The aim of this study was to compare heart rate variability -guided (HRVG) and predetermined (PD) block periodization of high intensity aerobic training (HIT). Endurance performance, neuromuscular performance, heart rate variability (HRV) and serum hormone concentrations were measured before, in the middle and after the 8-week training period in 24 endurance trained males. Both groups improved significantly maximal treadmill velocity (Vmax) (p<0.001) and 3000 m running performance (HRVG; p<0.001 and PD; p=0.001). The relative changes in Vmax and countermovement jump were significantly greater in HRVG (p<0.05). Nocturnal heart rate decreased in both groups (p<0.01), but HRV (RMSSD, LF and TP) increased significantly only in HRVG (p<0.05). The significant increase in serum testosterone concentration was observed from mid to post in HRVG (p<0.05). Significant correlations were found between individual Vmax changes and absolute serum testosterone levels. Individual baseline level of HF correlated significantly with Vmax changes in PD. Block periodization of HIT seems to be an effective way to improve endurance and running performance in already endurance trained males. Based on training induced increases in endurance and neuromuscular performance combined with significant changes in HRV and serum testosterone levels observed in HRVG, individually HRV -guided block training may be more optimal compared to predetermined training.

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11344 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (mean bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (mean bias 0.20 ms, p < 0.001) and nocturnal recordings (mean bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

Purpose: To assess the reliability of nocturnal heart rate (HR) and HR variability (HRV) and to analyze the sensitivity of these markers to maximal endurance exercise. Methods: Recreational runners recorded nocturnal HR and HRV on nights after 2 identical low-intensity training sessions (n = 15) and on nights before and after a 3000-m running test (n = 23). Average HR, the natural logarithm of the root mean square of successive differences (LnRMSSD), and the natural logarithm of the high-frequency power (LnHF) were analyzed from a full night (FULL), a 4-hour (4H) segment starting 30 minutes after going to sleep, and morning value (MOR) based on the endpoint of the linear fit through all 5-minute averages during the night. Differences between the nights were analyzed with a general linear model, and intraclass correlation coefficient (ICC) was used for internight reliability assessments. Results: All indices were similar between the nights followed by low-intensity training sessions. A very high ICC (P < .001) was observed in all analysis segments with a range of .97 to .98 for HR, .92 to .97 for LnRMSSD, and .91 to .96 for LnHF. HR increased (P < .001), whereas LnRMSSD (P < .01) and LnHF (P < .05) decreased after the 3000-m test compared with previous night only in 4H and FULL. Increments in HR (P < .01) and decrements in LnRMSSD (P < .05) were greater in 4H compared with FULL and MOR. Conclusions: Nocturnal HR and HRV indices are highly reliable. Demanding maximal exercise increases HR and decreases HRV most systematically in 4H and FULL segments.

Purpose: Long-term development of endurance performance requires a proper balance between strain and recovery. Because responses and adaptations to training are highly individual, this study examined whether individually adjusted endurance training based on recovery and training status would lead to greater adaptations compared with a predefined program. Methods: Recreational runners were divided into predefined (PD; n = 14) or individualized (IND; n = 16) training groups. In IND, the training load was decreased, maintained, or increased twice a week based on nocturnal heart rate variability, perceived recovery, and heart rate–running speed index. Both groups performed 3-wk preparatory, 6-wk volume, and 6-wk interval periods. Incremental treadmill tests and 10-km running tests were performed before the preparatory period (T ₀) and after the preparatory (T ₁), volume (T ₂), and interval (T ₃) periods. The magnitude of training adaptations was defined based on the coefficient of variation between T ₀ and T ₁ tests (high >2×, low <0.5×). Results: Both groups improved (P < 0.01) their maximal treadmill speed and 10-km time from T ₁ to T ₃. The change in the 10-km time was greater in IND compared with PD (−6.2% ± 2.8% vs −2.9% ± 2.4%, P = 0.002). In addition, IND had more high responders (50% vs 29%) and fewer low responders (0% vs 21%) compared with PD in the change of maximal treadmill speed and 10-km performance (81% vs 23% and 13% vs 23%), respectively. Conclusions: PD and IND induced positive training adaptations, but the individualized training seemed more beneficial in endurance performance. Moreover, IND increased the likelihood of high response and decreased the occurrence of low response to endurance training.

The purpose of this study was firstly to examine the sensitivity of heart rate (HR)‐based and subjective monitoring markers to intensified endurance training; and secondly, to investigate the validity of these markers to distinguish individuals in different fatigue states. A total of 24 recreational runners performed a 3‐week baseline period, a 2‐week overload period, and a 1‐week recovery period. Performance was assessed before and after each period with a 3000m running test. Recovery was monitored with daily orthostatic tests, nocturnal HR recordings, questionnaires, and exercise data. The participants were divided into subgroups (overreached/OR, n = 8; responders/RESP, n = 12) based on the changes in performance and subjective recovery. The responses to the second week of the overload period were compared between the subgroups. RESP improved their baseline 3000 m time (p < 0.001) after the overload period (−2.5 ± 1.0%), and the change differed (p < 0.001) from OR (0.6 ± 1.2%). The changes in nocturnal HR (OR 3.2 ± 3.1%; RESP −2.8 ± 3.7%, p = 0.002) and HR variability (OR −0.7 ± 1.8%; RESP 2.1 ± 1.6%, p = 0.011) differed between the subgroups. In addition, the decrease in subjective readiness to train (p = 0.009) and increase in soreness of the legs (p = 0.04) were greater in OR compared to RESP. Nocturnal HR, readiness to train, and exercise‐derived HR‐running power index had ≥85% positive and negative predictive values in the discrimination between OR and RESP individuals. In conclusion, exercise tolerance can vary substantially in recreational runners. The results supported the usefulness of nocturnal HR and subjective recovery assessments in recognizing fatigue states.

Purpose: Recent studies have suggested that the capability to resist deterioration of physiological characteristics could be an independent factor contributing to endurance performance. This study aimed at investigating whether prolonged low-intensity exercise induces shifts in the lactate threshold, and whether fatigue-induced changes differ between the sexes. Methods: A total of 31 (15 females) recreational runners performed an incremental treadmill test and a 90-min low-intensity exercise (LIT90) on two separate occasions. The LIT90 was performed at 90% of the first lactate threshold speed (LT1v), derived from the incremental treadmill test. The LT1v was determined from a 5-stage (3 min) submaximal threshold test (SubmaxLT), performed before and after LIT90. The SubmaxLTs were followed by a 10/5 reactivity jump test. Respiratory gases, heart rate (HR), and HR-derived detrended fluctuation analysis alpha 1 (DFA-a1) were assessed every 15 min during the LIT90. Results: A significant decrease (p < 0.01) was observed in the LT1v in females (− 5.8 ± 4.4%) and in males (− 5.3 ± 6.4%). The HR increased (p < 0.001) similarly in females (5.9 ± 3.1%) and in males (5.5 ± 3.6%) during the LIT90, while energy expenditure increased (3.1 ± 4.5%, p = 0.013) in females but remained unchanged in males (0.9 ± 3.1%). Change in DFA-a1 during the LIT90 was the only marker that correlated significantly with the relative change of LT1v (r = 0.463, p = 0.013). Conclusion: LIT90 induced significant decreases in the LT1v, and the changes were comparable between sexes. DFA-a1 could be a potential intra-session marker of durability.