Self-Similarity Analysis of Heartbeat Fluctuations in Sleep Among Female Shift Workers

Cardiovascular signals exhibit self-similarity characteristics, which are influenced by changes in autonomic nervous system (ANS) regulation caused by shift work. This study aims to assess the self-similarity properties of inter-beat interval (IBI) in healthy female shift workers and non-shift workers in different sleep stages to detect alterations in heartbeat fluctuations due to shift work. Short- and long-term self-similarity properties of the IBI signal (α1 and α2 scaling exponents, respectively) were analyzed using Detrended Fluctuation Analysis. Time and frequency indices were also calculated. In addition, Principal Component Analysis (PCA) was employed to reduce dimensionality and evaluate group separability based on the obtained features. Most indices showed similar values in the different sleep stages for both groups, but α1 during light sleep and sympathovagal balance during REM sleep showed a significant decrease in shift workers compared to non-shift workers (p<0.016). In addition, PCA was able to separate shift workers from non-shift workers and differentiate between nighttime and daytime sleep of workers. This analysis aids in identifying cardiovascular impairment associated with shift work and suggests a loss of ANS self-similarity in shift workers, indicating reduced adaptive capacity. Such alterations in ANS behavior could lead to serious health consequences related to cardiovascular disease.