Automated 3D video analysis of lower limb movements during REM sleep: a new diagnostic tool for isolated REM sleep behavior disorder

Study Objectives The differentiation of isolated rapid eye movement (REM) sleep behavior disorder (iRBD) or its prodromal phase (prodromal RBD) from other disorders with motor activity during sleep is critical for identifying α-synucleinopathy in an early stage. Currently, definite RBD diagnosis requires video polysomnography (vPSG). The aim of this study was to evaluate automated 3D video analysis of leg movements during REM sleep as objective diagnostic tool for iRBD. Methods A total of 122 participants (40 iRBD, 18 prodromal RBD, 64 participants with other disorders with motor activity during sleep) were recruited among patients undergoing vPSG at the Sleep Disorders Unit, Department of Neurology, Medical University of Innsbruck. 3D videos synchronous to vPSG were recorded. Lower limb movements rate, duration, extent, and intensity were computed using a newly developed software. Results The analyzed 3D movement features were significantly increased in subjects with iRBD compared to prodromal RBD and other disorders with motor activity during sleep. Minor leg jerks with a duration < 2 seconds discriminated with the highest accuracy (90.4%) iRBD from other motor activity during sleep. Automatic 3D analysis did not differentiate between prodromal RBD and other disorders with motor activity during sleep. Conclusions Automated 3D video analysis of leg movements during REM sleep is a promising diagnostic tool for identifying subjects with iRBD in a sleep laboratory population and is able to distinguish iRBD from subjects with other motor activities during sleep. For future application as a screening, further studies should investigate usefulness of this tool when no information about sleep stages from vPSG is available and in the home environment.

0814 A New Diagnostic Tool for Isolated REM Sleep Behavior Disorder: Automated 3D Video Analysis of Lower Limb Movements During REM Sleep

Introduction The differentiation of isolated REM sleep behavior disorder (iRBD) or its prodromal phase (prodromal RBD, pRBD) from other disorders with motor activity during sleep is critical for identifying α-synucleinopathy in an early stage. Currently, definite RBD diagnosis requires video-polysomnography (vPSG). Aim of this study was to evaluate automated 3D video analysis of leg movements during REM sleep as objective diagnostic tool for iRBD. Methods A total of 122 participants (40 iRBD, 18 pRBD, 64 with other disorders with motor activity during sleep) were recruited among patients undergoing vPSG at the Sleep Disorders Unit, Department of Neurology, Medical University of Innsbruck. 3D videos synchronous to vPSG were recorded. Lower limb movements rate, duration, extent and intensity were computed using a newly developed software. Results The analyzed 3D movement features were significantly increased in subjects with iRBD compared to pRBD and other disorders with motor activity during sleep. Minor leg jerks with a duration <2 seconds discriminated with the highest accuracy (90.4%) iRBD from other motor activity during sleep. Automatic 3D analysis did not differentiate between pRBD and other disorders with motor activity during sleep. Conclusion Automated 3D video analysis of leg movements during REM sleep is a promising diagnostic tool for identifying subjects with iRBD in a sleep laboratory population and is able to distinguish iRBD from subjects with other motor activities during sleep. For future application as a screening, further studies should investigate usefulness of this tool when no information about sleep stages from vPSG is available. Support This study was funded by the Austrian Science Fund (FWF), Project KLI 677-B31.

Time Required to Initiate a Defensive Reaction to Direct and Feint Attacks in Fencing

The two-fold purpose of this study was to analyze the time required by a fencer to initiate a defensive action in response to a direct attack, which involves identifying when the defending fencer detects the just-noticeable difference, and, secondly, to assess the effect that an attacker’s rapid armed hand movement (feint attack) has on the time required to initiate a defensive move. Twenty-four elite fencers and a fencing master were included in the study. Four adapted force plates were installed on a scaffold used as a fencing piste. A 3D video analysis system recorded the location of 2 markers installed on the fencing master’s shoulder and sword. The results confirm that the defending fencer has a mean movement time of 0.353 ± 0.028 s to perform the defensive action, which provides an advantage over the attacking fencer. The velocity of movement in the peripheral visual field has no influence on the time required by elite fencers to initiate a defensive action. This confirms the crucial role that response inhibition processes play when nonrelevant actions are perceived. Kinematic analysis of markers suggests that the eye movements of elite fencers are not the only source of information used while observing an attack.