Digital computer classifications of EEG sleep stages

摘要: Abstract Four programs have been developed to classify allnight sleep EEGs using digital computer techniques. Method one classified stages according the baseline cross primary wave and first derivative frequency patterns, amplitude, variability. two (sleep print) applies distance function approach as a standard mean values of measures EEG samples visually. three utilizes pattern in comparison pre-sleep resting record. four is based on average amplitude. The best agreement between visual classification was attained with “sleep print” method. effect psychotropic drugs could also be demonstrated this similarities period analysis visually samples, reliability sampling, its rapidity ease statistical portrayal, relative cost make such analyses useful practical.