Category: training

>Microsoft gives Kinect starter kit for academic research


This is excellent news. Now scientist will be able to access a software development kit to develop innovative solutions for using Microsoft Kinect a new gaming device developed by Microsoft.

What is special about Kinect? Kinect allows a controller-free gaming. Which means full body play. Kinect responds to how you move as it is a motion sensing, optical device.

If you have never seen one, have a look at the video.


I predict a large number of new applications developed for sports and rehabilitation!

Monitoring training load: Quo vadis? #3

The first two posts dealt with inexpensive and more expensive methods. I will now discuss the use of psychometric tools to get another dimension of monitoring training loads. I have not discussed the use of GPS or similar technologies, but will cover this in the next post.

I really want to present some info on various tools currently used and discuss pros and cons of them.

Profile of Mood States (POMS)

The Profile of Mood States (POMS) is a psychological rating scale used to assess transient, distinct mood states. The original scale, developed by McNair et al, has 65 items describing feelings people have.  There is a brief version,  comprising 11 of the original POMS items, developed by Cella et al, in 1987.  However, this version (Brief POMS) provides only one score for overall psychological distress.  There is yet another version called the short form of the Profile of Mood States (POMS-SF) developed by Shacham in 1983.  The short form version contains 37 items, selected from the original POMS.  It retains the six subscale information provided by POMS. The POM–Bipolar is the newest addition to the POMS. It measures moods and feelings primarily in clinical rather than nonclinical settings. It can help to determine an individual’s psychiatric status for therapy, or be used to compare mood profiles associated with various personality disorders. In nonclinical settings, the POMS–Bipolar can assess mood changes produced by techniques such as psychotherapy or meditation.

Here it is possible to download a POMS scale.

This scale has been used in a variety of populations with more than 2000 studies being performed using it. However there is a paucity of data on athletes and its links to other measures of overtraining and overreaching.

The POMS assessments are self-report inventories in which respondents rate a series of mood states (such as "Untroubled" or "Sorry for things done") based on how well each item describes the respondent’s mood during one of three time frames (i.e., during the past week, including today; right now; other). Normative data are based on the "during the past week, including today" time frame. The POMS Standard form contains 65 items and takes approximately 10 minutes to complete. The respondent rates each item on a 5-point scale ranging from “Not at all” to “Extremely”. The POMS Brief form, which is ideal for use with patients for whom ordinary tasks can be difficult and time-consuming, uses the same scale as the POMS Standard form, but contains only 30 items. It takes only 5 minutes to complete. Both the POMS Standard and POMS

Brief assessments measure six identified mood factors:

• Tension-Anxiety
• Depression-Dejection
• Anger-Hostility
• Vigor-Activity
• Fatigue-Inertia
• Confusion-Bewilderment

The POMS-Bi form contains 72 items and uses a 4-point scale. It takes approximately 10 minutes to complete. Responses for the POMS-Bi range from “Much unlike this” to “Much like this”. Unlike the other POMS assessments, the POMS-Bi measures both positive and negative affects. For each of the six bipolar scales, one pole represents the positive aspects of the dimension while the other pole refers to the negative aspects:

• Composed-Anxious
• Agreeable-Hostile
• Elated-Depressed
• Confident-Unsure
• Energetic-Tired
• Clearheaded-Confused

Since 1971, numerous research studies have provided evidence for the predictive and construct validity of the POMS Standard and POMS Brief assessments. Alpha coefficient and other studies have found the POMS Standard and POMS Brief to exhibit a highly satisfactory level of internal consistency, while product moment correlations indicate a reasonable level of test-retest reliability. Factor analytic replications provide evidence of the factorial validity of the 6 mood factors, and an examination of the individual items defining each mood state supporting the content validity of the factor scores. Studies have also supported the bipolar nature of moods measured by the POMS-Bi assessment, and reliability studies have shown that POMS-Bi items demonstrate sufficient internal consistency.

One of the first encouraging studies by O’Connor et al. (1989) examined POMS scores and resting salivary cortisol levels in 14 female college swimmers during progressive increases and decreases in training volume, and were compared to the same measures in eight active college women who served as controls. Training volume increased from 2,000 yards/day in September (baseline) to a peak of 12,000 yards/day in January (overtraining), followed by a reduction in training (taper) to 4,500 yards/day by February. The swimmers experienced significant alterations in tension, depression, anger, vigor, fatigue and global mood across the training season compared to the controls. Salivary cortisol was significantly greater in the swimmers compared to the controls during baseline and overtraining, but was not different between the groups following the taper. Salivary cortisol was significantly correlated with depressed mood during overtraining (r = .50) but not at baseline or taper. Global mood, depression, and salivary cortisol were significantly higher during the overtraining phase in those swimmers classified as stale, compared to those swimmers who did not exhibit large performance decrements.

This was one of the initial studies suggesting a link between increasing training workloads, POMS scores and cortisol responses advocating the possibility of using this psychometric tool to understand how athletes were coping with training loads.

Urhausen et al. (1998) found that the parameters of mood state at rest as well as the subjective rating of perceived exertion during exercise were significantly impaired during overtraining in a follow up study with endurance athletes.

Filaire et al. (2001) used POMS together with endocrine markers to study soccer players and found that in such group decreased testosterone to cortisol ratio does not automatically lead to a decrease in team performance or a state of team overtraining. However, they suggested that combined psychological and physiological changes during high-intensity training are primarily of interest when monitoring training stress in relation to performance.

It seems therefore clear that POMS has the potential to be used to assess how athletes cope with training loads and POMS score can potentially have a link with hormonal  imbalances.

REST Q Questionnaire

The Recovery-Stress Questionnaire for Athletes [RESTQ-Sport] is a questionnaire reported to identify the extent to which athletes are physically or mentally stressed and their current perception of recovery (Kellmann & Kallus, 2000 and Kellmann & Kallus 2001). It has been used by many individuals and organizations throughout the world and can therefore be reasonably estimated to have been used on at least several thousand high-performance athletes as a diagnostic tool to detect under-recovery states and to plan recovery practices. The predecessor of this psychometric tool was a General Recovery-Stress Questionnaire (Kallus, 1995) formulated on the idea that people will respond differently to physiological and psychological demands depending on how well-rested they are when faced with these demands.

The RESTQ-Sport was constructed based on the notion that an athlete well recovered may perform better than one who is under-recovered. However, theoretical and practical concerns governed the methods used to determine the 19 subscales of the RESTQ-Sport (Kellmann & Kallus, 2000 and Kellmann & Kallus, 2001) used an a priori method of identifying each of the subscales, combining to form several scales that reflect various aspects of stress and recovery. The RESTQ-Sport was developed through research in the area of stress for the General Scale, and the Sport Scale was comprised of items observed to coincide with stress or recovery states in athletes (Kellmann & Kallus, 2001).

The test consists of 7 stress scales, and 5 recovery scales.

The scales are:

General stress
Emotional stress
Social stress
Lack of energy
Physical complaints
Social recovery
Physical recovery
General well-being
Sleep quality
Disturbed breaks
Burnout/emotional exhaustion
Fitness/being in shape
Burnout/personal accomplishment

If you are interested in knowing more about this test and have a software to score the results, I strongly suggest you buy Dr. Kellmann’s and Kallus’ book at Human Kinetics. The book also contains a software to score the questionnaire and provide you with a graph.

The graph normally looks like this one presented by James Marshall in his blog:

Figure 1

However, you can develop your own spreadsheet to score it and graph it as I did.


Many studies have shown how valid and reliable this test is. However one of the most interesting ones was published by Jurimae et al. (2004). They studied the effects of increasing training loads in competitive rowers and found significant relationships between training volume and Fatigue scores (r=0.49), Somatic Complaints (r=0.50} and Sleep Quality (r=-0.58) at the end of heavy training. In addition, significant relationships were also observed between cortisol and Fatigue scores (r=0.48) at the end of heavy training as well as between changes in cortisol and changes in Fatigue (r=0.57) and Social Stress (r=0.51).

It should be pointed out that this test cannot be performed every day as it asks the athlete about how often the respondent participated in various activities during the preceding three days/nights. A Likert-type scale is used with values ranging from 0 (never) to 6 (always) to rank the frequency of activities/experiences of the preceding 3 days/nights.

BORG scale and perception of effort

The concept of perceived exertion was introduced half a century ago and an operational definition presented with methods to measure different aspects of perceived effort, strain and fatigue. One very common method is the RPE-Scale for "Ratings of Perceived Exertion" ("the Borg Scale") officially known now as the "Borg RPE Scale®".

As Professor Borg explains: “Stevens’ "Ratio (R) scaling methods for determinations of S-R-functions have been improved in order not only to obtain relative functions but also direct ("absolute") levels of intensity. This was done by placing verbal anchors, from simple category (C) scales (rank order scales) such as "very weak", "moderate", "strong" etc at the best possible position on a ratio scale, a "CR-scale", covering the total subjective dynamic range, so that a congruence in meaning was obtained between the numbers and the anchors”.

If you are really interested in this you should read Dr. Elisabet Borg’s thesis here where she presents the innovative approach to develop the "Borg CR100 Scale®" (also called the "centiMax Scale"). I had the pleasure to listen to her lecture last year in Italy and I was impressed by the quality of work she has done to follow up her father’s intuitions on the original rate of perceived exertion.

You can read more about Dr. Elisabet Borg here and about Professor Gunnar Borg here.

Recommendations to use a "Borg Scale" is given by many professional societies, e.g. American Heart Association, American Thoracic Society, American College of Sports Medicine, British Association for Cardiac Rehabilitation

These scales can be obtained from the firm: "Borg Perception", Gunnar Borg, Rädisvägen 124, 165 73 Hässelby, Sweden. Phone 46-8-271426.

Other alternatives

There are various tools out there these days such as the following ones:

  • Life Stress (LESCA)
  • State trait anxiety inventory (STAI)
  • Athletic coping skills inventory (ACSI)

however I have no experience in using them…maybe some of you readers know more and what to write comments about any of them?

Enough info now for psychometric tools…next post will cover aspects connected to strength, power and speed.

Monitoring training load: quo vadis? #2

After having presented a simple method to monitor training load without the need of expensive equipment, it is now the time to discuss other methods which involve the use of equipment.

The first and obvious one is monitoring training with the use of heart rate monitors. Thanks to the development of technology it is nowadays possible to measure in real time heart rate (HR) of numerous players on the field without the need for them to wear a watch or a recording device. Many companies in fact provide telemetry systems capable of storing and transmitting heart rate values recorded during training and/or competition. When I first started working in this field may years ago I remember the excitement of being able to measure HR during training and be able to download the files for analysis using the conventional heart rate bands and watches. The cost was prohibitive (there was no way I could afford 20 watches + HR bands!), it took ages to download the files with 1 interface connected to a serial port, and most of all, because athletes needed to wear a watch…we had to be creative about where to place it and also be prepared to sacrifice a few in some contact sports or due to falls.

Nowadays, it is very easy! The current systems can transmit information in real time, it is possible to measure many athletes at the same time and it is possible to store and analyse all data immediately after the end of each training session. Furthermore, due to the improved quality of the sensors used and the software and hardware developments, it is also possible to measure R-R intervals and analyse heart rate variability (HRV).



Heart rate can be considered as a reliable indicator of the physiological load both for immediate training monitoring and for post-training analysis in almost every sport. However, considering the influence of psychological components like anxiety and stress on HR, it is feasible to suggest that an appropriate assessment of training intensity should also consider this limitation of HR monitoring.

Typical training plans of team sports are characterised by a combination of technical and tactical specific drills, small sided games, or general types of team drills. In the above situations, all members or small groups of the team perform similar tasks. The determination of training intensity and training stress is an extremely important parameter for training planning and for appropriate distribution of training load in elite athletes competing in team sports.

The following methods have been suggested to be effective in quantifying the training load:

The Training Impulse [TRIMP] method

Proposed by Bannister et al. (1975), characterised by the following equation:

TRIMP = training time (minutes) x average heart rate (bpm).

For example, 30 minutes at 145 bpm. TRIMP = 30 x 145 = 4350

This approach is very simple, however it does not distinguish between different levels of training. So it has been used mainly to determine general load in aerobic-endurance sessions.


Developed by Foster et al (2001)  is based on assigning a coefficient of intensity to five HR zones expressed as a % of HRmax:

1. 50-60% HRmax

2. 60-70% HRmax

3. 70-80% HRmax

4. 80-90% HRmax

5. 90-100% HRmax

The zone number is used to quantify training intensity; TRIMP is calculated as the cumulative total of time spent in each training zone.

For example

  • 30 minutes at 140 bpm. Max HR = 185 bpm. %max HR = 140/185 x 100 = 76%. Therefore, training intensity = 3.

TRIMP = training volume (time) x training intensity (HR zone) = 30 x 3 = 90.

  • 25 minutes at 180 bpm. Max HR = 185 bpm. %max HR = 97%.

Training intensity = 5. TRIMP = 25 x 5 = 125

The zone TRIMP calculation method can distinguish between training levels while remaining mathematically simple, however this can only quantify aerobic training and it does not allow quantification of strength, speed, anaerobic and technical sessions.


Combining the two methods allows the determination of training intensity not only from a cardiovascular standpoint, but also taking into account the perception of effort and can be extended to strength training to be able to collect a cumulative training load score.

EPOC (excess post-exercise oxygen consumption) Methods

EPOC is basically the excess oxygen consumed during recovery from exercise as compared to resting oxygen consumption. The EPOC prediction method has been developed to provide a physiology-based measure for training load assessment.

EPOC is predicted only on the basis of heart rate derived information. The variables used in the estimation are current intensity (%VO2max) and duration of exercise (time between two sampling points, Dt) and EPOC in the previous sampling point. The model is able to predict the amount of EPOC at any given moment. No post-exercise measurement is needed. The model can be mathematically described as follows:

EPOC (t) = f(EPOC(t-1), exercise_intensity(t), Dt) (Saalasti, 2003)

At low exercise intensity (<30-40%VO2max), EPOC does not accumulate significantly after the initial increase at the beginning of exercise. At higher exercise intensities (>50%VO2max), EPOC accumulates continuously. The slope of accumulation gets steeper with increasing intensity.

(The following figure is from Firstbeat Technologies Withepaper)image

The relationship between measured and HR derived EPOC has been shown to be significantly large suggesting this method as an alternative solution to determine training load with minimally invasive procedures such as wearing a chest band (Rusko et al., 2003).


And by the same authors has been shown to be related to blood lactate.


The EPOC approach has been nowadays introduced by various HR monitors manufacturers ( and

(Figure above from

Various manufacturers are now developing innovative approaches to describe training loads based on HR measurements (e.g. and more will be available soon due to the ability for the current systems to record with high accuracy also R-R intervals and derive training stress information from Heart Rate Variability indices.

I will write more on these in the next posts on this interesting topic…this is it for now…stay tuned!