The effects of relaxation techniques following acute, high intensity football training on parasympathetic reactivation.

Background: Evidence shows relaxation techniques reactivate the parasympathetic nervous system (PNS) following physiological stressors such as exercise. As such, these techniques may be useful following exercise training of high intensity sports, like collegiate football. Purpose: To evaluate the impact of mindfulness and rest activities on PNS reactivation following training sessions, in a sample of Division-I collegiate, male football athletes. Methods: This study employed a cross-sectional, pre-post experimental design among 38 football athletes. Following three training sessions, each separated by one week, athletes were exposed to three groups: mindfulness, rest, and no-intervention. Athletes in the mindfulness group laid supine in a darkened room, while performing 15 min of guided breathing and body scans. The rest group remained seated in a lighted room, performing 15 min of restful activities (e.g., talking). The no-intervention group was instructed to perform usual post-training activities (e.g., showering). Heart rate (HR), respiration rate (RR) and two HR variability (HRV) indices were measured via an armband monitor (Warfighter Monitor, Tiger Tech Solutions, Inc, Miami, FL) equipped with electrocardiographic and photoplethysmography capabilities. HRV indices included standard deviation of the N-N intervals (SDNN) and root mean square of successive RR interval differences (rMSSD). Within and between-group differences were determined via analysis of variance (ANOVA) and corrected for multiple comparisons familywise error. Results: Statistically significant reductions in HR and RR were observed across all groups: -81.6, -66.4, -40.9 bpm and -31.7, -26.9, and -19.0 breaths⋅min-1, respectively. The mindfulness and rest groups exhibited a larger within-group reduction in HR and RR compared to the no-intervention group, p < 0.0000. Additionally, the mindfulness group showed a larger reduction in HR and RR compared to the rest group, p < 0.05. Post-intervention HR and RRs were significantly lower in the mindfulness group relative to the no-intervention group (77.0 vs. 120.1 bpm, respectively). Similar results were observed for RR (15.0 vs. 23.6 breaths⋅min-1, respectively) and HRV indices (SDNN: 46.9 vs. 33.1 ms and rMSSD: 17.9 vs. 13.8 ms, respectively) Athletes in the rest group showed significantly lower post-intervention HR (-30.2 bpm, 89.9 vs. 120.1 bpm, respectively), RR (-4.3 breaths⋅min-1, 19.3 vs. 23.6 breaths⋅min-1, respectively) and significantly higher HRV (SDNN: 42.9 vs. 33.1 ms and rMSSD: 16.7 vs. 13.8 ms, respectively) compared to their no-intervention counterparts. Conclusions: Our findings suggest that athletes engaging in either 15-minute guided mindfulness or rest activities (e.g., sitting) post training, may facilitate PNS reactivation. Implementing these strategies may accelerate recovery, improving performance. Longitudinal, randomized controlled trials among diverse sports are encouraged.

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 (ß = -0.18 ± 0.03; p < 0.0000), one-week (ß = -0.20 ± 0.03; p < 0.0000) and two-week (ß = -0.26 ± 0.03; p < 0.0000) training periods compared to average HR (ßetas: -0.09 to -0.02; p < 0.0000) and peak HR (ßetas: -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 (ß = -0.11 ± 0.00, p < 0.0000 and ß = -0.15 ± 0.04, p < 0.0000, respectively). Similarly, negative associations were found between baseline HR and running speed (ß = -0.45 ± 0.12, 95% CI: -0.70, -0.19; p = 0.001). HRV metrics were positively associated with running speed: (SDNN: ß = 0.32 ± 0.09, p < 0.03 and rMSSD: ß = 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 (ß = -0.08 ± 0.02, R2 = 0.31, p < 0.001), HR above 150 and 160 bpm intensity thresholds (ß = 0.25 ± 0.02, R2 = 0.69, p < 0.0000 and ß = 0.59 ± 0.06, R2 = 0.71, p < 0.0000). Similar associations were observed for HR recovery: HR < 140 bpm (ß = 0.15 ± 0.03, R2 = 0.43, p < 0.0000) and HR above 150 and 160 bpm (ß = -0.33 ± 0.03, R2 = 0.73, p < 0.0000 and ß = -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: ß range = 0.25 vs 0.59, R2: 0.69 vs 0.71 and HR recovery: ß 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 (ß = -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.

Internal or External Training Load Metrics: Which Is Best for Tracking Autonomic Nervous System Recovery and Function in Collegiate American Football?

Sport coaches increasingly rely on external load metrics for designing effective training programs. However, their accuracy in estimating internal load is inconsistent, and their ability to predict autonomic nervous system (ANS) deterioration is unknown. This study aimed to evaluate the relationships between internal and external training load metrics and ANS recovery and function in college football players. Football athletes were recruited from a D1 college in the southeastern US and prospectively followed for 27 weeks. Internal load was estimated via exercise cardiac load (ECL; average training heartrate (HR) × session duration) and measured with an armband monitor equipped with electrocardiographic capabilities (Warfighter MonitorTM (WFM), Tiger Tech Solutions, Miami, FL, USA). External load was estimated via the summation and rate of acceleration and decelerations as measured by a triaxial accelerometer using the WFM and an accelerometer-based (ACCEL) device (Catapult Player Load, Catapult Sports, Melbourne, Australia) worn on the mid-upper back. Baseline HR, HR variability (HRV) and HR recovery served as the indicators for ANS recovery and function, respectively. For HRV, two, time-domain metrics were measured: the standard deviation of the NN interval (SDNN) and root mean square of the standard deviation of the NN interval (rMSSD). Linear regression models evaluated the associations between ECL, ACCEL, and the indicators of ANS recovery and function acutely (24 h) and cumulatively (one- and two-week). Athletes (n = 71) were male and, on average, 21.3 ± 1.4 years of age. Acute ECL elicited stronger associations for 24 h baseline HR (R2 0.19 vs. 0.03), HR recovery (R2 0.38 vs. 0.07), SDNN (R2 0.19 vs. 0.02) and rMSSD (R2 0.19 vs. 0.02) compared to ACCEL. Similar results were found for one-week: 24 h baseline HR (R2 0.48 vs. 0.05), HR recovery (R2 0.55 vs. 0.05), SDNN (R2 0.47 vs. 0.05) and rMSSD (R2 0.47 vs. 0.05) and two-week cumulative exposures: 24 h baseline HR (R2 0.52 vs. 0.003), HR recovery (R2 0.57 vs. 0.05), SDNN (R2 0.52 vs. 0.003) and rMSSD (R2 0.52 vs. 0.002). Lastly, the ACCEL devices weakly correlated with ECL (rho = 0.47 and 0.43, p < 0.005). Our findings demonstrate that ACCEL poorly predicted ANS deterioration and underestimated internal training load. ACCEL devices may "miss" the finite window for preventing ANS deterioration by potentially misestimating training loads acutely and cumulatively.