Validation of a non-linear index of heart rate variability to determine aerobic and anaerobic thresholds during incremental cycling exercise in women.

Studies highlight the usage of non-linear time series analysis of heart rate variability (HRV) using the short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) during exercise to determine aerobic and anaerobic thresholds. The present study aims to further verify this approach in women. Gas exchange and HRV data were collected from 26 female participants with different activity levels. Oxygen uptake (VO2) and heart rate (HR) at first (VT1) and second ventilatory thresholds (VT2) were compared with DFA-alpha1-based thresholds 0.75 (HRVT1) and 0.50 (HRVT2). Results: VO2 at VT1 and VT2 were 25.2 ml/kg/min (± 2.8) and 31.5 ml/kg/min (± 3.6) compared with 26.5 ml/kg/min (± 4.0) and 31.9 ml/kg/min (± 4.5) for HRVT1 and HRVT2, respectively (ICC3,1 = 0.77, 0.84; r = 0.81, 0.86, p < 0.001). The mean HR at VT1 was 147 bpm (± 15.6) and 167 bpm (± 12.7) for VT2, compared with 152 bpm (± 15.5) and 166 bpm (± 13.2) for HRVT1 and HRVT2, respectively (ICC3,1 = 0.87, 0.90; r = 0.87, 0.90, p < 0.001). Bland-Altman analysis for VT1 vs. HRVT1 showed a mean difference of - 1.3 ml/kg/min (± 2.4; LoA: 3.3, - 6.0 ml/kg/min) for VO2 and of - 4.7 bpm (± 7.8; LoA: 10.6, - 20.0 bpm) for HR. VT2 vs. HRVT2 showed a mean difference of - 0.4 ml/kg/min (± 2.3; LoA: 4.1, - 4.9 ml/kg/min) for VO2 and 0.5 bpm (± 5.7; LoA: 11.8, - 10.8 bpm) for HR. DFA-alpha1-based thresholds showed good agreement with traditionally used thresholds and could be used as an alternative approach for marking organismic transition zones for intensity distribution in women.

Correlation properties of heart rate variability to assess the first ventilatory threshold and fatigue in runners.

PURPOSE: The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA-a1) of heart rate variability (HRV) has shown potential to delineate the first ventilatory threshold (VT1). The aims of this study were to investigate the accuracy of this method for VT1 determination in runners using a consumer grade chest belt and to explore the effects of acute fatigue. METHODS: We compared oxygen uptake (V̇O2) and heart rate (HR) at gas exchange VT1 to V̇O2 and HR at a DFA-a1 value of 0.75. Gas exchange and HRV data were obtained from 14 individuals during a treadmill run involving two incremental ramps. Agreement was assessed using Bland-Altman analysis and linear regression. RESULTS: Bland-Altman analysis between gas exchange and HRV V̇O2 and HR at VT1 during the first ramp showed a mean (95% limits of agreement) bias of -0.5 (-6.8 to 5.8) ml∙kg-1∙min-1, and -0.9 (-12.2 to 10.5) beats∙min-1, with R2 of 0.83 and 0.56, respectively. During the second ramp, the differences were -7.3 (-18.1 to 3.5) ml∙kg-1∙min-1 and -12.3 (-30.4 to 5.9) beats∙min-1, with R2 of 0.62 and 0.43, respectively. CONCLUSION: A chest-belt derived DFA-a1 of 0.75 is closely related to gas exchange VT1, with the variability in accuracy at an individual level being similar to gas exchange methods. This suggests this to be a useful method for exercise intensity demarcation. The altered relationship during the second ramp indicates that DFA-a1 is only able to accurately demarcate exercise intensity thresholds in a non-fatigued state, but also opens opportunities for fatigue-based training prescription.

The first ventilatory threshold determined with a nonlinear method (DFA-a1) to analyse heart rate variability derived from a chest-belt shows close agreement to the gas exchange first ventilatory threshold, with the variability in accuracy at an individual level being similar to gas exchange methods. This suggests this to be a useful method for exercise intensity demarcation.The altered relationship during fatigue indicates that DFA-a1 is only able to accurately demarcate exercise intensity thresholds in a non-fatigued state, but this also opens opportunities for fatigue-based training prescription.

Video analysis of Achilles tendon ruptures in professional male football (soccer) reveals underlying injury patterns and provides strategies for injury prevention.

PURPOSE: In professional football (soccer), Achilles tendon ruptures are severe injuries. Video analysis promotes a better understanding of the underlying situational and biomechanical patterns, and provides a roadmap for future research to improve the management and prevention of Achilles tendon ruptures. The purpose of this study was to identify injury patterns contributing to acute Achilles tendon ruptures in professional male football players. METHODS: Professional male football players with an acute Achilles tendon rupture were identified using an online database. For every in-competition injury, the corresponding football match was detected. Video footage of the injury was accessed using Wyscout.com or publicly available video databases. Situational patterns and injury biomechanics of the injury frame were independently analysed by two reviewers using a standardised checklist and a motion analysis software. Finally, consensus was reached to describe the main injury patterns of Achilles tendon ruptures in professional male football players. RESULTS: The search identified video footage of 80 Achilles tendon ruptures in 78 players. Most injuries (94%) occurred through indirect or non-contact mechanisms. The kinematic analysis revealed characteristic joint positions at the time of injury consisting of hip extension, knee extension, ankle dorsiflexion, foot abduction, and foot pronation in most cases. The underlying direction of movement was from flexion to extension (knee) and from plantarflexion to dorsiflexion (ankle). Player actions identified as main injury patterns were stepping back (26%), landing (20%), running/sprinting (18%), jumping (13%), and starting (10%). CONCLUSION: Most Achilles tendon ruptures in professional male football players are closed-chain indirect or non-contact injuries. Sudden loading to the plantarflexor musculotendinous unit remains to be the main component for most cases. By achieving a better understanding of underlying injury mechanisms, this study provides new strategies for the prevention of Achilles tendon ruptures. LEVEL OF EVIDENCE: Level IV.

Improved Estimation of Exercise Intensity Thresholds by Combining Dual Non-Invasive Biomarker Concepts: Correlation Properties of Heart Rate Variability and Respiratory Frequency.

Identifying exercise intensity boundaries has been shown to be important during endurance training for performance enhancement and rehabilitation. Unfortunately, even though surrogate markers show promise when assessed on a group level, substantial deviation from gold standards can be present in each individual. The aim of this study was to evaluate whether combining two surrogate intensity markers improved this agreement. Electrocardiogram (ECG) and gas exchange data were obtained from 21 participants who performed an incremental cycling ramp to exhaustion and evaluated for first (VT1) and second (VT2) ventilatory thresholds, heart rate (HR) variability (HRV), and ECG derived respiratory frequency (EDR). HRV thresholds (HRVT) were based on the non-linear index a1 of a Detrended Fluctuation Analysis (DFA a1) and EDR thresholds (EDRT) upon the second derivative of the sixth-order polynomial of EDR over time. The average of HRVT and EDRT HR was set as the combined threshold (Combo). Mean VT1 was reached at a HR of 141 ± 15, HRVT1 at 152 ± 14 (p < 0.001), EDRT1 at 133 ± 12 (p < 0.001), and Combo1 at 140 ± 13 (p = 0.36) bpm with Pearson's r of 0.83, 0.78, and 0.84, respectively, for comparisons to VT1. A Bland-Altman analysis showed mean biases of 8.3 ± 7.9, -8.3 ± 9.5, and -1.7 ± 8.3 bpm, respectively. A mean VT2 was reached at a HR of 165 ± 13, HRVT2 at 167 ± 10 (p = 0.89), EDRT2 at 164 ± 14 (p = 0.36), and Combo2 at 164 ± 13 (p = 0.59) bpm with Pearson's r of 0.58, 0.95, and 0.94, respectively, for comparisons to VT2. A Bland-Altman analysis showed mean biases of -0.3 ± 8.9, -1.0 ± 4.6, and -0.6 ± 4.6 bpm, respectively. Both the DFA a1 and EDR intensity thresholds based on HR taken individually had moderate agreement to targets derived through gas exchange measurements. By combining both non-invasive approaches, there was improved correlation, reduced bias, and limits of agreement to the respective corresponding HRs at VT1 and VT2.

The Between-Day Reliability of Correlation Properties of Heart Rate Variability During Running.

The short-term scaling exponent of detrended fluctuation analysis (DFA-a1) of heart rate variability may be a helpful tool to assess autonomic balance as a prelude to daily, individualized training. For this concept to be useful, between-session reliability should be acceptable. The aim of this study was to explore the reliability of DFA-a1 during a low-intensity exercise session in both a non-fatigued and a fatigued condition in healthy males and females. Ten participants completed two sessions with each containing an exhaustive treadmill ramp protocol. Before and after the fatiguing ramp, a standardized submaximal low-intensity exercise bout was performed during which DFA-a1, heart rate, and oxygen consumption (VO2) were measured. We compared between-session reliability of all metrics prior to the ramps (i.e., non-fatigued status) and after the first ramp (i.e., fatigued status). Intraclass correlation coefficients (ICC) with 95% confidence intervals (CI), the standard error of measurement, and the smallest worthwhile change (SWC) were determined. The ICC and SWC pre fatiguing ramp were 0.85 (95% CI 0.39-0.96) and 5.5% for DFA-a1, 0.85 (0.38-0.96) and 2.2% for heart rate, and 0.84 (0.31-0.96) and 3.1% for VO2. Post fatiguing ramp, the ICC and SWC were 0.55 (0.00-0.89) and 7.9% for DFA-a1, 0.91 (0.62-0.98) and 1.6% for heart rate, and 0.80 (0.17-0.95) and 3.0% for VO2. DFA-a1 shows generally acceptable to good between-session reliability with a SWC of 0.06 and 0.07 (5.5-7.9%) during non-fatigued and fatigued conditions. This suggests that this metric may be useful to inform on training readiness.

[Motoric cognitive risk syndrome-Setting the course for dementia prevention?] / Motor-kognitives Risikosyndrom ­ Weichenstellung für die Demenzprävention?

BACKGROUND: The predicted increase in adults with dementia will pose a major challenge for the German healthcare system. To mitigate this challenge, the early detection of adults with an increased risk of dementia is crucial. In this context, the concept of motoric cognitive risk (MCR) syndrome has been introduced into the English literature but is currently relatively unknown in German-speaking countries. OBJECTIVE: What are the characteristics and diagnostic criteria of MCR? What is the impact of MCR on health-related parameters? What is the current state of evidence regarding the risk factors and prevention of the MCR? MATERIAL AND METHODS: We reviewed the English language literature concerning MCR, the associated risk factors, and protective factors, similarities or differences with the concept of mild cognitive impairment (MCI), and its influence on the central nervous system. RESULTS: The MCR syndrome is characterized by subjective cognitive impairment and a slower gait speed. Compared to healthy adults, adults with the MCR have a higher risk of dementia, falls, and mortality. Modifiable risk factors provide a starting point for specific multimodal lifestyle-related preventive interventions. CONCLUSION: As MCR can be easily diagnosed in practical settings, it could become an important concept for the early detection of adults with an increased risk of dementia in German-speaking countries, although further research is necessary to empirically confirm this assumption.

Hamstring injury patterns in professional male football (soccer): a systematic video analysis of 52 cases.

OBJECTIVE: To closely describe the injury inciting events of acute hamstring injuries in professional male football (soccer) using systematic video analysis. METHODS: Video footage from four seasons (2014-2019) of the two highest divisions in German male football was searched for moderate and severe (ie, time loss of >7 days) acute non-contact and indirect contact match hamstring injuries. Two raters independently categorised inciting events using a standardised procedure to determine specific injury patterns and kinematics. RESULTS: 52 cases of hamstring injuries were included for specific pattern analysis. The pattern analysis revealed 25 sprint-related (48%) and 27 stretch-related hamstring injuries (52%). All sprint-related hamstring injuries occured during linear acceleration or high-speed running. Stretch-related hamstring injuries were connected with closed chain movements like braking or stopping with a lunging or landing action and open chain movements like kicking. The kinematic analysis of stretch-related injuries revealed a change of movement involving knee flexion to knee extension and a knee angle of <45° at the assumed injury frame in all open and closed chain movements. Biceps femoris was the most affected muscle (79%) of all included cases. CONCLUSION: Despite the variety of inciting events, rapid movements with high eccentric demands of the posterior thigh are likely the main hamstring injury mechanism. This study provides important data about how hamstring injuries occur in professional male football and supports the need for demand-specific multicomponent risk reduction programmes.

Estimation of Respiratory Frequency in Women and Men by Kubios HRV Software Using the Polar H10 or Movesense Medical ECG Sensor during an Exercise Ramp.

Monitoring of the physiologic metric, respiratory frequency (RF), has been shown to be of value in health, disease, and exercise science. Both heart rate (HR) and variability (HRV), as represented by variation in RR interval timing, as well as analysis of ECG waveform variability, have shown potential in its measurement. Validation of RF accuracy using newer consumer hardware and software applications have been sparse. The intent of this report is to assess the precision of the RF derived using Kubios HRV Premium software version 3.5 with the Movesense Medical sensor single-channel ECG (MS ECG) and the Polar H10 (H10) HR monitor. Gas exchange data (GE), RR intervals (H10), and continuous ECG (MS ECG) were recorded from 21 participants performing an incremental cycling ramp to failure. Results showed high correlations between the reference GE and both the H10 (r = 0.85, SEE = 4.2) and MS ECG (r = 0.95, SEE = 2.6). Although median values were statistically different via Wilcoxon testing, adjusted median differences were clinically small for the H10 (RF about 1 breaths/min) and trivial for the MS ECG (RF about 0.1 breaths/min). ECG based measurement with the MS ECG showed reduced bias, limits of agreement (maximal bias, -2.0 breaths/min, maximal LoA, 6.1 to -10.0 breaths/min) compared to the H10 (maximal bias, -3.9 breaths/min, maximal LoA, 8.2 to -16.0 breaths/min). In conclusion, RF derived from the combination of the MS ECG sensor with Kubios HRV Premium software, tracked closely to the reference device through an exercise ramp, illustrates the potential for this system to be of practical usage during endurance exercise.

Validity of the Polar H10 Sensor for Heart Rate Variability Analysis during Resting State and Incremental Exercise in Recreational Men and Women.

Heart rate variability (HRV) is frequently applied in sport-specific settings. The rising use of freely accessible applications for its recording requires validation processes to ensure accurate data. It is the aim of this study to compare the HRV data obtained by the Polar H10 sensor chest strap device and an electrocardiogram (ECG) with the focus on RR intervals and short-term scaling exponent alpha 1 of Detrended Fluctuation Analysis (DFA a1) as non-linear metric of HRV analysis. A group of 25 participants performed an exhaustive cycling ramp with measurements of HRV with both recording systems. Average time between heartbeats (RR), heart rate (HR) and DFA a1 were recorded before (PRE), during, and after (POST) the exercise test. High correlations were found for the resting conditions (PRE: r = 0.95, rc = 0.95, ICC3,1 = 0.95, POST: r = 0.86, rc = 0.84, ICC3,1 = 0.85) and for the incremental exercise (r > 0.93, rc > 0.93, ICC3,1 > 0.93). While PRE and POST comparisons revealed no differences, significant bias could be found during the exercise test for all variables (p < 0.001). For RR and HR, bias and limits of agreement (LoA) in the Bland−Altman analysis were minimal (RR: bias of 0.7 to 0.4 ms with LoA of 4.3 to −2.8 ms during low intensity and 1.3 to −0.5 ms during high intensity, HR: bias of −0.1 to −0.2 ms with LoA of 0.3 to −0.5 ms during low intensity and 0.4 to −0.7 ms during high intensity). DFA a1 showed wider bias and LoAs (bias of 0.9 to 8.6% with LoA of 11.6 to −9.9% during low intensity and 58.1 to −40.9% during high intensity). Linear HRV measurements derived from the Polar H10 chest strap device show strong agreement and small bias compared with ECG recordings and can be recommended for practitioners. However, with respect to DFA a1, values in the uncorrelated range and during higher exercise intensities tend to elicit higher bias and wider LoA.

The Movesense Medical Sensor Chest Belt Device as Single Channel ECG for RR Interval Detection and HRV Analysis during Resting State and Incremental Exercise: A Cross-Sectional Validation Study.

The value of heart rate variability (HRV) in the fields of health, disease, and exercise science has been established through numerous investigations. The typical mobile-based HRV device simply records interbeat intervals, without differentiation between noise or arrythmia as can be done with an electrocardiogram (ECG). The intent of this report is to validate a new single channel ECG device, the Movesense Medical sensor, against a conventional 12 channel ECG. A heterogeneous group of 21 participants performed an incremental cycling ramp to failure with measurements of HRV, before (PRE), during (EX), and after (POST). Results showed excellent correlations between devices for linear indexes with Pearson's r between 0.98 to 1.0 for meanRR, SDNN, RMSSD, and 0.95 to 0.97 for the non-linear index DFA a1 during PRE, EX, and POST. There was no significant difference in device specific meanRR during PRE and POST. Bland-Altman analysis showed high agreement between devices (PRE and POST: meanRR bias of 0.0 and 0.4 ms, LOA of 1.9 to -1.8 ms and 2.3 to -1.5; EX: meanRR bias of 11.2 to 6.0 ms; LOA of 29.8 to -7.4 ms during low intensity exercise and 8.5 to 3.5 ms during high intensity exercise). The Movesense Medical device can be used in lieu of a reference ECG for the calculation of HRV with the potential to differentiate noise from atrial fibrillation and represents a significant advance in both a HR and HRV recording device in a chest belt form factor for lab-based or remote field-application.

Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination.

Recent study points to the value of a non-linear heart rate variability (HRV) biomarker using detrended fluctuation analysis (DFA a1) for aerobic threshold determination (HRVT). Significance of recording artefact, correction methods and device bias on DFA a1 during exercise and HRVT is unclear. Gas exchange and HRV data were obtained from 17 participants during an incremental treadmill run using both ECG and Polar H7 as recording devices. First, artefacts were randomly placed in the ECG time series to equal 1, 3 and 6% missed beats with correction by Kubios software's automatic and medium threshold method. Based on linear regression, Bland Altman analysis and Wilcoxon paired testing, there was bias present with increasing artefact quantity. Regardless of artefact correction method, 1 to 3% missed beat artefact introduced small but discernible bias in raw DFA a1 measurements. At 6% artefact using medium correction, proportional bias was found (maximum 19%). Despite this bias, the mean HRVT determination was within 1 bpm across all artefact levels and correction modalities. Second, the HRVT ascertained from synchronous ECG vs. Polar H7 recordings did show an average bias of minus 4 bpm. Polar H7 results suggest that device related bias is possible but in the reverse direction as artefact related bias.

Correlation Properties of Heart Rate Variability during a Marathon Race in Recreational Runners: Potential Biomarker of Complex Regulation during Endurance Exercise.

There is only very limited data examining cardiovascular responses in real-world endurance training/competition. The present study examines the influence of a marathon race on non-linear dynamics of heart rate (HR) variability (HRV). Eleven male recreational runners performed a self-paced marathon road race on an almost flat profile. During the race, heart rate and beat-to-beat (RR) intervals were recorded continuously. Besides HRV time-domain measurements, fractal correlation properties using short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) were calculated. The mean finishing time was 3:10:22 ± 0:17:56 h:min:s with a blood lactate concentration of 4.04 ± 1.12 mmol/L at the end of the race. Comparing the beginning to the end segment of the marathon race (Begin vs. End) significant increases could be found for km split time (p < .001, d = .934) and for HR (p = .010, d = .804). Significant decreases could be found for meanRR (p = .013, d = .798) and DFA-alpha1 (p = .003, d = 1.132). DFA-alpha1 showed an appropriate dynamic range throughout the race consisting of both uncorrelated and anti-correlated values. Lactate was consistent with sustained high intensity exercise when measured at the end of the event. Despite the runners slowing after halfway, DFA-alpha1 continued to fall to values seen in the highest intensity domain during incremental exercise testing in agreement with lactate assessment. Therefore, the discrepancy between the reduced running pace with that of the decline of DFA-alpha1, demonstrate the benefit of using this dimensionless HRV index as a biomarker of internal load during exercise over the course of a marathon race.

Correlation properties of heart rate variability during endurance exercise: A systematic review.

BACKGROUND: Non-linear measures of heart rate variability (HRV) may provide new opportunities to monitor cardiac autonomic regulation during exercise. In healthy individuals, the HRV signal is mainly composed of quasi-periodic oscillations, but it also possesses random fluctuations and so-called fractal structures. One widely applied approach to investigate fractal correlation properties of heart rate (HR) time series is the detrended fluctuation analysis (DFA). DFA is a non-linear method to quantify the fractal scale and the degree of correlation of a time series. Regarding the HRV analysis, it should be noted that the short-term scaling exponent alpha1 of DFA has been used not only to assess cardiovascular risk but also to assess prognosis and predict mortality in clinical settings. It has also been proven to be useful for application in exercise settings including higher exercise intensities, non-stationary data segments, and relatively short recording times. METHOD: Therefore, the purpose of this systematic review was to analyze studies that investigated the effects of acute dynamic endurance exercise on DFA-alpha1 as a proxy of correlation properties in the HR time series. RESULTS: The initial search identified 442 articles (351 in PubMed, 91 in Scopus), of which 11 met all inclusion criteria. CONCLUSIONS: The included studies show that DFA-alpha1 of HRV is suitable for distinguishing between different organismic demands during endurance exercise and may prove helpful to monitor responses to different exercise intensities, movement frequencies, and exercise durations. Additionally, non-linear DFA of HRV is a suitable analytical approach, providing a differentiated and qualitative view of exercise physiology.

Non-linear dynamics of heart rate variability during incremental cycling exercise.

Within the last years complex models of cardiovascular regulation and exercise fatigue have implemented heart rate variability (HRV) as a measure of autonomic nervous system. Using detrended fluctuation analysis (DFA) to assess heart rate correlation properties, the present study examines the influence of exercise intensity on total variability and complexity in non-linear dynamics of HRV. Sixteen cyclists performed a graded exercise test on a bicycle ergometer. HRV time domain measures and fractal correlation properties were analyzed using short-term scaling exponent alpha1 of DFA. Amplitude and complexity of HRV parameters decreased significantly. DFA-alpha1 increased from rest to low exercise intensity and showed an almost linear decrease from higher intensities until exhaustion. These findings support a qualitative change in self-organized heart rate regulation from a complex autonomic control at rest and low intensities towards a breakdown of the interaction in control mechanisms with non-autonomic heart rate control dominating at high intensities.

Four weeks of high cadence training alter brain cortical activity in cyclists.

Exercise at different cadences might serve as potential stimulus for functional adaptations of the brain, because cortical activation is sensitive to frequency of movement. Therefore, we investigated the effects of high (HCT) and low cadence training (LCT) on brain cortical activity during exercise as well as endurance performance. Cyclists were randomly assigned to low and high cadence training. Over the 4-week training period, participants performed 4 h of basic endurance training as well as four additional cadence-specific exercise sessions, 60 min weekly. At baseline and after 4 weeks, participants completed an incremental exercise test with spirometry and exercise at constant load with registration of electroencephalogram (EEG). Compared with LCT, a greater increase of frontal alpha/beta ratio was confirmed in HCT. This was based on a lower level of beta activity during exercise. Both groups showed similar improvements in maximal oxygen consumption and power at the individual anaerobic threshold. Whereas HCT and LCT elicit similar benefits on aerobic performance, cycling at high pedalling frequencies enables participants to perform an exercise bout with less cortical activation.

The Athlete's Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise.

The "neural efficiency" hypothesis suggests that experts are characterized by a more efficient cortical function in cognitive tests. Although this hypothesis has been extended to a variety of movement-related tasks within the last years, it is unclear whether or not neural efficiency is present in cyclists performing endurance exercise. Therefore, this study examined brain cortical activity at rest and during exercise between cyclists of higher (HIGH; n = 14; 55.6 ± 2.8 mL/min/kg) and lower (LOW; n = 15; 46.4 ± 4.1 mL/min/kg) maximal oxygen consumption (VO2MAX). Male and female participants performed a graded exercise test with spirometry to assess VO2MAX. After 3 to 5 days, EEG was recorded at rest with eyes closed and during cycling at the individual anaerobic threshold over a 30 min period. Possible differences in alpha/beta ratio as well as alpha and beta power were investigated at frontal, central, and parietal sites. The statistical analysis revealed significant differences between groups (F = 12.04; p = 0.002), as the alpha/beta ratio was increased in HIGH compared to LOW in both the resting state (p ≤ 0.018) and the exercise condition (p ≤ 0.025). The present results indicate enhanced neural efficiency in subjects with high VO2MAX, possibly due to the inhibition of task-irrelevant cognitive processes.

Do Male And Female Cyclists' Cortical Activity Differ Before and During Cycling Exercise?

Although men and women are suggested to vary in resistance to fatigue, possible sex difference in its central component have rarely been investigated via electroencephalography (EEG). Therefore, we examined differences in cortical activity between male and female cyclists (n = 26) during cycling exercise. Participants performed an incremental test to derive the anaerobic threshold from the lactate power curve. In addition, cyclists' cortical activity was recorded with EEG before and during cycling exercise. Whereas women showed higher frontal alpha and beta activity at rest, no sex-specific differences of relative EEG spectral power occurred during cycling at higher intensity. Women and men's brains respond similarly during submaximal cycling, as both sexes show an inverted U-shaped curve of alpha power. Therefore, sex differences observable at rest vanish after the onset of exercise.