Abstract Study Objectives To evaluate the utility of multimodal low-cost approaches including actigraphy, a wrist-worn device monitoring rest/activity cycles, in identifying patients with idiopathic REM sleep behavior disorder (iRBD). Methods: Seventy patients diagnosed with sleep disorders causing different motor manifestations during sleep (iRBD, sleep apnea, restless legs syndrome) and 20 subjects without any relevant motor manifestation during sleep, underwent video-polysomnography (vPSG) and 2 week actigraphy, completed six validated RBD screening questionnaires, and sleep apps use was assessed. Actigraphy was analyzed automatically, and visually by seven blinded sleep medicine experts who rated as “no,” “possible,” and “probable” RBD. Results: Quantitative actigraphy analysis distinguished patients from controls, but not between patients with different types of motor activity during sleep. Visual actigraphy rating by blinded experts in sleep medicine using pattern recognition identified vPSG confirmed iRBD with 85%–95% sensitivity, 79%–91% specificity, 81%–91% accuracy, 57.7% ± 11.3% positive predictive value, 95.1% ± 3.3% negative predictive value, 6.8 ± 2.2 positive likelihood ratio, 0.14 ± 0.05 negative likelihood ratio and 0.874–0.933 area under the ROC curve (AUC). AUC of the best performing questionnaire was 0.868. Few patients used sleep apps; therefore, their potential utility in the evaluated patients’ groups is limited. Conclusions: Visual analysis of actigraphy using pattern recognition can identify subjects with iRBD, and is able to distinguish iRBD from other motor activities during sleep, even when patients are not aware of the disease in contrast to questionnaires. Therefore, actigraphy can be a reliable screening instrument for RBD potentially useful in the general population
