Measure by measure: Resting heart rate across the 24-hour cycle

Circadian and Diurnal Regulation of Cerebral Blood Flow

Circadian and diurnal variation in cerebral blood flow directly contributes to the diurnal variation in the risk of stroke, either through factors that trigger stroke or due to impaired compensatory mechanisms. Cerebral blood flow results from the integration of systemic hemodynamics, including heart rate, cardiac output, and blood pressure, with cerebrovascular regulatory mechanisms, including cerebrovascular reactivity, autoregulation, and neurovascular coupling. We review the evidence for the circadian and diurnal variation in each of these mechanisms and their integration, from the detailed evidence for mechanisms underlying the nocturnal nadir and morning surge in blood pressure to identifying limited available evidence for circadian and diurnal variation in cerebrovascular compensatory mechanisms. We, thus, identify key systemic hemodynamic factors related to the diurnal variation in the risk of stroke but particularly identify the need for further research focused on cerebrovascular regulatory mechanisms.

Physiological evidence of stress reduction during a summer Antarctic expedition with a significant influence of previous experience and vigor

Antarctica provides a unique environment for studying human adaptability, characterized by controlled conditions, limited sensory stimulation, and significant challenges in logistics and communication. This longitudinal study investigates the relationship between stress indicators, with a specific focus on mean sleep heart rate, during a COVID-19 quarantine and subsequent 83 days long summer Antarctic expedition at the J. G. Mendel Czech Antarctic Station. Our novel approach includes daily recordings of sleep heart rate and weekly assessments of emotions, stress, and sleep quality. Associations between variables were analyzed using the generalized least squares method, providing unique insights into nuances of adaptation. The results support previous findings by providing empirical evidence on the stress reducing effect of Antarctic summer expedition and highlight the importance of previous experience and positive emotions, with the novel contribution of utilizing physiological data in addition to psychological measures. High-frequency sampling and combination of psychological and physiological data addresses a crucial gap in the research of stress. This study contributes valuable knowledge to the field of psychophysiology and has implications for expedition planners, research organizations, teams in action settings, pandemic prevention protocols, global crises, and long-duration spaceflight missions. Comprehensive insights promote the well-being and success of individuals in extreme conditions.

Wearable Sensors as a Preoperative Assessment Tool: A Review

Surgery is a common first-line treatment for many types of disease, including cancer. Mortality rates after general elective surgery have seen significant decreases whilst postoperative complications remain a frequent occurrence. Preoperative assessment tools are used to support patient risk stratification but do not always provide a precise and accessible assessment. Wearable sensors (WS) provide an accessible alternative that offers continuous monitoring in a non-clinical setting. They have shown consistent uptake across the perioperative period but there has been no review of WS as a preoperative assessment tool. This paper reviews the developments in WS research that have application to the preoperative period. Accelerometers were consistently employed as sensors in research and were frequently combined with photoplethysmography or electrocardiography sensors. Pre-processing methods were discussed and missing data was a common theme; this was dealt with in several ways, commonly by employing an extraction threshold or using imputation techniques. Research rarely processed raw data; commercial devices that employ internal proprietary algorithms with pre-calculated heart rate and step count were most commonly employed limiting further feature extraction. A range of machine learning models were used to predict outcomes including support vector machines, random forests and regression models. No individual model clearly outperformed others. Deep learning proved successful for predicting exercise testing outcomes but only within large sample-size studies. This review outlines the challenges of WS and provides recommendations for future research to develop WS as a viable preoperative assessment tool.

Exposures to Elevated Core Temperatures during Football Training: The Impact on Autonomic Nervous System Recovery and Function

Exercising with elevated core temperatures may negatively affect autonomic nervous system (ANS) function. Additionally, longer training duration under higher core temperatures may augment these negative effects. This study evaluated the relationship between exercise training duration and 24 h ANS recovery and function at ≥37 °C, ≥38 °C and ≥39 °C core temperature thresholds in a sample of male Division I (D1) collegiate American football athletes. Fifty athletes were followed over their 25-week season. Using armband monitors (Warfighter MonitorTM, Tiger Tech Solutions, Inc., Miami, FL, USA), core temperature (°C) and 24 h post-exercise baseline heart rate (HR), HR recovery and heart rate variability (HRV) were measured. For HRV, two time-domain indices were measured: the root mean square of the standard deviation of the NN interval (rMSSD) and the standard deviation of the NN interval (SDNN). Linear regression models were performed to evaluate the associations between exercise training duration and ANS recovery (baseline HR and HRV) and function (HR recovery) at ≥37 °C, ≥38 °C and ≥39 °C core temperature thresholds. On average, the athletes were 21.3 (± 1.4) years old, weighed 103.0 (±20.2) kg and had a body fat percentage of 15.4% (±7.8%, 3.0% to 36.0%). The duration of training sessions was, on average, 161.1 (±40.6) min and they ranged from 90.1 to 339.6 min. Statistically significant associations between training duration and 24 h ANS recovery and function were observed at both the ≥38.0 °C (baseline HR: β = 0.10 ± 0.02, R2 = 0.26, p < 0.0000; HR recovery: β = -0.06 ± 0.02, R2 = 0.21, p = 0.0002; rMSSD: β = -0.11 ± 0.02, R2 = 0.24, p < 0.0000; and SDNN: β = -0.16 ± 0.04, R2 = 0.22, p < 0.0000) and ≥39.0 °C thresholds (β = 0.39 ± 0.05, R2 = 0.62, p < 0.0000; HR recovery: β = -0.26 ± 0.04, R2 = 0.52, p < 0.0000; rMSSD: β = -0.37 ± 0.05, R2 = 0.58, p < 0.0000; and SDNN: β = -0.67 ± 0.09, R2 = 0.59, p < 0.0000). With increasing core temperatures, increases in slope steepness and strengths of the associations were observed, indicating accelerated ANS deterioration. These findings demonstrate that exercise training under elevated core temperatures (≥38 °C) may negatively influence ANS recovery and function 24 h post exercise and progressively worsen.

A Novel Metric "Exercise Cardiac Load" Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes

Current metrics like baseline heart rate (HR) and HR recovery fail in predicting overtraining (OT), a syndrome manifesting from a deteriorating autonomic nervous system (ANS). Preventing OT requires tracking the influence of internal physiological loads induced by exercise training programs on the ANS. Therefore, this study evaluated the predictability of a novel, exercise cardiac load metric on the deterioration of the ANS. Twenty male American football players, with an average age of 21.3 years and body mass indices ranging from 23.7 to 39.2 kg/m2 were included in this study. Subjects participated in 40 strength- and power-focused exercise sessions over 8 weeks and wore armband monitors (Warfighter Monitor, Tiger Tech Solutions) equipped with electrocardiography capabilities. Exercise cardiac load was the product of average training HR and duration. Baseline HR, HR variability (HRV), average HR, and peak HR were also measured. HR recovery was measured on the following day. HRV indices assessed included the standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (rMSSD) Linear regression models assessed the relationships between each cardiac metric and HR recovery, with statistical significance set at α < 0.05. Subjects were predominantly non-Hispanic black (70%) and aged 21.3 (±1.4) years. Adjusted models showed that exercise cardiac load elicited the strongest negative association with HR recovery for previous day (β = -0.18 ± 0.03; p < 0.0000), one-week (β = -0.20 ± 0.03; p < 0.0000) and two-week (β = -0.26 ± 0.03; p < 0.0000) training periods compared to average HR (βetas: -0.09 to -0.02; p < 0.0000) and peak HR (βetas: -0.13 to -0.23; p < 0.0000). Statistically significant relationships were also found for baseline HR (p < 0.0000), SDNN (p < 0.0000) and rMSSD (p < 0.0000). Exercise cardiac load appears to best predict ANS deterioration across one- to two-week training periods, showing a capability for tracking an athlete's physiological tolerance and ANS response. Importantly, this information may increase the effectiveness of exercise training programs, enhance performance, and prevent OT.

Exercise Cardiac Load and Autonomic Nervous System Recovery during In-Season Training: The Impact on Speed Deterioration in American Football Athletes

Fully restoring autonomic nervous system (ANS) function is paramount for peak sports performance. Training programs failing to provide sufficient recovery, especially during the in-season, may negatively affect performance. This study aimed to evaluate the influence of the physiological workload of collegiate football training on ANS recovery and function during the in-season. Football athletes recruited from a D1 college in the southeastern US were prospectively followed during their 13-week "in-season". Athletes wore armband monitors equipped with ECG and inertial movement capabilities that measured exercise cardiac load (ECL; total heartbeats) and maximum running speed during and baseline heart rate (HR), HR variability (HRV) 24 h post-training. These metrics represented physiological load (ECL = HR·Duration), ANS function, and recovery, respectively. Linear regression models evaluated the associations between ECL, baseline HR, HRV, and maximum running speed. Athletes (n = 30) were 20.2 ± 1.5 years, mostly non-Hispanic Black (80.0%). Negative associations were observed between acute and cumulative exposures of ECLs and running speed (β = -0.11 ± 0.00, p < 0.0000 and β = -0.15 ± 0.04, p < 0.0000, respectively). Similarly, negative associations were found between baseline HR and running speed (β = -0.45 ± 0.12, 95% CI: -0.70, -0.19; p = 0.001). HRV metrics were positively associated with running speed: (SDNN: β = 0.32 ± 0.09, p < 0.03 and rMSSD: β = 0.35 ± 0.11, p < 0.02). Our study demonstrated that exposure to high ECLs, both acutely and cumulatively, may negatively influence maximum running speed, which may manifest in a deteriorating ANS. Further research should continue identifying optimal training: recovery ratios during off-, pre-, and in-season phases.

Recovery of the autonomic nervous system following football training among division I collegiate football athletes: The influence of intensity and time

The autonomic nervous system (ANS) is profoundly affected by high intensity exercise. However, evidence is less clear on ANS recovery and function following prolonged bouts of high intensity exercise, especially in non-endurance athletes. Therefore, this study aimed to investigate the relationships between duration and intensity of acute exercise training sessions and ANS recovery and function in Division I football athletes. Fifty, male football athletes were included in this study. Subjects participated in 135 days of exercise training sessions throughout the 25-week season and wore armband monitors (Warfighter Monitor, Tiger Tech Solutions) equipped with electrocardiography capabilities. Intensity was measured via heart rate (HR) during an 'active state', defined as HR ≥ 85 bpm. Further, data-driven intensity thresholds were used and included HR < 140 bpm, HR < 150 bpm, HR < 160 bpm, HR ≥ 140 bpm, HR ≥ 150 bpm and HR ≥ 160 bpm. Baseline HR and HR recovery were measured and represented ANS recovery and function 24h post-exercise. Linear regression models assessed the relationships between time spent at the identified intensity thresholds and ANS recovery and function 24h post-exercise. Statistical significance set at α < 0.05. Athletes participated in 128 training sessions, totaling 2735 data points analyzed. Subjects were predominantly non-Hispanic black (66.0%), aged 21.2 (±1.5) years and average body mass index of 29.2 (4.7) kg⋅(m2)-1. For baseline HR, statistically significant associations between duration and next-day ANS recovery were observed at HR < 140 bpm (β = -0.08 ± 0.02, R2 = 0.31, p < 0.001), HR above 150 and 160 bpm intensity thresholds (β = 0.25 ± 0.02, R2 = 0.69, p < 0.0000 and β = 0.59 ± 0.06, R2 = 0.71, p < 0.0000). Similar associations were observed for HR recovery: HR < 140 bpm (β = 0.15 ± 0.03, R2 = 0.43, p < 0.0000) and HR above 150 and 160 bpm (β = -0.33 ± 0.03, R2 = 0.73, p < 0.0000 and β = -0.80 ± 0.06, R2 = 0.71, p < 0.0000). The strengths of these associations increased with increasing intensity, HR ≥ 150 and 160 bpm (baseline HR: β range = 0.25 vs 0.59, R2: 0.69 vs 0.71 and HR recovery: β range = -0.33 vs -0.80, R2 = 0.73 vs 0.77). Time spent in lower intensity thresholds, elicited weaker associations with ANS recovery and function 24h post-exercise, with statistical significance observed only at HR < 140 bpm (β = -0.08 ± 0.02, R2 = 0.31, p < 0.001). The findings of this study showed that ANS recovery and function following prolonged high intensity exercise remains impaired for more than 24h. Strength and conditioning coaches should consider shorter bouts of strenuous exercise and extending recovery periods within and between exercise training sessions.