Assessment of Multifractal-Multiscale Properties of Heart Rate Variability in Sleep Disorders

Area of Science:

• Cardiovascular physiology
• Nonlinear dynamics
• Sleep medicine

Background:

• Cardiovascular signals, particularly heart rate variability (HRV), exhibit complex self-similar properties.
• Sleep disorders are known to impact autonomic nervous system (ANS) function and cardiovascular control.
• Traditional HRV analysis may not fully capture the intricate alterations caused by sleep-related conditions.

Purpose of the Study:

• To investigate the multifractal-multiscale characteristics of HRV components in patients with sleep apnea and REM sleep behavior disorder (RBD).
• To identify specific alterations in cardiovascular control mechanisms associated with these sleep disorders.
• To explore the potential of advanced fractal analysis for early detection of cardiovascular impairment.

Main Methods:

• Decomposition of HRV signals into intrinsic mode functions (IMFs) using complete ensemble empirical mode decomposition with adaptive noise.
• Analysis of IMFs using multiscale-multifractal detrended fluctuation analysis (MF-DFA).
• Calculation of a multifractal index to quantify multifractality across different scales.

Main Results:

• Sleep apnea patients showed increased scaling coefficients (α(q, τ)) in IMF1 and decreased values in IMF4, potentially linked to respiratory events.
• REM sleep behavior disorder (RBD) patients exhibited decreased α(q, τ) in IMF1-IMF3 at short scales, indicating abnormal autonomic modulation.
• Significant alterations in the fractal properties of HRV were observed, reflecting autonomic dysfunction in sleep.

Conclusions:

• Multifractal-multiscale analysis of HRV provides deeper insights into cardiovascular autonomic control during sleep.
• These findings highlight specific fractal alterations in HRV associated with sleep apnea and RBD.
• This advanced analytical approach offers potential for the early detection of cardiovascular impairment in sleep disorder patients.