Comparison between an automatic and a visual scoring method of the chin muscle tone during rapid eye movement sleep

ObjectiveTo compare two different methods, one visual and the other automatic, for the quantification of rapid eye movement (REM) sleep without atonia (RSWA) in the diagnosis of REM sleep behavior disorder (RBD).MethodsSeventy-four RBD patients (mean age, 62.14 ± 9.67 years) and 75 normal controls (mean age, 61.04 ± 12.13 years) underwent one night video-polysomnographic recording. The chin electromyogram (EMG) during REM sleep was analyzed by means of a previously published visual method quantifying the percentage of 30 s epochs scored as tonic (abnormal, ⩾30%) and that of 2 s mini-epochs containing phasic EMG events (abnormal, ⩾15%). For the computer quantitative analysis we used the automatic scoring algorithm known as the atonia index (abnormal, <0.8). The percentage correct classification, sensitivity, specificity, and Cohen kappa were calculated.ResultsThe atonia index correctly classified 82.6% of subjects, similar to the percentage of correct classifications with individual components of the visual analysis (83.2% each for tonic and phasic), and the combined visual parameters (85.9%). The sensitivity and specificity of automatic analysis (84% and 81%) was similar to the combined visual analysis (89% and 83%). The correlation coefficient between the automatic atonia index and the percentage of visual tonic EMG was high (r = −0.886, P < 0.00001), with moderately high correlation with the percentage of phasic EMG (r = −0.690, P < 0.00001). The agreement between atonia index and the visual parameters (individual or combined) was approximately 85% with Cohen’s kappa, ranging from 0.638 to 0.693.ConclusionSensitivity, specificity, and correct classifications were high with both methods. Moreover, there was general agreement between methods, with Cohen’s kappa values in the ‘good’ range. Given the considerable practical advantages of automatic quantification of REM atonia, automatic quantification may be a useful alternative to visual scoring methods in otherwise uncomplicated polysomnograms.