Heart rate variability at bedtime predicts subsequent sleep features

Menstrual Cycle Variations in Wearable-Detected Finger Temperature and Heart Rate, But Not in Sleep Metrics, in Young and Midlife Individuals

Most studies about the menstrual cycle are laboratory-based, in small samples, with infrequent sampling, and limited to young individuals. Here, we use wearable and diary-based data to investigate menstrual phase and age effects on finger temperature, sleep, heart rate (HR), physical activity, physical symptoms, and mood. A total of 116 healthy females, without menstrual disorders, were enrolled: 67 young (18-35 years, reproductive stage) and 53 midlife (42-55 years, late reproductive to menopause transition). Over one menstrual cycle, participants wore Oura ring Gen2 to detect finger temperature, HR, heart rate variability (root mean square of successive differences between normal heartbeats [RMSSD]), steps, and sleep. They used luteinizing hormone (LH) kits and daily rated sleep, mood, and physical symptoms. A cosinor rhythm analysis was applied to detect menstrual oscillations in temperature. The effect of menstrual cycle phase and group on all other variables was assessed using hierarchical linear models. Finger temperature followed an oscillatory trend indicative of ovulatory cycles in 96 participants. In the midlife group, the temperature rhythm's mesor was higher, but period, amplitude, and number of days between menses and acrophase were similar in both groups. In those with oscillatory temperatures, HR was lowest during menses in both groups. In the young group only, RMSSD was lower in the late-luteal phase than during menses. Overall, RMSSD was lower, and number of daily steps was higher, in the midlife group. No significant menstrual cycle changes were detected in wearable-derived or self-reported measures of sleep efficiency, duration, wake-after-sleep onset, sleep onset latency, or sleep quality. Mood positivity was higher around ovulation, and physical symptoms manifested during menses. Temperature and HR changed across the menstrual cycle; however, sleep measures remained stable in these healthy young and midlife individuals. Further work should investigate over longer periods whether individual- or cluster-specific sleep changes exist, and if a buffering mechanism protects sleep from physiological changes across the menstrual cycle.

Comprehensive evaluation of machine learning algorithms for predicting sleep-wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate variability

Introduction

Perinatal women tend to have difficulties with sleep along with autonomic characteristics. This study aimed to identify a machine learning algorithm capable of achieving high accuracy in predicting sleep-wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate variability (HRV).

Methods

Nine HRV indicators (features) and sleep-wake conditions of 154 pregnant women were measured for 1 week, from the 23rd to the 32nd weeks of pregnancy. Ten machine learning and three deep learning methods were applied to predict three types of sleep-wake conditions (wake, shallow sleep, and deep sleep). In addition, the prediction of four conditions, in which the wake conditions before and after sleep were differentiated-shallow sleep, deep sleep, and the two types of wake conditions-was also tested.

Results and Discussion

In the test for predicting three types of sleep-wake conditions, most of the algorithms, except for Naïve Bayes, showed higher areas under the curve (AUCs; 0.82-0.88) and accuracy (0.78-0.81). The test using four types of sleep-wake conditions with differentiation between the wake conditions before and after sleep also resulted in successful prediction by the gated recurrent unit with the highest AUC (0.86) and accuracy (0.79). Among the nine features, seven made major contributions to predicting sleep-wake conditions. Among the seven features, "the number of interval differences of successive RR intervals greater than 50 ms (NN50)" and "the proportion dividing NN50 by the total number of RR intervals (pNN50)" were useful to predict sleep-wake conditions unique to pregnancy. These findings suggest alterations in the vagal tone system specific to pregnancy.

Heart Rate Variability and Chronotype in Young Adult Men

Whether morning heart rate variability (HRV) predicts the magnitude of its circadian variation in the absence of disease or is influenced by chronotype is unclear. We aimed to quantify associations between (1) morning HRV and its diurnal change, and (2) morning HRV and a Morningness−Eveningness Questionnaire (MEQ)-derived chronotype. Resting electrocardiograms were obtained in the morning and evening on separate days in a counterbalanced order to determine the mean RR interval, root mean square of successive differences (RMSSD), and standard deviation of normal-to-normal RR intervals (SDNN) in 23 healthy men (24.6 ± 3.4 yrs; body mass index: 25.3 ± 2.8 kg/m2). The MEQ was completed during the first laboratory visit. Morning RMSSD and SDNN were significantly higher (Ps < 0.05) than evening values. Morning RMSSD and SDNN were associated with their absolute (Ps < 0.0001), and relative diurnal changes (Ps < 0.01). No associations were observed between HRV parameters and the MEQ chronotypes (Ps > 0.09). Morning HRV was a stronger determinant of its evening change than chronotype. Greater diurnal variation in HRV was dependent on higher morning values. Strategies to improve basal HRV may therefore support healthier cardio-autonomic circadian profiles in healthy young men.

A Workcation Improves Cardiac Parasympathetic Function during Sleep to Decrease Arterial Stiffness in Workers

A “Workcation” (combining work and vacation) has become increasingly common. Traditionally, the workcation focus has been on productivity; however, data showing associations between workcations and improvements in employees’ health are lacking. Therefore, this study examines the effects of a workcation on blood pressure, arterial stiffness, heart rate, autonomic nervous system function, and physical activity. Twenty healthy employees participating in a five-day workcation project at a large private company agreed to participate in this study. Data on arterial stiffness, heart rate, autonomic nerve activity, and physical activity were collected before, during, and after the workcation. Arterial stiffness, blood pressure, and heart rate significantly decreased (p < 0.05); meanwhile, physical activity levels and parasympathetic function during sleep significantly increased during the workcation (p < 0.05). Thus, a workcation implies a new way of working that improves employees’ cardiovascular indices and parasympathetic function during sleep.

The association between chronotype and sleep quality among female home care workers performing shift work

There is a scarcity of evidence on the association between shift work, sleeping parameters, heart rate variability (HRV), and chronotype, i.e., morningness and eveningness. The aims of this study were to 1) compare participants with different chronotypes (morning (M), evening (E), or neither (N)) in terms of their total sleep time, sleep efficiency, and HRV parameters, taking their age into account, and 2) examine whether self-reported work-related stress, the length of the working career and years performing shift work affect this association. The participants of the study were home care workers working in two shifts in one municipality in Eastern Finland (N = 395). Of these, 52 females (mean age 42.78 y, SD 12.92 y) completed the study questionnaire and participated in physiological measurements. Several sleep-related parameters were assessed (total sleep time, sleep efficiency, number of awakenings, and length of awakening) and indices of autonomic nervous system based on HRV were calculated. The participants worked in two shifts: a morning shift (7:00-15:00 h) and an evening shift (14:00-21:30 h). All these parameters were assessed during the night before the first work shift (N1), the night before the second work shift (N2), the night before the final work shift (N3), and the night before the first day off work (N4). According to the results, 21.2% of the participants were M-types, 17.3% were E-types, and 61.5% were N-types. On average, the participants had been in working life for 18.8 years and performing shift work for 13.7 years. On night N3, E-types had a significantly shorter total sleep time and spent less time in bed compared to M- and N-types. The total sleep time of M-type and N-type participants was on average 66 minutes and 82 minutes longer, respectively, when compared to E-types on night N3. There were no statistically significant differences in actigraphy-based sleep quality parameters between M-, N-, and E-types on nights N1, N2, and N4. Our results together indicate that M- and N-type individuals may have better sleep quality than E-types, which was also reflected in HRV parameters. Further research with longitudinal study design and workplace interventions is needed to determine how the chronotype can be optimally and individually utilized to improve the health and well-being of morning-type and evening-type people. This is particularly important for both younger and older workers entering the workforce to support healthier and longer working lives.

Lifestyle Modification Using a Wearable Biometric Ring and Guided Feedback Improve Sleep and Exercise Behaviors: A 12-Month Randomized, Placebo-Controlled Study

Purpose: Wearable biometric monitoring devices (WBMD) show promise as a cutting edge means to improve health and prevent disease through increasing accountability. By regularly providing real-time quantitative data regarding activity, sleep quality, and recovery, users may become more aware of the impact that their lifestyle has on their health. The purpose of this study was to examine the efficacy of a biometric tracking ring on improving sleep quality and increasing physical fitness over a one-year period. Methods: Fifty-six participants received a biometric tracking ring and were placed in one of two groups. One group received a 3-month interactive behavioral modification intervention (INT) that was delivered virtually via a smartphone app with guided text message feedback (GTF). The other received a 3-month non-directive wellness education control (CON). After three months, the INT group was divided into a long-term feedback group (LT-GTF) that continued to receive GTF for another nine months or short-term feedback group (ST-GTF) that stopped receiving GTF. Weight, body composition, and VO2max were assessed at baseline, 3months, and 12months for all participants and additionally at 6 and 9months for the ST-GTF and LT-GTF groups. To establish baseline measurements, sleep and physical activity data were collected daily over a 30-day period. Daily measurements were also conducted throughout the 12-month duration of the study. Results: Over the first 3months, the INT group had significant (p<0.001) improvements in sleep onset latency, daily step count, % time jogging, VO2max, body fat percentage, and heart rate variability (rMSSD HRV) compared to the CON group. Over the next 9months, the LT-GTF group continued to improve significantly (p<0.001) in sleep onset latency, daily step count, % time jogging, VO2max, and rMSSD HRV. The ST-GTF group neither improved nor regressed over the latter 9months except for a small increase in sleep latency. Conclusion: Using a WBMD concomitantly with personalized education, encouragement, and feedback, elicits greater change than using a WBMD alone. Additionally, the improvements achieved from a short duration of personalized coaching are largely maintained with the continued use of a WBMD.

Heartbeat-Evoked Cortical Potential during Sleep and Interoceptive Sensitivity: A Matter of Hypnotizability

Individuals with different hypnotizability display different interoceptive sensitivity/awareness (IS) and accuracy (IA), likely sustained by morphofunctional differences in interoception-related brain regions and, thus, possibly also observable during sleep. We investigated the heartbeat-evoked cortical potential amplitude (HEP) during sleep, its association with IS, and the role of hypnotizability in such association. We performed a retrospective analysis of polysomnographic recordings of 39 healthy volunteers. Participants completed the Multidimensional Assessment of Interoceptive Awareness (MAIA), measuring IS and IA, and underwent hypnotic assessment via the Stanford Hypnotic Susceptibility Scale, form A. The amplitude of the early and late HEP components was computed at EEG frontal and central sites. In both regions, the early HEP component was larger in N3 than in N2 and REM, with no difference between N2 and REM. Greater HEP amplitude at frontal than at central sites was found for the late HEP component. HEP amplitudes were not influenced by the autonomic state assessed by heart rate variability in the frequency and time domains. We report for the first time a positive correlation between the central late HEP component and MAIA dimensions, which became non-significant after removing the effects of hypnotizability. Our findings indicate that hypnotizability sustains the correlation between IS and HEP amplitude during sleep.

Applying Heart Rate Variability to Monitor Health and Performance in Tactical Personnel: A Narrative Review

Human performance optimization of tactical personnel requires accurate, meticulous, and effective monitoring of biological adaptations and systemic recovery. Due to an increased understanding of its importance and the commercial availability of assessment tools, the use of heart rate variability (HRV) to address this need is becoming more common in the tactical community. Measuring HRV is a non-invasive, practical method for objectively assessing a performer's readiness, workload, and recovery status; when combined with additional data sources and practitioner input, it provides an affordable and scalable solution for gaining actionable information to support the facilitation and maintenance of operational performance. This narrative review discusses the non-clinical use of HRV for assessing, monitoring, and interpreting autonomic nervous system resource availability, modulation, effectiveness, and efficiency in tactical populations. Broadly, HRV metrics represent a complex series of interactions resulting from internal and external stimuli; therefore, a general overview of HRV applications in tactical personnel is discussed, including the influence of occupational specific demands, interactions between cognitive and physical domains, and recommendations on implementing HRV for training and recovery insights into critical health and performance outcomes.

Heart rate variability and chronotype - a systematic review

There is a scarcity of evidence on the association between heart rate variability (HRV) and chronotype, i.e., morningness and eveningness. The aim of this systematic review was to examine the association between chronotype, HRV, mood and stress response. We searched PubMed, Web of Science, Scopus, Cinahl, PsycINFO and Google Scholar for peer-reviewed articles published in English between January 2000 and June 2020. A total of 11 articles met the inclusion criteria and were on study population, assessment of HRV and chronotype, main results and study limitations. Seven of the included studies were experimental and four were crossovers. The sample size varied from 9 to 221 participants, and both females and males were included. HRV was assessed using mostly time-domain and frequency-domain parameters; nonlinear parameters were used in only one study. The most used assessments for measuring chronotype were the Horne-Östberg Morningness-Eveningness Questionnaire (MEQ) and the Munich Chronotype Questionnaire (MCTQ). The results showed that chronotype was associated with HRV, but the study designs were situation-specific, focusing, for example, on the effects of shiftwork, stressful situations, exercise, or sleep deprivation on HRV. In addition, some studies showed that evening types (E-type) performed better during evening or nighttime tasks, whereas morning types (M-type) performed better during morning activities. Specifically, E-types showed decreased HRV and HRV recovery in relation to tasks performed during morning or daytime when compared to M-types. As the findings are somewhat contradictory and include some methodological limitations (e.g., small sample sizes, age groups), it is important for future studies to evaluate the association between chronotype and HRV in a longitudinal setting. In addition, further research is needed to determine how chronotype can be optimally and individually utilized to increase the health and well-being of M-type and E-type individuals.

Sleep Indices and Cardiac Autonomic Activity Responses during an International Tournament in a Youth National Soccer Team

This study aimed to describe habitual sleep and nocturnal cardiac autonomic activity (CAA), and their relationship with training/match load in male youth soccer players during an international tournament. Eighteen elite male youth soccer players (aged 14.8 ± 0.3 years; mean ± SD) participated in the study. Sleep indices were measured using wrist actigraphy, and heart rate (HR) monitors were used to measure CAA during night-sleep throughout 5 consecutive days. Training and match loads were characterized using the session-rating of perceived exertion (s-RPE). During the five nights 8 to 17 players slept less than <8 h and only one to two players had a sleep efficiency <75%. Players' sleep duration coefficient of variation (CV) ranged between 4 and 17%. Nocturnal heart rate variability (HRV) indices for the time-domain analyses ranged from 3.8 (95% confidence interval, 3.6; 4.0) to 4.1 ln[ms] (3.9; 4.3) and for the frequency-domain analyses ranged from 5.9 (5.6; 6.5) to 6.6 (6.3; 7.4). Time-domain HRV CV ranged from 3 to 10% and frequency-domain HRV ranged from 2 to 12%. A moderate within-subjects correlation was found between s-RPE and sleep duration [r = -0.41 (-0.62; -0.14); p = 0.003]. The present findings suggest that youth soccer players slept less than the recommended during the international tournament, and sleep duration was negatively associated with training/match load.