Stefan Endler

The longer the better: Sleep-wake patterns during preparation of the World Rowing Junior Championships.

ABSTRACT Recovery is essential for high athletic performance, and therefore especially sleep has been identified as a crucial source for physical and psychological well-being. However, due to early-morning trainings, which are general practice in many sports, athletes are likely to experience sleep restrictions. Therefore, this study investigated the sleep–wake patterns of 55 junior national rowers (17.7 ± 0.6 years) via sleep logs and actigraphy during a four-week training camp. Recovery and stress ratings were obtained every morning with the Short Recovery and Stress Scale on a 7-point Likert-type scale ranging from 0 (does not apply at all) to 6 (fully applies). The first training session was scheduled for 6:30 h every day. With two to four training sessions per day, the training load was considerably increased from athletes’ home training. Objective sleep measures (n = 14) revealed less total sleep time (TST) in the first two weeks (342.9 ± 30.3 and 340.4 ± 32.0 min), while training volume and intensity were higher. In the second half of the camp, less training sessions were implemented, more afternoons were training free and TSTs were longer (357.0 ± 24.6 and 368.7 ± 44.8 min). A single occasion of 1.5-h delayed bedtime and usual early morning training (6:30 h) resulted in reduced ratings of Overall Recovery (OR) (M = 3.3 ± 1.3) and greater Negative Emotional State (NES) (M = 1.3 ± 1.2, p < .05), which returned to baseline on the next day. Following an extended night due to the only training-free day, sleep-offset times were shifted from ~5:30 to ~8:00 h, and each recovery and stress score improved (p < .01). Moreover, subjective ratings of the first six days were summarised as a baseline score to generate reference data as well as to explore the association between sleep and recovery. Intercorrelations of these sleep parameters emphasised the relationship between restful sleep and falling asleep quickly (r = .34, p < .05) as well as few awakenings (r = .35, p < .05). Overall, the findings highlight the impact of sleep on subjective recovery measures in the setting of a training camp. Providing the opportunity of extended sleep (and a day off) seems the most simple and effective strategy to enhance recovery and stress-related ratings.

Sleep monitoring of a six-day microcycle in strength and high-intensity training

Abstract This study examined the effect of microcycles in eccentric strength and high-intensity interval training (HIT) on sleep parameters and subjective ratings. Forty-two well-trained athletes (mean age 23.2 ± 2.4 years) were either assigned to the strength (n = 21; mean age 23.6 ± 2.1 years) or HIT (n = 21; mean age 22.8 ± 2.6 years) protocol. Sleep monitoring was conducted with multi-sensor actigraphy (SenseWear Armband™, Bodymedia, Pittsburg, PA, USA) and sleep log for 14 days. After a five-day baseline phase, participants completed either eccentric accented strength or high-intensity interval training for six days, with two training sessions per day. This training phase was divided into two halves (part 1 and 2) for statistical analyses. A three-day post phase concluded the monitoring. The Recovery-Stress Questionnaire for Athletes was applied at baseline, end of part 2, and at the last post-day. Mood ratings were decreased during training, but returned to baseline values afterwards in both groups. Sleep parameters in the strength group remained constant over the entire process. The HIT group showed trends of unfavourable sleep during the training phase (e.g., objective sleep efficiency at part 2: mean = 83.6 ± 7.8%, F3,60 = 2.57, P = 0.06, = 0.114) and subjective improvements during the post phase for awakenings (F3,60 = 2.96, P = 0.04, = 0.129) and restfulness of sleep (F3,60 = 9.21, P < 0.001, = 0.315). Thus, the HIT protocol seems to increase higher recovery demands than strength training, and sufficient sleep time should be emphasised and monitored.

Comparing Subjective With Objective Sleep Parameters Via Multisensory Actigraphy in German Physical Education Students

This study compared subjective with objective sleep parameters among 72 physical education students. Furthermore, the study determined whether 24-hr recording differs from nighttime recording only. Participants wore the SenseWear Armband™ for three consecutive nights and kept a sleep log. Agreement rates ranged from moderate to low for sleep onset latency (ICC = 0.39 to 0.70) and wake after sleep onset (ICC = 0.22 to 0.59), while time in bed (ICC = 0.93 to 0.95) and total sleep time (ICC = 0.90 to 0.92) revealed strong agreement during this period. Comparing deviations between 24-hr wearing time (n = 24) and night-only application (n = 20) revealed no statistical difference (p > 0.05). As athletic populations have yet to be investigated for these purposes, this study provides useful indicators and practical implications for future studies.

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise—Basics and Options for Wearable Devices

The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.

A biomechanical comparison of countermovement performance after short-term traditional and daily-undulated loaded vertical jump training

ABSTRACT In order to assess lower extremity muscle mechanical properties in athletes, power-load characteristics during multi-joint tasks are frequently examined. This work compared 6 weeks of traditional (TP) and daily-undulated (DUP) periodized loaded countermovement jumping (CMJ). 20 amateur athletes (age: 24.2 ± 2.6 years, height: 175.6 ± 7.1 cm, body mass: 71.5 ± 7.7 kg, 10 males/10 females) exercised three times weekly using maximal CMJs with loads corresponding to 0%, 15% and 30% of body mass. Prior to the training period, subjects were once-only assigned by random to either the TP or DUP training scheme. Pre-to-post training, maximal center of mass (COM) -height, -take-off velocity, -power output and -impulse were compared during CMJ with additional loads corresponding to 0–30% of body mass. ANOVA (time * group) with repeated measures revealed significant (P < 0.05) temporal gains of maximal COM-height (2–11%), -take-off velocity (1–7%), -power (2–8%) and -impulse (3–9%) over most loading conditions for TP and DUP. However, ANOVA indicated no group effects for any outcome. Independent from the periodization model, maximal power output remained statistically unchanged with increased testing loads. For short-term conditioning periods, TP and DUP were equally effective in enhancing biomechanical jumping variables under varying loading conditions.

Performance Estimation using the Fitness-Fatigue Model with Kalman Filter Feedback

Abstract Tracking and predicting the performance of athletes is of great interest, not only in training science but also, increasingly, for serious hobbyists. The increasing availability and use of smart watches and fitness trackers means that abundant data is becoming available, and the interest to optimally use this data for performance tracking and training optimization is great. One competitive model in this domain is the 3-time-constant fitness-fatigue model by Busso based on the model by Banister and colleagues. In the following, we will show that this model can be written equivalently as a linear, time-variant state-space model. With this understanding, it becomes clear that all methods for optimum tracking in statespace models are also directly applicable here. As an example, we show how a Kalman filter can be combined with the fitness-fatigue model in a mathematically consistent fashion. This gives us the opportunity to optimally consider measurements of performance to adapt the fitness and fatigue estimates in a datadriven manner. Results show that this approach is capable of clearly improving performance tracking and prediction over a range of different scenarios.

What is the best fitting function? Evaluation of lactate curves with common methods from the literature

Using the lactate threshold for training prescription is the gold-standard, although there are several open questions. One open question is: What is the best fitting method for the load-lactate data points? This investigation re-analyses over 3500 lactate diagnostic datasets in swimming. Our evaluation software examines six different fitting methods with two different minimization criteria (RMSE and SE). Optimization of parameters of the functions is put in excecution with gradient descent. From a mathematical point of view, the double phase model, which consists of two linear regression lines, shows the least errors (RMSE min 0.254 ± 0.172; SE min 0.311 ± 0.210). However, this method cannot be used for every further determination of lactate thresholds. Some threshold determination models need a single curve. In these cases, the exponential function shows the least errors (RMSE min 0.846 ± 0.488; SE min 1.196 ± 0.689). This confirms the default fitting method used in practice.

Security of invertible media authentication schemes revisited

Dittmann, Katzenbeisser, Schallhart and Veith (SEC 2005) introduced the notion of invertible media authentication schemes, embedding authentication data in media objects via invertible watermarks. These invertible watermarks allow to recover the original media object (given a secret encryption key), as required for example in some medical applications where the distortion must be removable. Here we revisit the approach of Dittmann et al. from a cryptographic viewpoint, clarifying some important aspects of their security definitions. Namely, we first discuss that their notion of unforgeability may not suffice in all settings, and we therefore propose a strictly stronger notion. We then show that the basic scheme suggested by Dittmann et al. achieves our notion if instantiated with the right cryptographic primitives. Our proof also repairs a flaw in the original scheme, pointed out by Hopper, Molnar and Wagner (TCC 2007). We finally address the issue of secrecy of media authentication schemes, basically preventing unauthorized recovering of the original media object without the encryption key. We give a rigorous security statement (that is, the best security guarantee we can achieve) and prove again that the scheme by Dittmann et al. meets this security level if the right cryptographic building blocks are deployed. Together our notions of unforgeability and of secrecy therefore give very strong security guarantees for such media authentication schemes.