appropriate responses to exercise stressors are driven , in large part , by the autonomic nervous system ( ans ) and the resultant balance between sympathetic and parasympathetic influences on peripheral tissues ( sympathovagal balance )
. heart rate ( hr ) and the variability of heart beat - to - beat intervals , i.e. , heart rate variability ( hrv ) , are indirect metrics reflecting ans activity ( 19 ) , and reflect stress level during large muscle mass , dynamic exercise like running and cycling . however , the accuracy of these metrics in the field is complicated by the disproportionate change in the sympathovagal balance versus intensity relationship at or around the anaerobic threshold ( at ) ( 8 , 14,16,17 , 21 , 22 ) .
numerous studies have identified hr threshold ( hrt ) and  thresholds  for various hrv metrics corresponding to at ( 6 , 2 , 10 , 11 , 13 , 18 ) .
expressing stress level relative to such a hr or hrv threshold ( e.g. , power output eliciting 75% of hrt ) , as opposed to absolute cardiac metrics , would allow accurate , real - time pacing in the field .
furthermore , the ability to assess at in the field using hr or hrv would be more applicable for athletes and coaches than established laboratory - based techniques such as lactate threshold ( lt ) and ventilatory threshold ( vt ) ( 6 ) .
most investigations that evaluate hr or hrv versus intensity use continuous incremental exercise protocols ( reviewed in 6 ) .
the exercise stages for these protocols typically last 12 min , which does not allow time for adequate sympathovagal balance .
this is due to inherent fluctuations of efferent / afferent control systems , which are more dynamic during the initial response to stress .
once the appropriate afferent / efferent balance is achieved , the recorded metric will not fluctuate greatly ( i.e. ,  steady state  ) unless the stress level changes .
for instance , during exercise of a given intensity , o2 consumption and hr both rise during the first minutes exercise ( 14 ) . therefore , in the first minute of a 12 min exercise stage , it is difficult to know if data collected during the first minutes of a given exercise stage reflect steady - state responses ( 5 ) .
in addition , with continuous protocols it is probable that responses to one exercise stage carryover to the next stage .
because of this , development of accurate linear relationships between hr / hrv and intensities below at are not possible .
therefore , the ideal endurance training output at hrt derived from a continuous test protocol would be misidentified , and premature fatigue would likely occur .
discontinuous incremental exercise protocols allow for longer stages at given intensities and brief recovery periods .
in such a protocol , exercise performance metrics such as hr and vo2 are assessed late in the exercise stage ( e.g. , after 35 min of the same exercise intensity ) .
thus , the assessment occurs after hr and vo2 responses have plateaued , reflecting appropriately  balanced
additionally , the recovery period in between stages ensures that the subsequent stage data is not influenced by protracted factors from a previous stage ( i.e. , lactic acid , epinephrine , etc . ) .
because of these differences , discontinuous protocols allow for a true indication of steady - state physiologic stress responses , independent of the possible carryover effects from previous exercise stages ( reviewed in 5 ) compared to continuous protocols . despite the physiological benefits described above , discontinuous protocols have not been used to study simple surrogate measures of at .
therefore , the purpose of the present study was to determine if changes in hr and/or hrv would reflect at using a discontinuous , incremental , cycle test . to accomplish this ,
exercise thresholds were determined for hr and hrv metrics and compared with the criterion at assessment , vt .
using a student t - based algorithm with an alpha = 0.05 , and beta ( power level ) = 80% , a power analysis was run to determine the minimum number of subjects required for our comparison .
it was determined based on available pilot data for at ( n=100 , sd=20 ) , that 15 subjects were needed to detect a 5 w difference in w at at .
experienced cyclists , age 1835 y , were recruited for this study , with eight female and seven male participants subjected to the protocols described below . for this study ,
the term  experienced cyclist  was defined as an individual self - reporting moderate intensity cycling an average of three times per week .
this study was approved by the institutional review board for the protection of human subjects in research of the university of texas at san antonio .
written informed consent was obtained from all participants following a verbal and written briefing of all experimental procedures .
participants were asked to abstain from stimulants , including caffeine , exercise , and alcohol 12 h before the cycling sessions .
participants reported to the laboratory in the morning after an 8 h fasting condition on two sessions .
the height and weight of the participants was recorded and their body composition was assessed using 7-site skinfolds ( 1 ) .
four frame measurements were taken on each participant s bicycle were matched on a lode excalibur ( lode b.v . , groningen , netherlands ) cycle ergometer to reproduce the participants training position .
participants performed all testing in their usual training attire and used their own cycle pedals and shoes .
all procedures were performed in a thermoneutral environment under close supervision of laboratory assistants familiar with the testing protocol and data collection . following measurement of shoeless height and body mass ,
participants were outfitted with a breathing mask allowing for inhalation of room air and analysis of expired air for ventilation ( ve ; l airmin1 ) , oxygen consumption ( vo2 ; l o2min1 ) and carbon dioxide production ( vco2 ; l co2min1 ; trueone2400 metabolic measurement system , parvomedics inc . , sandy , ut ) .
participants wore a chest hr transmitter ( 2-lead ecg ; polar electro , kempele , finland ) and wristwatch monitor ( polar model rs810 ) capable of measuring the time interval between successive heart beats as denoted by cardiac cycle r - waves ( i.e. , r - r interval ) .
participants completed a traditional continuous cycle exercise test during which intensity was increased by 20 watts ( w ) every minute starting at 60 w and continuing until volitional fatigue ( e.g. , ~400 w for males and ~300 w for female cyclists ) .
this session provided data to 1 ) determine of the cardiorespiratory fitness of each participant ( i.e. , vo2peak ) , 2 ) determine participants individual vt using ve versus w ( i.e. , vet1w ) , and 3 ) establish the intensities for the subsequent discontinuous cycle test exercise stages .
individual s ve data were plotted versus w for each stage to determine vt by computer linear regression to establish vet1w ( 20 ) .
the same instrumentation described above , participants performed a series of seven stages of exercise lasting 6 min each with 3 min of rest between each stage .
one stage was then performed at vet1w ( i.e. , at at ) followed by three stages above vet1w ( i.e. , above at ) .
for example , with vet1w considered as 100% , stage 1 w were 40% of vet1w , stage 2 w were 60% of vet1w and stage 3 w were 80% of vet1w .
for the stages above at , 10% increases in intensity were used from vet1w ( i.e. , stages 5 , 6 , and 7 were 110 , 120 , and 130% of vet1w , respectively ) .
exercise ve , hr , and cardiac interbeat intervals were recorded during the last 3 min of each stage .
hr and interbeat interval data were downloaded to a computer for off - line analysis with kubios hrv analysis software ( biosignal analysis and medical imaging group ; department of physics , university of kuopio , finland ) . averaged
for hrv metrics , the following time - domain data were assessed : mean rr interval ( mrr ) , standard deviation rr interval ( stdrr ) , and root mean square standard deviation ( rmssd ) .
additionally , the following frequency - domain results were analyzed : low frequency spectral energy ( lf ; 0.0140.15 hz ) , high frequency spectral energy ( hf ; 0.150.4 hz ) , hf frequency peak ( fhf ; ms2 ) , and hffhf ( hzms2 ) .
the averaged stage data for ve , hr , and each time- and frequency - domain hrv metric were plotted versus w ( microsoft office excel 2007 , microsoft corporation ) .
for each parameter , two trend lines with corresponding slope - intercept ( i.e. , y = mx+b ) formulas were established for the stage data using microsoft excel ( microsoft corporation ) .
one trend line was established for data points from stages known to be below and at at , as reflected by vet1w , while the other trend line was established for data points collected at stages corresponding to at and above .
the intersection point of the two lines was then determined using y = ax+b and y = cx+d followed by x=(db)(ac)1 .
the w corresponding to the intersection of these trend lines was considered to represent each metric s  threshold  .
no relationships were discernible for stdrr or rmssd data versus w so these parameters were not evaluated further .
once parameters thresholds were identified , they were compared to the w corresponding to the discontinuous cycle test vt ( i.e. , vet2w ) using pearson ( two - tailed ) and paired - sample t - test ( ibm spss statistic , version 19 ; ibm company ) .
using a student t - based algorithm with an alpha = 0.05 , and beta ( power level ) = 80% , a power analysis was run to determine the minimum number of subjects required for our comparison .
it was determined based on available pilot data for at ( n=100 , sd=20 ) , that 15 subjects were needed to detect a 5 w difference in w at at .
experienced cyclists , age 1835 y , were recruited for this study , with eight female and seven male participants subjected to the protocols described below . for this study ,
the term  experienced cyclist  was defined as an individual self - reporting moderate intensity cycling an average of three times per week .
this study was approved by the institutional review board for the protection of human subjects in research of the university of texas at san antonio .
written informed consent was obtained from all participants following a verbal and written briefing of all experimental procedures .
participants were asked to abstain from stimulants , including caffeine , exercise , and alcohol 12 h before the cycling sessions .
participants reported to the laboratory in the morning after an 8 h fasting condition on two sessions .
the height and weight of the participants was recorded and their body composition was assessed using 7-site skinfolds ( 1 ) .
four frame measurements were taken on each participant s bicycle were matched on a lode excalibur ( lode b.v . , groningen , netherlands ) cycle ergometer to reproduce the participants training position .
participants performed all testing in their usual training attire and used their own cycle pedals and shoes .
all procedures were performed in a thermoneutral environment under close supervision of laboratory assistants familiar with the testing protocol and data collection . following measurement of shoeless height and body mass ,
participants were outfitted with a breathing mask allowing for inhalation of room air and analysis of expired air for ventilation ( ve ; l airmin1 ) , oxygen consumption ( vo2 ; l o2min1 ) and carbon dioxide production ( vco2 ; l co2min1 ; trueone2400 metabolic measurement system , parvomedics inc . , sandy , ut ) .
participants wore a chest hr transmitter ( 2-lead ecg ; polar electro , kempele , finland ) and wristwatch monitor ( polar model rs810 ) capable of measuring the time interval between successive heart beats as denoted by cardiac cycle r - waves ( i.e. , r - r interval ) .
participants completed a traditional continuous cycle exercise test during which intensity was increased by 20 watts ( w ) every minute starting at 60 w and continuing until volitional fatigue ( e.g. , ~400 w for males and ~300 w for female cyclists ) .
this session provided data to 1 ) determine of the cardiorespiratory fitness of each participant ( i.e. , vo2peak ) , 2 ) determine participants individual vt using ve versus w ( i.e. , vet1w ) , and 3 ) establish the intensities for the subsequent discontinuous cycle test exercise stages .
individual s ve data were plotted versus w for each stage to determine vt by computer linear regression to establish vet1w ( 20 ) .
following the same instrumentation described above , participants performed a series of seven stages of exercise lasting 6 min each with 3 min of rest between each stage .
one stage was then performed at vet1w ( i.e. , at at ) followed by three stages above vet1w ( i.e. , above at ) .
for example , with vet1w considered as 100% , stage 1 w were 40% of vet1w , stage 2 w were 60% of vet1w and stage 3 w were 80% of vet1w . for the stages above at , 10% increases in intensity were used from vet1w ( i.e. , stages 5 , 6 , and 7 were 110 , 120 , and 130% of vet1w , respectively ) .
exercise ve , hr , and cardiac interbeat intervals were recorded during the last 3 min of each stage .
hr and interbeat interval data were downloaded to a computer for off - line analysis with kubios hrv analysis software ( biosignal analysis and medical imaging group ; department of physics , university of kuopio , finland ) . averaged
for hrv metrics , the following time - domain data were assessed : mean rr interval ( mrr ) , standard deviation rr interval ( stdrr ) , and root mean square standard deviation ( rmssd ) .
additionally , the following frequency - domain results were analyzed : low frequency spectral energy ( lf ; 0.0140.15 hz ) , high frequency spectral energy ( hf ; 0.150.4 hz ) , hf frequency peak ( fhf ; ms2 ) , and hffhf ( hzms2 ) .
the averaged stage data for ve , hr , and each time- and frequency - domain hrv metric were plotted versus w ( microsoft office excel 2007 , microsoft corporation ) . for each parameter , two trend lines with corresponding slope - intercept ( i.e. , y = mx+b ) formulas were established for the stage data using microsoft excel ( microsoft corporation ) .
one trend line was established for data points from stages known to be below and at at , as reflected by vet1w , while the other trend line was established for data points collected at stages corresponding to at and above .
the intersection point of the two lines was then determined using y = ax+b and y = cx+d followed by x=(db)(ac)1 .
the w corresponding to the intersection of these trend lines was considered to represent each metric s  threshold  .
no relationships were discernible for stdrr or rmssd data versus w so these parameters were not evaluated further .
once parameters thresholds were identified , they were compared to the w corresponding to the discontinuous cycle test vt ( i.e. , vet2w ) using pearson ( two - tailed ) and paired - sample t - test ( ibm spss statistic , version 19 ; ibm company ) .
participants average age , height , body mass , body mass index ( bmi ) , vet1w , and vo2peak are provided in table 1 .
normal  while the vo2peak data is consistent with that of ~80th percentile for 2040 year olds by the american college of sports medicine ( 1 ) .
the average observed w corresponding to vt during the continuous cycle test ( vet1w ) and the discontinuous cycle test ( vet2w ) were normally distributed ( shapiro - wilk=0.931 , df=15 , p>0.05 ) highly correlated ( r=0.97 ; p=0.000 ) , with individual participants vet1w and vet2w varying by less than 3 w ( p>0.05 ) .
participants individual vet2w were used in the comparison of hr and hrv metrics threshold w. the w corresponding to the intersection of trend lines established for hr , mrr , lf , hf , fhf , hffhf data were considered to represent each metric s  threshold 
( i.e. , hrtw , mrrtw , lftw , hftw , fhftw , and hffhftw , respectively ) ( figure 1 ) .
discernible linear relationships between the hrv metric data and w were not observed for all participants .
namely , hrtw was not established for one female subject , mrrtw was not established for two male subjects and one female subject , hftw and fhftw were each not established for a male subject .
when a hr or hrv metric threshold could not be established , the subject s data , including vet2w , were not included in the subsequent statistical analyses .
comparisons of the established hr and hrv metric threshold w and the corresponding vet2w are presented in table 2 .
statistically significant correlations ( p0.05 ) were observed between all hr and hrv metric threshold w and vet2w when participants data were compared .
significant statistical differences ( p<0.05 ) were not observed for vet2w and hrtw ( 2.0  13.4w difference ) , mrrtw ( 10.0  26.4w difference ) , hftw ( 7.3  19.0w difference ) , and hffhftw ( 2.4  23.1w difference ) .
however , the 11.3  17.8w difference for lftw and 13.9  18.7w difference for fhftw were statistically significant ( p=0.028 and p=0.015 , respectively ) .
we have demonstrated that the power output at at can be determined using hrt and several hrv metric thresholds from a discontinuous , incremental cycling protocol . in the present study , thresholds for hrt and the related mrr correlated significantly with w at at as determined by vt .
the inherent fluctuation of autonomic balance makes it difficult to determine if physiologic data collected early in a given exercise stage will reflect the body s definitive response .
hrt and hrv threshold investigations in cycling have utilized continuous , incremental exercise protocols consisting of 12 min stages . therefore , threshold determination using blood lactate , ve , vo2 , hr , or hrv metrics may not be optimally applicable for training or competition wattage prescription in the field .
for example , the hrt , or oft - termed  heart rate deflection point 
( hrdp ) , was identified in cyclists by bourgois and colleagues ( 7 ) using a continuous cycle test . a subsequent 30 min test at hrdp w
only 6 of 11 subjects were able to complete the 30 min with 5 subjects demonstrating accumulating blood lactate values .
these findings are indicative of the hrdp w , as determined by a continuous test , over - predicting the subsequent work rate leading to premature fatigue .
such an at over - prediction was also observed in a large cycle study by carey et al .
the agreement between time trial performance and data collected during protocols using multiple , longer stages ( e.g. , 3 min ) of exercise has also been demonstrated by bentley dj & mcnaughton lr ( 4 ) . when considering that typical endurance ( i.e. , at ) cycle training rides or races last far longer than 30 min , the potential performance impact of an over - prediction of at using continuous protocol - derived w from hrt is clear .
together , the findings above suggest that at data derived from a discontinuous protocol stages that are long enough to establish  steady - state  may be more appropriate for exercise prescription
. accurate representation of the initial , sub - at , linear relationship between intensity and ve , hr , and hrv metrics is paramount to subsequent identification of the nonlinear deflection in the data collected at intensities above at .
the data from the present study were collected during the last 3 min of cycling at each 6 min exercise intensity stage .
furthermore , several minutes of rest between each stage ensures that no lingering effects from an earlier stage the physiological response to a subsequent workrate .
therefore , data from the sub - at intensity stages can be considered as steady - state conditions and reflective of the appropriate response level of the fast - responding physiological metrics of interest . the highest observed absolute difference in vet2w and
the hrtw and hrv metrics w was > 16 w with several comparisons differing by as little as 2 w. this range is notable as bicycles used for endurance training and competition commonly will change by ~20 w per sprocket / gear shift at the same cadence .
a low degree of error of the appropriate sub - at power output determined in the laboratory to the field allows cyclists to determine the optimal sprocket and cadence combination to suit their performance .
we are not aware of any study reporting comparisons between hrv and ve thresholds using a discontinuous exercise protocol .
several studies have focused on evaluation of hrv changes near at using continuous protocols ( 2 , 10 , 11 , 13 , 18 ) .
spectral analysis of hrv has proven useful in these investigations because cardiorespiratory parameters temporal series , namely hr and ve , fluctuate dramatically during load increases . observed changes in the increment of increase in the hf domain ( > 0.15 hz )
the hf parameter reflects the amplitude of the sinus arrhythmia ( rsa ) and vagal tone .
high frequency increases in vagal tone above the intrinsic sinus depolarization rate ( i.e. , ~100bpm ) is perhaps a response to venous return - mediated stretch of the right atrium and sinus node .
thresholds identified in the present study using hf hrv metrics ( i.e. , hftw , fhftw , hffhftw ) all correlated with vet2w .
spectral lf variations in r - r intervals reflect changes in both sns and psns activity ( 19 ) .
this finding was somewhat surprising from a physiological perspective as the overall psns influence is minimal above low intensity exercise ( hr > 100 bpm ) .
in such , changes in lf above at would be influenced predominantly by sns , possibly decreasing the predictive potential of lf for atw .
additionally , other , non - neural factors such asepinephrine or respiratory pump on hr increase with intensity which may play a role as well , which could impact the reliability of the lf parameter to predict at .
there are a few key limitations to our generalizing our findings to all adult cyclists .
whether or not the findings would apply across a wider range of experience levels or age groups is not known . secondly
, discernible relationships between the hrv metric data and w were not observed for all participants .
namely , hrtw was not established for one female subject , mrrtw was not established for two male subjects and one female subject , hftw was not established for one male subject , and fhftw was not established for one male subject .
when a hr or hrv metric threshold could not be established , the subject s data , including vet2w , were not included in the statistical analyses .
furthermore , the inability of identifying a threshold in 30% of participants has important implications for the consistency of these metrics in the field .
the low number of participants makes extrapolation of the findings to similar populations difficult at best .
further studies are needed to ascertain if failure to identify a threshold results from the protocol , data collection techniques , or participants individual differences .
at is the best predictor of performance in endurance activities such as cycling and running ( reviewed in 12 ) .
knowing the w associated with at is especially relevant when cyclists want to maintain a given % of at for extended periods of time .
cycling at or just under at allows for sustained performance without premature fatigue due to effects of lactic acid .
using a hrv metric threshold would allow detection of changes in ans balance ( cardiac drift , dehydration , fatigue , metabolic status , etc . ) preceding premature fatigue .
in such a case , appropriate adjustments to power output could be made to avoid performance detriments .
future studies will need to compare the hrtws from continuous and discontinuous protocols to maximal lactate steady state ( mlss ) during a prolonged performance test .
this will have further relevance to the field as mlss and mlss velocity are highly correlated with prolonged endurance performance in cyclists ( 3 , 12 ) .
 the purpose was to determine if heart rate ( hr ) and heart rate variability ( hrv ) responses would reflect anaerobic threshold ( at ) using a discontinuous , incremental , cycle test . 
 at was determined by ventilatory threshold ( vt ) . 
 cyclists ( 30.65.9y ; 7 males , 8 females ) completed a discontinuous cycle test consisting of 7 stages ( 6 min each with 3 min of rest between ) . 
 three stages were performed at power outputs ( w ) below those corresponding to a previously established at , one at w corresponding to at , and 3 at w above those corresponding to at . 
 the w at the intersection of the trend lines was considered each metric s  threshold  . 
 the averaged stage data for ve , hr , and time- and frequency - domain hrv metrics were plotted versus w. the w at the  threshold  for the metrics of interest were compared using correlation analysis and paired - sample t - test . in all , several heart rate - related parameters accurately reflected at with significant correlations ( p0.05 ) were observed between at w and hr , mean rr interval ( mrr ) , low and high frequency spectral energy ( lf and hr , respectively ) , high frequency peak ( fhf ) , and hfxfhf metrics threshold w ( i.e. , mrrtw , etc . ) . 
 differences in hr or hrv metric threshold w and at for all subjects were less than 14 w. the steady state data from discontinuous protocols may allow for a true indication of steady - state physiologic stress responses and corresponding w at at , compared to continuous protocols using 12 min exercise stages . 
INTRODUCTION
METHODS
Participants
Protocol
Statistical Analysis
RESULTS
DISCUSSION