automatic k-complex detection using hjorth parameters and fuzzy decision
K-complex is a stereotyped transient wave in the human electroencephalogram (EEG), it appears frequently during sleep recordings. Its role and significance have been disregarded since its discovery until recently, when the American Association of Sleep Medicine (AASM) proposed a new classification of sleep with a relevant role for the K-complexes in the definition of the sleep stages. It is now one of the key features that contribute to sleep stage assessment. K-complexes are associated with sleep arousal and can occur spontaneously or as an evoked response to external stimuli. Since the EEG has a stochastic nature, K-complex can have a wide variety of shapes and it can be difficult to distinguish it from other EEG waves. The visual scoring of K-complex is a very complex, time consuming and expensive procedure and reported agreement between human expert scorers is very poor. In this paper a new method for K-complex automatic detection is presented. The detection method is based on Hjorth parameters and employs fuzzy decision. The performance of the detection system is compared to the visual human scoring.
k-complex hjorth parameters fuzzy decision sleep eeg