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Background and purpose: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted people's lifestyles, changing sleep patterns. This study investigated changes in sleep patterns and disturbances in South Koreans over the past decade, including during the pandemic. Methods: We compared data from the Korean Sleep Headache Society Phase I survey (n = 2484; conducted in 2010) and the National Sleep Survey of South Korea 2022 (n = 3729; conducted in 2022), involving participants aged 20–69 years. Changes in sleep schedule, sleep duration, social jet lag, insomnia, and daytime sleepiness were explored. Results: Workday bedtimes were advanced and free-day bedtimes and workday and free-day waking times were delayed during the pandemic. Increased circadian preference for eveningness and social jet lag were noted. A significant decrease in sleep duration and sleep efficiency, along with an increased prevalence of insomnia and daytime sleepiness, was noted with age- and sex-specific variations. Conclusions: Over the past decade, including during the COVID-19 pandemic, sleep habits have changed significantly and sleep problems worsened. This study emphasize the need for more comprehensive public health strategies and research to facilitate sleep recovery in the post-pandemic period within a society known for its high prevalence of sleep deprivation. [ABSTRACT FROM AUTHOR]

Periodic Limb Movements (PLMs) are episodic, involuntary movements caused by fairly specific muscle contractions that occur during sleep and can be scored during nocturnal polysomnography (NPSG). Because leg movements (LM) may be accompanied by an arousal or sleep fragmentation, a high PLM index (i.e. average number of PLMs per hour) may have an effect on an individual’s overall health and wellbeing. This study presents the design and validation of the Stanford PLM automatic detector (S-PLMAD), a robust, automated leg movement detector to score PLM. NPSG studies from adult participants of the Wisconsin Sleep Cohort (WSC, n = 1,073, 2000–2004) and successive Stanford Sleep Cohort (SSC) patients (n = 760, 1999–2007) undergoing baseline NPSG were used in the design and validation of this study. The scoring algorithm of the S-PLMAD was initially based on the 2007 American Association of Sleep Medicine clinical scoring rules. It was first tested against other published algorithms using manually scored LM in the WSC. Rules were then modified to accommodate baseline noise and electrocardiography interference and to better exclude LM adjacent to respiratory events. The S-PLMAD incorporates adaptive noise cancelling of cardiac interference and noise-floor adjustable detection thresholds, removes LM secondary to sleep disordered breathing within 5 sec of respiratory events, and is robust to transient artifacts. Furthermore, it provides PLM indices for sleep (PLMS) and wake plus periodicity index and other metrics. To validate the final S-PLMAD, experts visually scored 78 studies in normal sleepers and patients with restless legs syndrome, sleep disordered breathing, rapid eye movement sleep behavior disorder, narcolepsy-cataplexy, insomnia, and delayed sleep phase syndrome. PLM indices were highly correlated between expert, visually scored PLMS and automatic scorings (r2 = 0.94 in WSC and r2 = 0.94 in SSC). In conclusion, The S-PLMAD is a robust and high throughput PLM detector that functions well in controls and sleep disorder patients. [ABSTRACT FROM AUTHOR]