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Tuesday, July 13, 2010

How to determine your lactate threshold

What is "Lactate Threshold"?

Lactate threshold (LT) has many names; it is also known as "threshold", anaerobic threshold (AT), maximal lactate steady state (MLSS), or onset of blood threshold (OBLA).  It is the point at which one's body begins to accumulate more lactate acid than it can process/metabolize or expel  during a progressive intensity of exercise.  While in a laboratory setting, LT is measured in terms of the percent of lactic acid in your blood, a good surrogate can be found using your power output (wattage) and/or heart rate (beats per minute or bpm).  This leads us to another term that is commonly used to describe LT in a practical way:  functional threshold power or FTP.  This is the most common term presently used by many cycling coaches to measure, describe and represent what most cyclists are really  concerned with - what maximal power output (or related functional threshold heart rate (FTHR)) can they sustain for an endurance event to produce maximal performance.  Wherever I refer to LT below, for the purposes of this article, any of the terms above (LT, LTP, FTHR, AT, MLSS, OBLA.) can be used interchangeably because they all are measurements of your performance threshold. 

LT is related to the build-up of lactic acid during exercise - along with other biochemical events that occur in the muscle -  that serves as a fatigue marker.  Physical efforts above LT progressively lead to a reduction and eventual shutdown of your ability to further physically exert yourself, whereas efforts below LT can be generally maintained for considerably long periods (from one to several hours).

The Importance of Knowing Your Lactate Threshold

You may ask yourself, "Why would I want to know my lactate threshold?"  If you are a recreational rider, knowing your LT may be of no more value than knowing your IQ score. However, if you are a competitive cyclist and/or you are following a comprehensive training program, it would be extremely valuable to know where your LT lands on the heart rate and power charts.  A higher lactate threshold will allow you to work harder and/or longer before you fatigue.  For longer time trials, you can monitor your heart rate and or power, and maximize your performance by adjusting your speed by cadence and gear selection in order to stay at your known threshold (wattage and/or heart rate).  The strongest/fittest rider who rides at their LT will almost always win a time trial. For criteriums and road races, while race strategy is key, building fitness by raising your lactate threshold can mean the difference between staying with the pack, or being dropped off the back.
If you don’t know your threshold, it’s difficult to know if you are optimizing your training.  Knowing your LT or FTP and periodically measuring it is extremely important for making sure your training program is effective in terms of improving your endurance.  In addition, when you accumulate this data over time, you can analyze it to determine any changes in your conditioning.

How to Determine Your Lactate Threshold

Below are four methods for determining your LT or FTP.  In order to get the best results you should not be fatigued (at least 3 days from last interval session), you should be well hydrated and you should be prepared nutritionally (eat properly and timely).

Method 1:  Exercise Laboratory

One way to determine your lactate threshold is in a laboratory setting, where blood samples can be drawn during exercise to determine LT and correlated  to a heart rate and wattage output.  This method is complicated and the results are dependent on the physiologist/laboratory technician's design protocols and interpretation of data.   Additionally,  most people don't have access to a laboratory for testing.  However, you are in luck - there are a few simple, cost-effective alternatives to estimate your LT.

Method 2:  The 40 kilometer Time Trial

This method requires a long, flatish course (extremely hilly courses are not suitable), and either a heart rate monitor and/or a watt meter.   In my experience, riding  a 40 kilometer, flat time trial is close to ideal for this.  First, it is long enough so that you simply can not stay above your LT without dropping back down to recover and ride at your actual threshold.   This allows averaging to give a more accurate number. Secondly, the 40 kilometer timetrial is typically the standard for most state and national championships. Third, I find that this distance is long enough to be a complete workout in itself.

Warm up appropriately.   Ride easy for 20-30 minutes, then follow this with a few efforts at or just below your expected time trial effort.  This isn't hard science.  You can do 4 leg openers. These should last about 3 minutes each. Over the first minute, gradually bring yourself up to a pace that you believe you can sustain for your time trial. Hold it there for one or two minutes and over the last minute bring your effort back down to an easy/moderate pace. Recover 5 minutes and repeat. Your effort should be just hard enough to get your heart rate up and a sweat going, but not tax your system or require any significant recovery time.  Or you can do two 5-minute efforts with five minute recovery between and just before starting the actual time trial.

Make sure you 'zero' your watt meter before starting,  then do your best effort.  Later you can upload the power data and use your preferred power software to see your average wattage and heart rate. 

If you only have a heart rate monitor, it must have the ability to download the data.  There is too much change and variation over a 40 kilometer effort to accurately estimate the average heart rate from memory. 

Heart rate data is valuable information and it generally tracks linearly in relation to effort and aerobic efficiency.  However, it isn't instantaneously responsive to exercise stimuli and doesn't have the same amount of predictability and reliability that power meters do or laboratory gas analyzers.  Heart rate tends to elevate with temperature, dehydration, certain medications, caffeine, decreased fitness, and is also effected by the time of last meal, illness, heat adaption, and current fitness level as well as having a delayed response to exercise stimuli.  With that understood and accounted for, heart rate data becomes more meaningful as I will describe later.

Method 3:  25-minute time trial

An alternative to the 40k method is to use a static time rather than distance; this method also requires the use of a power meter attached to your bicycle and/or a heart-rate monitor that can record and transfer data.

Begin by warming up as described earlier in this article, then ride a 25 minute flat time trial course at your maximum controlled effort.   Record the last twenty minutes of the ride on either your heart-rate monitor or power meter.  To estimate your LT point, subtract 5% from the average power and/or heart rate data during this period.

Method 4:  The Conconi Test

A fourth way to estimate your LT is the Conconi Test.  This method requires the use of a power meter attached to your bicycle and a heart-rate monitor.  Alternatively, you may be able to use a stationary trainer that is appropriately outfitted.  The premise of this test is that below you LT, there is a linear relationship between wattage and heart rate.  After reaching LT, this relationship begins to flatten when graphed.  If you incrementally increase wattage over time and plot this against the resulting change in heart rate on  X and Y axes, respectively, you will observe a point where it is no longer linear.  That point of deflection is your LT.

Example of the Conconi Test  

In 1995, I recorded data for a Conconi test at my University gym using a simple polar heart-rate monitor and a stationary trainer with digital watt resistance.  I  increased my effort by 25 watts every minute. and wrote down my heart rate just after increasing the wattage (the machine maxed out at 400 watts).  My data is charted below (Figure 1):

Figure 1:  1995 Conconi Test

Based on this chart, my predicted lactate threshold occurred at a heart rate of 169 bpm and at a power output of 325 watts (not bad for a Category a 4 rider... upgrading soon followed). To see predicted power outputs for different categories of racers - ranging all the way from untrained cyclists all the way to world class cyclists - see my article on the "Comparative Measurements of Maximal Outputs for Cyclists".

There is some criticism that the Conconi Test only works with certain fit athletes, for whom LT is close to their maximum heart rate.  Here are links (1 and 2 ) to two studies suggesting that Conconi's test simply isn't a good method to predict LT.  There are studies that say the opposite as well.

To achieve an accurate Conconi test result, it is very important to note that several rules must be followed:
     1. be rested (fatigue affects heart rate);
     2. you should eat in a manor appropriate with racing (meal 3-4 hours previous to test);
     3. you should perform the test in a temperate environment and or use cooling fans (rising core-      temperature can create upward heart rate drift);
     4. You should not consume caffeine within a few hours of testing (also raises hr) or it should be mitigated by consuming the same amount of caffeine at the same time frame before testing for all tests and all future performances;
     5. You should be hydrated (dehydration causes elevated hr).

I would also suggest that you thoroughly warm-up prior to the test, to account for any heart rate drift that will occur as your core temperature rises from exercise.  I would also suggest that each new wattage be maintained for  2-minutes before changing to a new wattage to allow your heart rate to stabilize at a fixed effort (there's a delay in heart rate response to increased wattage).    While this will tend to prevent an athlete from going much higher than threshold, the purpose of this test is only for estimating LT and not VO2max.  Any additional wattage/load added over LT will hopefully cause the heart rate to drift right off the previous trend of a linear relationship between wattage and heart rate.

Below (Figure 2) is  data from a more recent Conconi Test, using my road bike on a stationary trainer.  It illustrates the strong correlation between exertion and heart rate.  However, because I broke a few of the above rules, (such as being not rested, and I had consumed caffeine proximal to the test), it also demonstrates how these factors can render the Conconi test inconclusive. 

Note-worthy is that the slope of the plot line is almost identical to the slope of my chart 15 years previous.  This should be true for most athletic individuals.  As a person improves their conditioning  the line shifts to the right (more wattage at the same heart rate).  A very unfit person will have a relatively steep slope when compared to a later slope after some gain some fitness.  Further fitness typically shows a shift of the slope to the right.  You can compare Conconi tests from different periods and see fitness changes at a glance when layed on top of each other.

Figure 2:  2010 Conconi Test

I the graph in Figure 2 (above) from the data above from my SRM software which I downloaded from my watt meter device, shown below in Figure 3.
Figure 3:  2010 Wattage data Conconi test using SRM

The vertical lines represent one-minute increments.  Wattage is graphed in green and heart rate is the brown stair-stepping line.  It is worth noting that the wattage has some up and down movement  (+/- 5 watts).  In my defense, it is hard to ride at an exact specific wattage for any length of time.  This is another reason that I suggest 2-minute intervals rather than one minute intervals, to allow heart rate stabilization to each new work load.  Additionally, my watt monitor displayed 3 cadence smoothing ( it displayed wattage as an average of 3 rotations of the crank)  which made my wattage appear much more steady while riding than is shown in Figure 3.  

Note:  The Conconi test works best if you can maintain a consistent cadence throughout all the tests. Cadence can affect heartrate as a function of performance efficiency.    In my test shown in Figure 3 (above), I was able to maintain a cadence of 87 to 93 rpm throughout the test except at the end with wattages of 385 and 400, where I had to increase my cadence to 98 and 100 rpm accordingly.  This may have negatively affected this Conconi test because heart rate does tend to rise with performance inefficiencies.   From careful evaluation I have determined that I am slightly more efficient with a cadence in the low 80s when riding at my threshold.   This can be done by riding at your functional threshold power (wattage at LT) at different cadences (70, 80, 90, 100rpm) for several minutes each with a 4 minute recovery period between and noting which cadence produced the lowest heart rate.   If you would like to learn more details about what the ideal cadence is for competitive cyclists please click here and read my post on this subject.

Figure 4: SRM Conconi analysis
The final chart (Figure 4) is also from my SRM software.  I have included it because it is rather interesting.  The squiggly line is the exact same data as Figure 3, only graphed in a continuous line on an X and Y axis, starting with yellow and changing to brown, green, aqua, blue, and finally ending in purple.  The only significance of the color change is help see the data change over time during the test.   SRM's  Conconi analysis view does not run the test for you, only the data analysis.

I think it is amusing that SRM appears to think that the Conconi test is worthy enough to include it in their software.

Please check back in another 15 years for another watt/heartrate chart update.   I predict a shift back to the left.  

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  1. Howdy! I can clearly notice that you really get the sense of what you are writing about here. Do you own a degree or an education which is associated with the subject of your entry? Can't wait to hear from you.

    1. I started studying medical technology at the University of Missouri and finished with a degree in psychology. So I have some basic knowledge in physiology, biology, chemistry, research methods I & II, statistics etc.

      Plus I had a deep interest in the science of cycling, and as a result I've read a lot on the topic.

      I'm definitely not an expert, but I hope any of errors are pointed out for correction.


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