The way in which the Root Mean Square of the Successive Differences between adjacent RR intervals (RMSSD) recovers immediately after exercise could be a good indicator of internal training load (ITL). The aim of this study is to design a recovery index based on RMSSD. Forteen healthy men took part in this study. The experiment lasted 2 weeks, with 4 separate (48 -72 h) sessions. First session was an incremental treadmill test to determine ventilatory thresholds (VT1 and VT2) and maximal aerobic speed (MAS). Each subject ran at VT1 speed (second day), VT2 speed (third day) and a time-to-exhaustion test at MAS (fourth day). The duration of VT1 and VT2 loads was selected in such a way that the product intensity-duration (training load) was the same. HRV was measured from 10' prior to test (Rest) to 30' after completed (Recovery). Recovery slopes were calculated from RMSSD values at 10 and 30 minutes. Borg scale was recorded at the end of every test and the Training Impulse (TRIMP) values were calculated using Banister equations. The RMSSD values dropped substantially regardless of the intensity and the duration of exercise (average 4 ms). The RMSSD recovery was linear during the 30 min and different depending on the intensity of exercise. To propose a recovery index, we calculated the slope of RMSDD over the 30 minutes (slope-30) and also the first 10 minutes (slope-10). Given that the slopes presented an exponential behavior in relation with effort intensity, three curves were obtained (average values, plus SD and minus SD) defining a nomogram. For practical application, we propose: 1) to measure RMSSD the last 5 minutes of exercise and any period of 5 minutes during the first 30 minutes recovery; 2) to calculate the slope of RMSSD between exercise and recovery; 3) to compare with the nomogram.

We aimed to analyse the complexity and fractal nature of heartbeat during constant exercise, at three different intensities, and recovery.Fourteen healthy men underwent 4 separate sessions. The first session was an incremental treadmill test to determine ventilatory thresholds (VT1 and VT2) and maximal aerobic speed (MAS). Each subject ran at VT1 and VT2 speeds and MAS (second, third and fourth day). The duration of VT1 and VT2 loads were selected in such a way that the product intensity-duration (training load) was the same. Sample Entropy (SampEn) and slope of Detrended Fluctuation Analysis (DFA α1) were measured during the whole session.DFA α1 declines with exercise, being less in the VT1 trial than in the other two.SampEn shows no significant change during exercise. The three tests induce the same decline in SampEn, but at the highest intensity (MAS) tends to decline during the exercise itself, whereas at lower intensities (VT1, VT2) the decline is delayed (10 min of recovery). Subsequently, SampEn at VT1 gradually recovers, whereas at VT2 and MAS it remains stable during recovery.In conclusion, exercise produces a loss of heartbeat complexity, but not fractal nature, during recovery and it depends on intensity.

The aim of this study was to validate the measurements of the beat intervals taken at rest by the Omegawave® device by comparing them to an ambulatory electrocardiogram system. For this purpose, the electrocardiogram was digitally processed, time-aligned, and scrutinized for its suitable use as gold-standard. Rest measurements were made for 10 minutes on 5 different days to 10 men and 3 women (24.8±5.05 years; 71.82±11.02 kg; 174.35±9.13 cm). RR intervals were simultaneously recorded using the Omegawave device and a Holter electrocardiogram. The processing of Holter electrocardiogram signals included the detrending of baseline noise and a high-pass filtering for emphasizing the QRS complexes and attenuating the T waves. After obtaining the RR intervals from the electrocardiogram, those from the Omegawave device were automatically aligned to them with cross-correlation digital processing techniques and compared to check whether both measurements could be considered superimposable. A Bland-Altman analysis was applied to the 5 measurements made for all subjects. The Omegawave device exhibited very strong agreement with a quality-controlled Holter electrocardiogram. Deviations not exceeding 25 ms could be expected in 95% of the cases, which is within manageable ranges both for clinical practice and for sports.

El objetivo de este estudio fue describir una metodología de seguimiento en una atleta que combina el Ultra Trail Running (UTR) y el Ironman durante 16 semanas, mediante variabilidad de la frecuencia cardiaca (VFC). La carga de entrenamiento (CE) diaria se programó y se cuantificó el sumatorio semanal. Se registraron los intervalos RR (ms) en reposo cada mañana durante 5 minutos y a partir de ellos se midió la RMSSD (raíz cuadrada de la media de las diferencias de la suma de los cuadrados entre intervalos RR adyacentes) como medida de la actividad parasimpática y el índice de estrés (SS) como actividad simpática. Los registros diarios de VFC matutinos parecen ser una forma útil para monitorizar el estado de equilibrio simpático-parasimpático en deportistas antes de abordar las sesiones de entrenamiento. Esta monitorización serviría para detectar precozmente estados de fatiga y para poder monitorizar la planificación de las cargas.

The control of training load has become a very interesting field for investigation in sports, but few tools are used to assess internal training load (ITL). The aim of this study is to use a post-exercise analysis methodology in different athletes and situations to establish its utility and reliability as a measure of ITL. In a retrospective review, we analysed 112 measurements of 74 subjects (38 men and 36 women) grouped in: University students (UNI); national team (FUTSAL 1); university team (FUTSAL 2); athletes (ATL); badminton players (BADM). Measures of Heart Rate Variability (HRV) were made with a Polar V800 with a thoracic band H10, during 5 minutes in a seated position after exercise. We calculated the Root Mean Square of the successive differences between adjacent RR intervals (RMSSD) and its slope from exercise to recovery. Measurements from UNI, FUTSAL-2, ATL-M and ATL-F were grouped into three categories of intensity (60%, 75% and 100%). RMSSD-Slope values were lower as intensity increased but different for every subject. In the BADM and FUTSAL-1 groups, RMSSD-Slope was progressively lower after consecutive matches for every player. The RMSSD-Slope seems to be a very accurate method to assess ITL.