The use of AI is becoming increasingly pronounced in our daily lives. Its potential in enha g sleep disorder diagnosis has recently been uncovered. Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is an early indicator for Parkinson’s disease or dementia. Current diagnosis with a video-polysomnogram is deficient due to symptom overlap with other diseases and subjectivity of data from complex sleep variables. The newly enhanced AI algorithm detects rate, ratio, magnitude and velocity of movements, as well as ratio of immobility during REM sleep captured in video polysomnograms. An accuracy of up to 91.1% was achieved using this technology and demonstrates promising clinical potential in iRBD diagnosis. The ability of AI to automatically detect REM sleep also suggests its potential for use in home settings, offering a pathway to more accessible and widespread diagnosis for a condition that could otherwise easily go unnoticed. ¹⁷

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