In the current paper a new approach for K-complex detection using a Continuous Density Hidden Markov Model (CD-HMM) is presented. The system performance was evaluated in two manners. First using three seconds long segments of K-complexes and of background EEG (classification problem). Second using a whole night record and detecting the K complexes (detection problem). The fist test achieved an equal error rate of 7%. In the second test the system performance was compared to four trained scores that scored the signal independently. The performance of the algorithm was within the variance of the human scorers.
|Number of pages||4|
|Journal||Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings|
|State||Published - 1 Dec 2004|
|Event||Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States|
Duration: 1 Sep 2004 → 5 Sep 2004