THE DETECTION OF DROWSINESS AND SLEEP ONSET PERIODS FROM AMBULATORY RECORDED POLYGRAPHIC DATA

A 30 ruin sample recording at the sleep onset of 7 healthy male subjec ts was used to further develop a computer-scoring algorithm applied ea rlier For the analysis of MSLT recordings. The performance of this alg orithm was tested on 7 patients with obstructive sleep apnea by using 6 h daytime recordings including drowsiness and sleep episodes. The to tal epoch-bg-epoch agreement between visual and computer scoring was o ver 90% and the accurate detection rate of non-REM sleep was 64%. The hypnograms produced by the computer scoring corresponded sufficiently to those obtained by visual scoring. Our automatic scoring system can give a good estimation of the daytime vigilance profile but for clinic al diagnosis the results have to be verified visually. However, by usi ng modern digital recording, analyzing and scoring techniques the spee d of analysis and thus the costs can markedly been reduced as compared to traditional visual analysis. (C) 1997 Elsevier Science Ireland Ltd .