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Hypnogram and Hypnodensity Analysis of REM Sleep Behaviour Disorder Using Both EEG and HRV-Based Sleep Staging Models
Jaap F van der Aar1,2, Merel M van Gilst1,3, Daan A van den Ende4
1Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
Journal of Sleep Research
|March 13, 2025
Summary
Automated sleep staging models perform poorly in Rapid-eye-movement sleep behaviour disorder (RBD). Hypnodensity analysis reveals classification ambiguities, particularly in N1+N2 and REM sleep stages, offering insights into RBD sleep characteristics.
Area of Science:
- Neurology
- Sleep Medicine
- Biomedical Engineering
Background:
- Rapid-eye-movement sleep behaviour disorder (RBD) is a sleep disorder strongly linked to Parkinson's disease.
- Accurate sleep structure assessment is crucial for understanding RBD pathophysiology and developing diagnostic tools.
- Current automated sleep stage classification (ASSC) models show suboptimal performance in RBD.
Purpose of the Study:
- To investigate the reasons behind suboptimal ASSC performance in RBD.
- To compare ASSC performance in RBD with Obstructive Sleep Apnea (OSA) patients, controlling for sleep stability.
- To explore the utility of hypnodensity analysis in characterizing RBD sleep and classification challenges.
Main Methods:
- Compared ASSC performance using neurological signals (ExG) and heart rate variability with body movements (HRVm) in RBD (n=36) and OSA patients.
- Utilized hypnograms and hypnodensity (probability distribution of ASSCs) for analysis.
- Analyzed sleep macrostructure, bout durations, and stage transition profiles.
Main Results:
- Lower 4-stage classification performance was confirmed in RBD compared to OSA for both ExG-based (RBD: κ=0.74 vs. OSA: κ=0.80) and HRVm-based (RBD: κ=0.50 vs. OSA: κ=0.63) ASSC.
- Hypnodensity analysis revealed increased ambiguity in N1+N2 and REM sleep stages for RBD.
- RBD stage transitions showed a more continuous probability distribution profile compared to abrupt changes in OSA.
Conclusions:
- Automated sleep staging in RBD remains challenging with both ExG and HRVm.
- Hypnodensity analysis provides valuable insights into the characteristics of RBD sleep and the drivers of classification disagreement.
- Sleep instability may not be the primary factor limiting ASSC agreement in RBD; transition profiles might play a more significant role.
Keywords:
REM sleep behaviour disorderelectroencephalographyhypnodensityobstructive sleep apneaphotoplethysmographysleep structureMore Related Videos
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