Sleep RR-Interval U-Patterns and Their Correlation to Movement Events Sasan Yazdani *,1 , Alexandre Cherqui 1 , Nicolas Bourdillon 2 , Gregoire Millet 2 , Jean-Marc Vesin 1 1 Applied Signal Processing Group, Swiss Federal Institute of Technology, Lausanne, Switzerland 2 ISSUL, Institute of Sport Sciences, Faculty of Biology and Medicine, Unil, Lausanne, Switzerland Abstract The aim of this work is to investigate the relation be- tween a phenomenon called ”U-patterns” and their possi- ble correlation to movement events in the context of sleep deprivation. U-patterns take place in the RR-interval time series during sleep. As their name suggests, these patterns present a U-shaped decrease-increase in RR-intervals, with a duration lasting from 20 to 40 seconds together with a minimum decrease of 15% in the local RR mean value. Over a span of 17 days, 15 healthy subjects (7males, 22.1 ± 1.7 yrs.) participated in a study of three subse- quent stages. First, a baseline phase of seven days, dur- ing which the subjects slept normally. Immediately af- ter, a sleep deprivation phase with a duration of three days, during which participants slept only three hours per night. Finally, in a 7-day recovery phase subjects went back to their normal baseline sleeping routine. Subjects underwent polysomnography (PSG) data acquisition while sleeping. U-patterns were extracted from RR-intervals while movement events were extracted from different PSG channels. Their relative temporal layout was studied to determine whether U-patterns are caused due to subject movement during sleep or vice versa. Results show that U- pattern/movement events are correlated, always initiated by U-patterns with movement events terminating before the termination of their respective U-patterns. 1. Introduction Sleep analysis can reveal much information about human physiological health. A comprehensive sleep study can be performed through polysomnography (PSG) as it offers simultaneous recording of multiple bio- physiological parameters. PSG records a number of bio-signals, from the electrical activity of the brain, i.e. electroencephalography (EEG), to eye movement tracking through electrooculography (EOG), nasal and abdominal respiration signals. Moreover, muscle and heart activity are monitored respectively via EMG and ECG recordings. The benefits of sleep assessment have been pointed out in the literature, with researches showing the negative ef- fects of sleep deprivation on human health. Low quality of sleep and sleep deprivation have been linked to cognitive impairment [1], hypertension [2] and myocardial hypertro- phy [3]. This highlights the importance of PSG analysis, which has already been deemed as an effective measure to identify disorders such as sleep apnea [4, 5], insomnia [6], fatigue [7]. Even with the numerous studies carried out on sleep analysis,this interesting field remains one of the active re- search areas. The aim of this study is to investigate an intriguing phenomenon called ”U-patterns”, which mani- fest itself in the RR-interval time series during sleep. U- patterns were introduced and studied in [8] and [9], how- ever the state-of-the-art had indirectly observed their ex- istence [10]. This study aims to further investigate these patterns and analyze their correlation to movement events during sleep. The remainder of this paper is organized as follows. Section 2 describes the research material used in this study. A short description of U-patterns, and the processing tech- niques to extract them as well as movement events are pro- vided in section 3. Results are presented and discussed in Section 4. Finally in Section 5, the main conclusions of this work are drawn. 2. Research Material The data used in this study were collected from 15 sub- jects (7 males and 8 females), whose anthropometric pa- rameters are reported in Table 1. This study was carried out over a span of 17 days, in three successive stages. First a "baseline" phase lasting for seven days, during which the subjects slept normally with no constraints. Following the baseline, subjects went through a "sleep deprivation" phase with a duration of Table 1. Anthropometric parameters of this study. Characteristic mean ± std(N = 15) Range Age (years) 22.1 ± 1.7 18 - 25 Height (cm) 172.7 ± 8.8 160 - 196 Weight (kg) 65.9 ± 11.6 52 - 92 Computing in Cardiology 2019; Vol 46 Page 1 ISSN: 2325-887X DOI: 10.22489/CinC.2019.052