TY - JOUR
T1 - Automatic 3D Video Analysis of Upper and Lower Body Movements to Identify Isolated REM Sleep Behavior Disorder
T2 - A Pilot Study
AU - Cesari, Matteo
AU - Kohn, Bernhard
AU - Holzknecht, Evi
AU - Ibrahim, Abubaker
AU - Heidbreder, Anna
AU - Bergmann, Melanie
AU - Brandauer, Elisabeth
AU - Hogl, Birgit
AU - Garn, Heinrich
AU - Stefani, Ambra
PY - 2021/11
Y1 - 2021/11
N2 - Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by dream enactment, abnormal jerks and movements during REM sleep. Isolated RBD (iRBD) is recognized as the early stage of alpha-synucleinopathies, i.e. dementia with Lewy bodies, Parkinson's disease and multiple system atrophy. The certain diagnosis of iRBD requires video-polysomnography, evaluated by experts with time-consuming visual analyses. In this study, we propose automatic analysis of movements detected with 3D contactless video as a promising technology to assist sleep experts in the identification of patients with iRBD. By using automatically detected upper and lower body movements occurring during REM sleep with a duration between 4s and 5s, we could discriminate 20 iRBD patients from 24 patients with sleep-disordered breathing with an accuracy of 0.91 and F1-score of 0.90. This pilot study shows that 3D contactless video can be successfully used as a non-invasive technology to assist clinicians in identifying abnormal movements during REM sleep, and therefore to recognize patients with iRBD. Future investigations in larger cohorts are needed to validate the proposed technology and methodology.
AB - Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by dream enactment, abnormal jerks and movements during REM sleep. Isolated RBD (iRBD) is recognized as the early stage of alpha-synucleinopathies, i.e. dementia with Lewy bodies, Parkinson's disease and multiple system atrophy. The certain diagnosis of iRBD requires video-polysomnography, evaluated by experts with time-consuming visual analyses. In this study, we propose automatic analysis of movements detected with 3D contactless video as a promising technology to assist sleep experts in the identification of patients with iRBD. By using automatically detected upper and lower body movements occurring during REM sleep with a duration between 4s and 5s, we could discriminate 20 iRBD patients from 24 patients with sleep-disordered breathing with an accuracy of 0.91 and F1-score of 0.90. This pilot study shows that 3D contactless video can be successfully used as a non-invasive technology to assist clinicians in identifying abnormal movements during REM sleep, and therefore to recognize patients with iRBD. Future investigations in larger cohorts are needed to validate the proposed technology and methodology.
KW - Humans
KW - Parkinson Disease/diagnosis
KW - Pilot Projects
KW - Polysomnography
KW - REM Sleep Behavior Disorder/diagnosis
KW - Sleep, REM
UR - https://www.scopus.com/pages/publications/85122542867
U2 - 10.1109/EMBC46164.2021.9630011
DO - 10.1109/EMBC46164.2021.9630011
M3 - Article
C2 - 34892726
SN - 2375-7477
VL - 2021
SP - 7050
EP - 7053
JO - Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
JF - Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
ER -