Validity, Reliability, and Sensitivity to Exercise-Induced Fatigue of a Customer-Friendly Device for the Measurement of the Brain's Direct Current Potential

Modulation of Heart Rate Variability and Brain Excitability through Acute Whole-Body Vibration: The Role of Frequency

This cross-over study aimed to explore effects of acute whole-body vibration (WBV) at frequencies of 5-35 Hz on heart rate variability and brain excitability. Thirteen healthy physically active college students randomly completed eight interventions under the following conditions: static upright standing without vibration (CON), static squat exercise (knee flexion 150°) on the vibration platform (SSE), and static squat exercise (knee flexion 150°) combined with WBV at vibration frequency of 5, 9, 13, 20, 25, and 35 Hz. Five bouts × 30 s with a 30-s rest interval were performed for all interventions. The brain's direct current potentials (DCPs), frequency domain variables (FDV) including normalized low frequency power (nLF), normalized high frequency power (nHF) and the ratio of LF to HF (LF/HF), along with the mean heart rate (MHR) were collected and calculated before and after the WBV intervention. Results suggested that WBV frequency at 5 Hz had a substantial effect on decreasing DCPs [-2.13 μV, t(84) = -3.82, p < 0.05, g = -1.03, large] and nLF [-13%, t(84) = -2.31, p = 0.04, g = -0.62, medium]. By contrast, 20-35 Hz of acute WBV intervention considerably improved DCPs [7.58 μV, t(84) = 4.31, p < 0.05, g = 1.16, large], nLF [17%, t(84) = 2.92, p < 0.05, g = 0.79, large] and the LF/HF [0.51, t(84) = 2.86, p < 0.05, g = 0.77, large]. A strong (r = 0.7, p < 0.01) correlation between DCPs and nLF was found at 5 Hz. In summary, acute WBV at 20-35 Hz principally activated the sympathetic nervous system and increased brain excitability, while 5-Hz WBV activated the parasympathetic nervous system and reduced brain excitability. The frequency spectrum of WBV might be manipulated according to the intervention target on heart rate variability and brain excitability.

Evaluating the relationship between neurological function, neuromuscular fatigue, and subjective performance measures in professional rugby union players

Managing the health and wellbeing of full-time professional athletes is a multifaceted task. In elite high-performance environments, medical staff and strength training coaches attempt to identify improved methods to monitor player health. Monitoring player health could indicate potential injury risk and assist in adjustments to training and workload management. Measuring fatigue is a notable component of monitoring player readiness before and after training sessions, and after competitive fixtures. In the present study, a novel method of gathering non-invasive player data was investigated by utilizing the Omegawave (OW) to monitor direct current (DC) potential brainwave activity. This method allowed for non-invasive data gathering to assess recovery, player readiness and indicators of workload that may affect optimal performance. DC potential is based on recording low electrical frequencies (&gt;0.5 Hz) that is derived from (1) Stabilization point of DC potential (mV), (2) Stabilization time (1.0–7.0) and (3) Curve shape (1.0–7.0). These measures evaluate the athlete's internal stress, readiness to perform, and neurological function through DC potential brain wave activity and heart rate variability (HRV) assessments. The primary aim of this case series was to compare the efficacy of objective DC potential brainwave activity measurements (neurological function) with neuromuscular fatigue data using reactive strength index modified (RSImod) and profile of mood states (POMS) questionnaires to assess a player's state of readiness to train. The participants in this study were eleven male senior professional rugby union players with a mean stature (±SD) of 185.2 ± 8.6 cm, mass of 101.1 ± 12.9 kg, and age of 27.1 ± 2.1 years. All players were tested 3 days per week over a 6-week mid-season period. Results from this case study suggest that DC potentials could be used as an objective measure to indicate player readiness and managing individual player workload. The final analyses identified a weak negative correlation (r = −0.17) between the RSImod data and the DC potential data was observed. DC potential brainwave activity data could be used in conjunction with subjective measures such as POMS, RSImod and reported injury status to adjust player daily activity.

Effects of Resistance Training on Skin Temperature and Its Relationship with Central Nervous System (CNS) Activation

The aim of this work was to relate the activation of the sympathetic and parasympathetic nervous systems with the skin temperature (Tsk) of the lower limbs after a resistance training exercise. Under controlled conditions, the average Tsk in the areas of the anterior and posterior thighs, knees and legs was obtained with a thermal imager and the parasympathetic and sympathetic activation was registered with an Omegawave^® device on 20 healthy and trained male volunteers (25.39 ± 8.21 years) before exercise, immediately after standard resistance training (3 exercises (2 quadriceps + 1 hamstrings) × 4 sets × 10 repetitions (70% 1RM), 90-sec recovery) and after 20 min of recovery. The results showed a significant effect of exercise and recovery on Tsk in all regions of interest (ROIs) considered (p < 0.05) and strong inverse relationships between sympathetic and parasympathetic activation values. Significant results were found for the total variation of Tsk (p < 0.05) with highly positive values for subjects with lower sympathetic activation and almost null or even negative values for those with higher sympathetic activation. Sympathetic activity was a significant predictor of total Tsk variation in the anterior thigh, posterior thigh and anterior knee but not in the posterior knee, anterior leg, and posterior leg. Baseline Tsk was a significant predictor of total Tsk variation the all ROIs except in the posterior knee. Tsk measured by thermography could be used to estimate the level of participation of muscle areas in exercise and registering the level of sympathetic activation before exercise could be interesting in predicting the athlete’s physiological response to strength training.

Training Load, Heart Rate Variability, Direct Current Potential and Elite Long Jump Performance Prior and during the 2016 Olympic Games

The primary objective of this investigation was to investigate the relationships between training load (TL), heart rate variability (HRV) and direct current potential (DC) with elite long jump performance prior to and during the 2016 Olympics Games. Sessional ratings of perceived exertion (sRPE), training duration, HRV and DC were collected from four elite athletes (26.4 ± 1.4 years, height 1.83 ± 0.05 m, weight 68.9 ± 5.0 kg) for a 16-week period in qualification for and competition at the 2016 Olympic Games. Acute and chronic TL, training stress balance and differential load were calculated with three different smoothing methods. These TL measures along with HRV and DC were examined for their relationship to intra-athlete performance using repeated measure correlations and linear mixed models. Successful compared to unsuccessful intra-athlete performances were characterised by a higher chronic TL (p < 0.01, f² = 0.31) but only when TL was exponentially smoothed. There were also negative correlations between HRV and performance (r = -0.55, p < 0.01) and HRV was significantly lower for more successful performances (p < 0.01, f² = 0.19). Exponentially smoothed chronic TL was significantly higher and HRV was significantly lower for successful intra-athlete performances prior and during the 2016 Olympics Games in an elite group of long jump athletes. Monitoring sRPE and HRV measures and manipulating TL prior to competition seems worthwhile for elite long jump athletes.

Impact of Weekly Physical Activity on Stress Response: An Experimental Study

The aim of this research is focused on analyzing the alteration of the psychophysiological and cognitive response to an objective computerized stress test (Determination Test - DT-, Vienna test System^®), when the behavioral response is controlled. The sample used was sports science students (N = 22), with a mean age of 22.82 (M_age = 22.82; SD_years = 3.67; M_{PhysicalActivity hours/Week} = 7.77; SD_hours/_week = 3.32) A quasi-experimental design was used in which the response of each participant to the DT test was evaluated. The variable “number of hours of physical activity per week” and the variable “level of behavioral response to stress” were controlled. Before and after this test, the following parameters were measured: activation and central fatigue (Critical Flicker Fusion Threshold (CFF Critical flicker fusion ascending and Critical flicker fusion descending; DC potential), and perceived exertion (Central Rating of Perceived Exertion and Peripheral Rating of Perceived Exertion). Significant differences were found in all of the measures indicated. The usefulness of this protocol and the measures used to analyze the stress response capacity of the study subjects are discussed.

Heart Rate Variability and Direct Current Measurement Characteristics in Professional Mixed Martial Arts Athletes

This study’s purpose was to examine heart rate variability (HRV) and direct current potential (DC) measures’ sensitivity and correlations between changes in the acute recovery and stress scale (ARSS) and the previous day’s training load. Training load, HRV, DC and ARSS data were collected from fourteen professional mixed martial arts athletes (32.6 ± 5.3 years, 174.8 ± 8.8 cm, 79.2 ± 17.5 kg) the following morning after hard, easy and rest days. Sensitivity was expressed as a signal-to-noise ratio (SNR, inter-day typical error (TE) or coefficient of variation (%CV) divided by intra-day TE or %CV). Correlations between HRV, DC and ARSS with training load were also examined. The SNRs for the various HRV and DC measures were acceptable to good (1.02–2.85). There was a 23.1% CV average increase between measures taken between different locations versus the same location. Training load changes were not correlated with HRV/DC but were correlated with ARSS stress variables. Practitioners should be aware of HRV/DC variability; however the daily training signal was greater than the test-retest error in this investigation. Upon awakening, HRV/DC measures appear superior for standardization and planning. HRV and DC measures were less sensitive to the previous day’s training load than ARSS measures.