I wrote an initial post on this subject a few months ago and have continued using the analysis protocol described therein. This protocol uses a metric derived from the measured training effect (as calculated by the Firstbeat algorithm included in the Garmin 610 (and 910) watches) by multiplying by the training session duration in minutes. Herein this metric is referred to as intensity-minutes. This metric is very valuable as it quantitatively captures the effort expended during the training session. The nice part of this approach is that the watch can reliably record and calculate the training effect without potential mis-perception of your perceived effort. Of course you must ensure that the basis data (your heart rate zones) that you provide to the Firstbeat algorithm is accurate. I continue to find both the calculated training effect and the intensity minutes to be an accurate description of the training sessions.
In the meantime I have done a bit more reading to justify the multiplicative functionality of the the two inputs (training effect and session time) and found support for this from a physiological basis (in Dr. T Noakes treatise, The Lore of Running). In addition, I recently came upon a fully developed literature on the use of this very same metric for use in training for endurance (and other) athletes.
TRIMP (Training Impuse)
It was surprising to discover that the approach that I naively developed, i.e the use of “intensity minutes” (training effect times duration of session) as a fundamental metric of a training session, was first proposed in 1975 (1) and has been in use in numerous forms ever since. The authors refer to the metric as Training Impulse, or TRIMP. This method appears to be quite robust and is best illustrated by a recent study (2) of three elite marathon runners leading up to the London Olympics where TRIMP is used as a basic training monitoring tool. A review and commentary of the data in this study is here.
The aforementioned recent study used a perceived effort scale called the Borg Scale:6 No exertion at all 7
7.5 Extremely light
8 9 Very light 10 11 Light 12 13 Somewhat hard 14 15 Hard (heavy) 16 17 Very hard 18 19 Extremely hard 20 Maximal exertion
Although a reasonably divided scale, with the Borg Scale I would find it difficult to be repeatable and reliable with the various sorts of training sessions I partake in. I have found that a primary issue with the perceived effort approach in capturing training effect is that it is not generally a reliable indicator of actual effort. In contrast, upon analysis of the time series heart rate data as compared to the calculated training effect, I have found the Firstbeat firmware to be quite accurate, even at short (ca. 3 minute) duration. Given that the calculation is a direct output of every training session, it is convenient as well. In addition, since the Firstbeat training effect scale ranges from 1.0 to 5.0, this allows for 40 levels of calculated effort, a much finer scale than the Borg Scale.
Given the issues associated with structured training sessions (e.g. intervals, fartlek, etc.) and the common use of average HR for estimations of perceived effort, other approaches have been developed to overcome shortcomings and they are nicely summarized in the following three articles/posts:
With respect to using the training effect calculation provided by the Garmin 610 via the Firstbeat firmware embedded in the watch, I have found that I can accurately capture the true effort expended in short (3-10 minute) intervals by saving each interval as a separate event. This way each part of the interval workout (w/u, individual intervals, and c/d) can be separately recorded and TRIMP values (or “intensity minute” values) can be calculated individually. These calculations are then just additive for the total “intensity minutes” of the training session. Given that the Firstbeat firmware is also analyzing HR recovery rate (in addition to time series HR and duration), i.e. a direct measurement of the training load on your system, the calculated TE, in my experience, is very sensitive to the transient and cumulative training load. For instance I have found in interval sessions of 5 X 7 minute hill repeats (both in running and in Nordic skiing) that the calculated TE for each of the 5 repeats shows typically as follows: e.g. TE= 4.8, 4.7, 5.0, 5.0, 5.0. As you can see the first two repeats are typically slightly low but as I work into the sessions the desired maximal effect is evident. I have found such accurate measures at interval segment times as short as 3 minutes.
As far as specific strength sessions with weights, I find the calculated TE is a bit low based on my perceived effort, but this actually may be accurate as outlined above, as perceived effort can be an unreliable measure- i.e. a workout may seem hard but is analytically not. I prefer specific strength sessions that replicate the actual whole body motion of the particular sport, for instance e.g. double pole rollerski sessions for nordic skiing or hill repeats for running. I find that such whole body motions are much more focused on correctly developing the correct muscle systems for the activity. The TE value can then be reliably derived from the watch algorithm.
Training Analysis Update
Since I last posted on this subject in mid-May 2012, I have attempted to use the intensity minute metric to plan and monitor a structured training program over the past five months. This period also included two ultramarathon races (53 km/7,000 vert and 70 km/11,200 vert) and preparation for a third ultramarathon (84 km/9,600 vert) which I did not do due to fires and the associated smoke at the race site.
What seems to be working for my monitoring purposes is time series graphs of 7-day total, 7-day average, and daily measures of :
- intensity minutes
- vertical ascention
Plotted below is the intensity minute data:
These data include only the running sessions. During this period I am also doing ski-specific sessions which are primarily double pole roller skiing for an average of about 3-6 hours per week.
The training structure is fairly obvious, but here is a narrative:
- from mid-April to mid-May- developing base aerobic training with a couple of progressions and a bout of Achilles tendonitis
- a build up to about 17 June for a 53km race with about 7,000 feet of vertical on 23 June
- a week of taper and then the race
- a recovery period (about 3 days)
- another build up to about 7 July for a 70 km race with about 11,000 feet of vertical on 14 July
- a week of taper and then the race
- a recovery period (about 2 days) and about 2 weeks of lower volume
- a third build up to about 11 August for a 84 km race with about 10,000 feet of vertical on 1 September which was truncated because I decided not to do the race due to fires and associated smoke
- a volume block from about 20 August until about 5 October
- a recovery period of about 7 days
- transition to ski-specific training (some running but more roller skiing and hill bounding)
As far as the effectiveness of this training periodization, I placed in the top ten overall (5th and 9th) in each race. A better evaluation is that in each race a nationally ranked runner participated (and won) so I can calibrate my performance on a more national level. I was within 20% of the winning time in both races, which, given that these are my first two ultramarathon races, that I have been training for ultramarathons since April 2012, and that I am old (56) it would seem that the training protocol is at least passable. I have a lot of skill development and lateral muscle building to do, but this is a good start. My only thought is that I would add more long (20+ miles) runs into the program. You can see that I have started to do this. Time will tell if it will have any positive effect; I expect that more longer runs will help with having a strong finish. I also need to concentrate on the climbing as I was in the early part of this training period.
Plotted below are the vertical ascention, distance, and time data for the same period:
I have found that the Firstbeat training effect calculation that is embedded in the firmware of the Garmin 610 (and 910) watch is reliable and very useful from training monitoring and training periodization perspectives. So long as one takes the time to accurately determine their heart rate zones, the calculation has been very consistent and in agreement with expected perceived effort.
Further review of the literature has validated the use of the “intensity-minute” metric (or TRIMP, as accepted by professionals in the field) as presented here. Some care needs to be taken to properly capture all aspects of structured training sessions, particularly interval sessions. But with intelligent application and diligent recording of the data, a periodized training plan can be based on “intensity minutes” and reliably executed upon. In addition, appropriate modifications can be made within a given training period based on the intensity minute data to allow one to get the most out of their training time commitment.
I highly recommend that consideration of this approach be a part of your training planning.
8 Feb 2013 update: I have posted a complete analysis of my entire training year (both running and skiing seasons) utilizing the protocol described above here.
1. E. Banister et al., “A systems model of training for athletic performance”, Australian Journal of Sports Medicine, 7:57-61, 1975.
2. T. Stellingwerff, “Case study: nutrition and training periodization in three elite marathon runners”, International Jouranl of Sports Nutrition and Exercise Metabolism, 5:392-400 (2012).