Effects of Heat Exposure on Body Water Assessed using Single-Frequency Bioelectrical Impedance Analysis and Bioimpedance Spectroscopy

International Journal of Exercise Science 10(7): 1085-1093, 2017. The purpose of this study was to determine if heat exposure alters the measures of total body water (TBW), extracellular water (ECW), and intracellular water (ICW) in both single-frequency bioelectrical impedance analysis (BIA) and bioimpedance spectroscopy (BIS). Additionally, we sought to determine if any differences exist between the BIA and BIS techniques before and after brief exposure to heat. Body water was evaluated for twenty men (age=24±4 years) in a thermoneutral environment (22°C) before (PRE) and immediately after (POST) 15 min of passive heating (35°C) in an environmental chamber. The mean difference and 95% limits of agreement at PRE demonstrated that BIS yielded significantly higher body water values than BIA (all p0.05; 0.2±1.5kg). Additionally, the ES of the mean differences at POST were trivial to small and the r-values were high (r≥0.96). When analyzing the changes in body water before and after heat exposure, POST values for BIS were significantly higher than PRE (all

Comparison of Electromyographical Signal Analyses for Estimating Lactate Threshold

Background: Currently, no published literature exists comparing the most appropriate and efficient filtering methods of electromyographical (EMG) analyses to estimate the workload at which lactate threshold (LT) occurs. Purpose: The purpose of this investigation was to evaluate and compare EMG transformations and time windows to predict LT. Methods: Participants (n=14) completed a maximal exercise test on a cycle ergometer until exhaustion. Blood lactate was measured every minute, while EMG was recorded continuously at the vastus lateralis. EMG signaling was then transformed and filtered using two time-segment windows (i.e., 10 and 60 seconds), as well as three signal conversions (i.e., root mean square, smoothing, and peak amplitude averaging). Results: Results indicated no mean differences between the EMG thresholds, for any of the filtering methods or time-segment windows, when compared to the LT criterion. Moderate correlations were seen when comparing the lactate and EMG time-curves ranging from 0.69 – 0.79. Conclusions: EMG may be a useful tool to estimate the work rate associated with LT. Averaging EMG over a minute of time and continual 10-second recordings demonstrate comparable readings and allow an easier application of EMG threshold in the field

The Predictability of Peak Oxygen Consumption Using Submaximal Ratings of Perceived Exertion in Adolescents

International Journal of Exercise Science 11(4): 1173-1183, 2018. Rating of perceived exertion (RPE) extrapolation involves mathematically extending the submaximal relationship between RPE and oxygen consumption (VO2) to maximal intensity. This technique allows practitioners to forego, potentially dangerous, maximal exertion testing while attaining accurate measures of maximal oxygen consumption used for exercise prescription. This method has been proven accurate in adults, but much less in known when applied to an adolescent population. The purpose of this study was to assess the accuracy of the RPE extrapolation as method for estimating VO2max in adolescents. Twenty-two healthy, asymptomatic adolescents performed a graded exercise test (GXT) to exhaustion. Heart rate and VO2 were recorded throughout the bout with RPE being queried every two minutes using the Borg (6-20) RPE scale. Individual regression lines were fitted for each subject using RPE and VO2 for RPE values up to 13,15, and 17. Theoretical maximal RPE values of 20 and 19 were entered into the equation to calculate an estimated VO2max. Repeated measures ANOVA with planned contrasts showed that all VO2max estimation methods significantly overpredicted measured VO2max (p \u3c .001). Error analysis via Bland-Altman plots revealed large limits of agreement between the all methods, indicating large variability in error between estimated and measured VO2max. The results suggest that submaximal RPE values using the Borg scale cannot be used to predict VO2max in children due to the amount of error in the prediction equations. These inaccuracies could lead to potential under or over-prescription of exercise intensity and adverse effects on the person’s health

Reliability of Lactate Threshold Following a Fatiguing Bout of Exercise

Background: Assessment and monitoring of lactate threshold (LT) are important factors to monitor to prioritize which metabolic system is being stressed. LT training is a popular form of training due to its ability improve anaerobic performance. Furthermore, training below this intensity can be extremely advantageous for producing adaptations to aid in aerobic performance. However, accumulation of fatigue has been shown to precipitate changes to muscle recruitment strategies and metabolic pathways. These changes could then lower the intensity at which lactate begins to accumulate. The purpose of this study was to evaluate the reliability of LT threshold following a bout of exhaustive exercise. Methods: Eleven healthy, asymptomatic adults completed two graded exercises tests (GXT) interspersed with a 30-min fatiguing cycling session. The GXT started at 80 watts followed by increases of 40 W every three minutes at a cadence of 80 rpm. The GXT was ended upon volitional exhaustion or if cadence dropped below 75 rpm. Oxygen consumption was recorded throughout the GXT trials, while lactate was recorded every minute. The thirty minute fatiguing trial was completed at one stage above LT. Raw lactate values from the GXT tests were then input into a Dmax calculator in order to obtain threshold values and the corresponding stages in which they occurred. Results: A paired samples T-test found revealed significant differences in baseline lactate values from when comparing the pre-fatigue trial (1.55 ± 0.49 mmol.L-1) to the post fatigue trial (3.44 ± 2.04 mmol.L-1; p = 0.09, Cohen’s d = 1.27). No significant mean differences were seen in lactate values threshold during the pre-fatigue trial (3.56 ± 0.84 mmol.L-1) versus the post fatigue trial (3.50 ± 1.99 mmol.L-1). However, when expressed as a wattage, LT occurred at a significantly higher wattage in the pre-fatigue trial than the post fatigue trial (128 vs. 104 watts; p = 0.03). Half of the participants reached LT during the same stage of the GXT, while four participants had an LT that occurred one stage lower in the post fatigue trial than the pre-fatigue trial. When expressed as %VO2peak, there were no significant mean differences between pre-fatigue LT compared to post fatigue LT (p = 0.19; Cohen’s d = 0.75). LT with poor reliability (ICC = -0.36; 95% CI = -3.32 to 0.637; p = 0.69). Furthermore, there were no significant mean differences in LT when data was expressed as %HRmax (p = 0.74, Cohen’s d = 0.17). Conclusions: A fatiguing bout of exercise does not mediate LT when examining blood lactate levels, or when LT is represented as a percentage of maximal heart rate and peak oxygen consumption. However, it appears that the power output needed to achieve LT is significantly lower after fatigue has set in. Practical Application: Lactate threshold is an important metric for prescribing exercise intensity for optimal athletic performance. Practitioners need to confirm that the athlete is adequately recovered before measuring LT to ensure an accuracy of the work output measure. Furthermore, LT training should be prescribed as a %HRmax or %VO2peak rather than a raw power to help control for the effect of fatigue on the measure

Ability of Wearable Electromyographical Compression Shorts to Predict Lactate Threshold

Background: Proper determination of lactate threshold (LT) is an important variable in improving cardiovascular endurance and performance. Unfortunately, monitoring LT during exercise is a costly, invasive blood analysis, which requires either capillary blood samples or an indwelling venous catheter. However, electromyography (EMG) is a potential new method of monitoring exercise intensity and may provide a novel, non-invasive technique to monitor lactate during exercise. Purpose: The purpose of this investigation was to determine if EMG compression shorts accurately estimated LT during incremental cycling. Methods: Thirteen adult men (n = 8) and women (n = 5) volunteered to participate in this study. Participants completed an incremental, maximal graded exercise test on a cycle ergometer. Blood lactate, heart rate, and oxygen consumption were measured every minute, while EMG was recorded continuously throughout the test at the vastus lateralis. Surface EMG signals were acquired via compression shorts containing built-in, non-invasive surface electrodes. The lactate and EMG thresholds were determined in each participant via Dmax calculations. Results: Results demonstrated no significant difference in work rate (p = 0.08) between lactate and electromyographical thresholds. Additionally, no mean differences existed between EMG and lactate thresholds for maximal heart rate (p = 0.13, Cohen’s d = 0.43) or percent peak oxygen consumption (p = 0.64, Cohen’s d = 0.09). Consistent with previous results, EMG provided a moderate correlation with the prediction of work rate associated with the LT (r = 0.68, p = 0.01). Conclusions: The results demonstrate that no differences occurred between LT and EMG threshold for any of the metrics examined (i.e., work rate, heart rate, or oxygen consumption). This confirms that both lactate and EMG exhibit similar properties (i.e., increasing exponential values) during incremental exercise. A possible mechanism includes the rise in blood lactate concentration increasing motor unit recruitment in an attempt to maintain proper cadence and force output during incremental exercise. Thus, a coincidental, exponential increase in EMG amplitude may occur. Practical Application: Monitoring blood lactate values may be an important determinant of the ability of the athlete to maintain pre-determined exercise intensities for extended durations. Therefore, EMG, monitored via specialized compression gear, may provide a viable option in monitoring training intensity and predicting LT levels due to its ability to provide feedback in real-time

Comparison of Electromyographical Signal Analyses for Estimating Lactate Threshold

Background: The relationship between the lactate and electromyographical (EMG) thresholds have previously been established via graded exercising testing during cycling. Currently, no published literature exists comparing the most appropriate and efficient filtering methods of EMG analyses to estimate the workload at which lactate threshold (LT) occurs. Purpose: The purpose of this investigation was to evaluate and compare EMG transformations and time windows to predict LT. Methods: Participants (n=14) completed an incremental, maximal exercise test on a cycle ergometer until exhaustion. Blood lactate was measured every minute, while EMG was recorded continuously at the site of the vastus lateralis. EMG signaling was then transformed and filtered using two time-segment windows (i.e., 10 and 60 seconds), as well as three signal conversions (i.e., root mean square, smoothing, and peak amplitude averaging). Results: Results indicated no mean differences between the EMG thresholds, for any of the filtering methods or time-segment windows, when compared to the LT criterion. Significant moderate correlations were seen when comparing the lactate and EMG time-curves ranging from 0.69 - 0.79. Root mean square and Smoothing filters accurately indicated LT in 10 out of 14 participants; whereas peak amplitude averaging indicated LT for 11 out of 14 participants. Conclusions: EMG may be a useful tool to estimate the work rate associated with LT. Averaging EMG over a minute of time and continual 10-second recordings demonstrate comparable readings and allow an easier application of EMG threshold in the field

Ability of Wearable Electromyographical Compression Shorts to Predict Lactate Threshold

Background: Proper determination of lactate threshold (LT) is an important variable in improving cardiovascular endurance and performance. Unfortunately, monitoring LT during exercise is a costly, invasive blood analysis, which requires either capillary blood samples or an indwelling venous catheter. However, electromyography (EMG) is a potential new method of monitoring exercise intensity and may provide a novel, non-invasive technique to monitor lactate during exercise. Purpose: The purpose of this investigation was to determine if EMG compression shorts accurately estimated LT during incremental cycling. Methods: Thirteen adult men (n = 8) and women (n = 5) volunteered to participate in this study. Participants completed an incremental, maximal graded exercise test on a cycle ergometer. Blood lactate, heart rate, and oxygen consumption were measured every minute, while EMG was recorded continuously throughout the test at the vastus lateralis. Surface EMG signals were acquired via compression shorts containing built-in, non-invasive surface electrodes. The lactate and EMG thresholds were determined in each participant via Dmax calculations. Results: Results demonstrated no significant difference in work rate (p = 0.08) between lactate and electromyographical thresholds. Additionally, no mean differences existed between EMG and lactate thresholds for maximal heart rate (p = 0.13, Cohen’s d = 0.43) or percent peak oxygen consumption (p = 0.64, Cohen’s d = 0.09). Consistent with previous results, EMG provided a moderate correlation with the prediction of work rate associated with the LT (r = 0.68, p = 0.01). Conclusions: The results demonstrate that no differences occurred between LT and EMG threshold for any of the metrics examined (i.e., work rate, heart rate, or oxygen consumption). This confirms that both lactate and EMG exhibit similar properties (i.e., increasing exponential values) during incremental exercise. A possible mechanism includes the rise in blood lactate concentration increasing motor unit recruitment in an attempt to maintain proper cadence and force output during incremental exercise. Thus, a coincidental, exponential increase in EMG amplitude may occur. Practical Application: Monitoring blood lactate values may be an important determinant of the ability of the athlete to maintain pre-determined exercise intensities for extended durations. Therefore, EMG, monitored via specialized compression gear, may provide a viable option in monitoring training intensity and predicting LT levels due to its ability to provide feedback in real-time

The Effect of Fatigue on Rate of Change of Physiological Markers on Exertion During Graded Exercise

Background: The accumulation of fatigue during exercise can severely impact performance, physiological systems, and perceptual responses causing a disassociation between external work and physiological variables. Often times variables such as heart rate (HR) and rating of perceived exertion (RPE) are used to prescribe exercise intensity. It may be that in a fatigued state, these variables disassociate from external work, thus causing the athlete to either overestimate or underestimate their performance. This could lead to either underperformance due to training and a decreased intensity or overtraining which again leads to detrimental performance. Thus, the purpose of this study was to evaluate the role that acute fatigue plays in measures of physiological markers of exertion. Methods: Ten healthy, college-aged subjects participated in two graded exercise tests (GXT), interspersed with a 30-min, steady state fatiguing protocol. Both GXT’s started with an initial workload of 80 watts with 40 watt increases in workload every three minutes and subjects were asked to maintain a cadence of 80 ± 5 revolutions per minute. The test was terminated upon volitional exhaustion or the inability to maintain a cadence of at least 75 revolutions per minute. Subjects were then given 15 minutes to recover before beginning the fatiguing protocol, which intensity was set at one stage below lactate threshold, which was measured during the initial GXT. Immediately following the 30 minute fatiguing session, subjects were asked to complete another GXT identical to the first one. Heart rate, relative VO2, lactate, and rating of perceived exertion were recorded within the last minute of each stage of the tests. Hierarchical linear growth modeling (HLGM) was used to control for variance across trial (pre-fatigue vs. post-fatigue) and stage, as well as allow for missing data from cessation of exercise at different stages. Results: The analysis revealed no main effect for trial (p = 0.27) or interaction effect for VO2 (p = 0.49). However, there was a significant main effect for trial on heart rate where subjects in the post fatigue session exhibited a significantly higher heart rate than the pre-fatigue trial despite equivalent intensities (91 bpm vs. 104 bpm; p \u3c 0.001). As to be expected, rate of HR increase was significant with HR increasing 18 bpm per stage. Lastly, there was a significant trial effect for rating of perceived exertion where participants reported an RPE 1.7 points higher in the post fatigue trial (p = 0.002). A significant time effect was also observed where RPE increased linearly from at a rate of 3.02 points per stage. Conclusions: It appears that fatigue severely impacts measures of exertion at equivalent exercise intensities. Both rate of HR increase and RPE were found to be significantly higher in the post fatigue trials. If athletes were asked to control performance by RPE or HR in a fatigued state then this would lead to under performance. Practical Application: Practitioners need to be weary of prescribing exercise based upon HR or RPE during periods of high intensity training. It is suggested that measures of external work (i.e., %1-RM or km/h) are used to help alleviate this discrepancies brought on by accumulated fatigue. That notwithstanding, practitioners should not be dismissive of these inflated perceptual and physiological measures, as they may be signs of impending overtraining