Office of Technology Transfer – University of Michigan

Automated Polysomnographic Assessment for Rapid Eye Movement (REM) Sleep Behavior Disorder

Technology #3367

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Researchers
Ronald D. Chervin MD
Managed By
Jessica Soulliere
Patent Protection
US Patent Pending

Background

The main features of this rapid eye movement sleep behavior disorder (RBD) has been defined as the loss of the normal muscle atonia, excessive phasic electromyographic twitches, and abnormal motor and vocal behavior emerging from REM sleep. RBD can be associated with aggressive dream content, which can lead to involuntary violent behavior resulting in injuries. According to clinical data, RBD may represent one of the earlier symptoms, preceding the diagnosis by as much as 10 years, of such neurodegenerative conditions as Parkinson’s disease, multiple-system atrophy, and dementia. However, most patients with RBD, as with many sleep disorders, are likely to be undiagnosed, despite the fact that effective treatment is available. Although a sleep study (polysomnogram) can identify abnormalities of muscle tone to aid in the diagnosis, even if no behavior occurs on the particular night of the recording, identification of the critical polysomnographic features “by eye” is usually highly subjective or else highly time-consuming if quantitative manual approach is used.

Technology

Researchers at the University of Michigan developed a computerized algorithm to identify polysomnographic features useful in the diagnosis of RBD. This algorithm can potentially be incorporated into software used with proprietary sleep recording systems.

Applications

  • Rapid eye movements sleep behavior disorder diagnostic based on computerized analysis of polysomnographic data

Advantages

  • Faster, cheaper and more accurate than currently used methods