domain features of electroencephalographic and electrocardiographic signals for seizure detection was performed. For the classification we relied on the support vector machines algorithm. The seizure detection architecture was evaluated on three subjects and the achieved detection accuracy was more than 90% for two of them and slightly lower than 90% for the third subject.