This page contains guides on how to get the most out of your equipment by looking for key measures and patterns in your data. Select the topic below to jump to the appropriate section

>> Speed Analysis

>> Heart Rate Analysis

>> Stride Analysis

>> Troubleshooting Data Issues

 


 

Speed Analysis

Selection Process
Speed is the most straightforward metric to understand within equinITy as it is a very relatable number, that we can associate and understand easily. When analysing speed, the first encounter is in the summarised data on the work selection screen.

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This view can be filtered to focus on a particular track/gallop, a speed range, a date range a working distance or any combination and then sorted to provide an immediate and quick method to sort data. In this example, we look at only work faster than 35 mph and working over 6 furlongs with the data sorted by maximum speed to determine our fastest pieces of exercise.

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Summary Screen
Detailed analysis of speed data involves opening a specific exercise to look more closely at the data. The first view, Summary, gives a detailed overview of the exercise including: Horse details, Work/Recovery time (including recovery intervals), distance, average stride count (and average length) per furlong/200m, maximum speed/HR/strides, local weather details and sectional times.

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Map View (including animation)
The Map tab allows us to animate the data to playback in real time or accelerated to monitor speed visually using on-screen display and a gauge

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Speed versus Heart Rate Chart
The Speed/HR chart allows us to view the exercise graphically, highlighting the acceleration and pullup profile and also the sectional times. The background of this chart can be adjusted to also show Heart Rate intensity. Using your mouse, you can follow the chart highlighting the precise numbers behind each point.

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Speed Profiling
The Speed Profile chart, shows us a visual distribution of the speed brackets used during the exercise (5 mph brackets). Each slice of the pie chart shows a residence time at the highlighted speed bracket, allowing analysis and review of riding performance, allowing you to achieve more effective exercises, targeting specific speeds for a set duration.

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Splits/Sectional Times Analysis
Splits shows a detailed analysis of the sectional timing from the exercise. Each sectional details start/end time, split, elapsed (+/-) time, minimum/maximum/average speed as well we HR and Stride data. Any column can be sorted by clicking on the header (see left example below). Sub-sections can be selected using the check boxes on the left-hand side (example on the right below where the final 3 furlongs of the exercise are selected).  This allows a new average bar to be dynamically calculated, allowing you to focus your analysis on a specific portion of the exercise, rather than reviewing it as a whole.

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Using Speed data effectively
With all of these views of the data available to us, how do we use this data in a meaningful way?  Speed data is naturally intuitive and relatable, so this is straightforward. For any comparison, we should always be looking at comparable exercises (similar distances, weather conditions, same surface etc) and more importantly in this case comparable speed profiles (similar average and peak speed and similar acceleration/deceleration profiles) – there is little value in comparing entirely different exercises with each other.

 Once we have identified suitable data sets, to look for improvement we are simply looking for higher average or peak speeds, shorter total working time or faster sectional times. Inversely, if we see slower average or peak speeds (for similar effort in terms of maximum HR), slower total working time or slower sectional times, this can be an indication of a decline in fitness which should be monitored closely and where appropriate, a 3rd party should assess the horse.  Highlighting a pattern like this can prevent fatigue and potential injury.

 



Heart Rate Analysis

Selection Process
Heart Rate data in equinITy is modelled in such a way that it is easy to understand, allowing you to get the maximum benefit with the minimum effort. When analysing Heart Rate data, the first encounter is in the summarised data on the work selection screen

HR1.png

This view can be filtered to focus on a particular track/gallop, a speed range, a date range a working distance or any combination and then sorted to provide an immediate and quick method to sort data. In this example, the data sorted by maximum heart rate, allowing us to focus on the exercises in which the horse has been pushed hardest

HR2.png

Summary View Options
Detailed analysis of heart rate data involves opening a specific exercise to look more closely at the data. The first view, Summary, gives a detailed overview of the exercise including: Horse details, Work/Recovery time (including recovery intervals), distance, average stride count (and average length) per furlong/200m, maximum speed/HR/strides, local weather details and sectional times

HR3.png

Recovery Time
Recovery Time is the time it takes the horse to reach the Recovery Target after pulling up.  The default configuration of this target is 120 bpm, but this can be changed according to your preference (some clients for instance choose to monitor to a lower figure). So, this example shows us that after a 6f exercise, the horse pulled up and from that point, it took 1 minute and 51 seconds for the horse’s heart rate to fall to 120 bpm

We can also see the 1, 2- and 3-minute recovery intervals.  This is an alternative way of monitoring recovery.  Rather than focusing on a recovery target, we can see how many beats are dropped at these intervals.

Speed versus Heart Rate Heart Rate Zones
The Speed/HR chart allows us to view the exercise graphically, highlighting the correlation between speed and heart rate. The background of this chart can be adjusted to show Heart Rate zones.  The interpretation of the chart is that whichever zone the red (heart rate) line is in, that is in an indication of how hard the horse’s heart is working at that point in time.

The scale is based on bands built around a theoretical maximum HR of 240 bpm.  Up to 60% capacity is considered Recovery, 61-70% is considered Moderate, 71-80% is considered Aerobic, 81-90% Threshold and 91%+ Maximal.  The higher the effort, the harder the exercise. Using your mouse, you can follow the chart highlighting the precise numbers behind each point.

HR5.png

Heart Rate Zones Chart
The Zones chart allows the data from the Heart Rate Zones to be summarised in a very visual and easy to follow way.  The example on the left below is the residence time in each zone from the example in 5.  It shows that the exercise was spent entirely in the Threshold and Maximal Zones, meaning the horse was putting in significant effort throughout to achieve the time/speeds in this exercise

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The example on the right above, shows how a typical walking/trotting exercise might look.  Significantly less effort. 

Using Heart Rate data effectively
With all these views of the data available to us, how do we use this data in a meaningful way?  For any comparison, we should always be looking at comparable exercises - similar distances, weather conditions, same surface and similar speed – there is little value in comparing entirely different exercises with each other, especially with heart rate as every variable could have an effect. Once we have identified suitable data sets, to look for improvement we can focus on several measures:

  • Recovery Time
    Recovery Time is easy to understand and subsequently easy to analyse.  Recovery Times should become shorter until the horse reaches peak fitness.  Once you have established this “baseline”, any time the horse has a break from training, you have a good indication of when the horse is back to peak fitness. Inversely, if you witness a recovery time becoming longer, this might be an indication that the horse’s fitness is in decline and if a pattern emerges, you should seek veterinary advice, especially if this data is backed up by observations or feedback from riders

  • Peak/Average HR
    To complete an exercise of a certain distance at a given speed, the horse’s Maximum and average HR can be monitored over several exercises.  Whilst a horse is reaching peak fitness levels, the peak/average HR will usually come down.  Once this numbers plateau, this can then be assumed to be the horse in peak fitness.  After a break from training, you now have an established and proven baseline to work towards whilst the horse regains full fitness

  • If you see a pattern of the peak or average HR increasing, this could be an indicator of illness or pain and you should consult a veterinary expert for a more detailed assessment.  Highlighting a pattern like this early could prevent a potential injury

  • Erratic/spiking HR profiles
    Heart Rate should, in general, be responsive to speed changes and fairly consistent, for example:

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  • If you find data that contains “spikes” that are somewhat erratic and have no obvious correlation to speed (or an external factor such as traffic, sudden sounds etc), this could be an indication of an underlying issue.  Again, you should consult a veterinary expert for a more detailed assessment.  Here is an example of how such data could look:

HR9.png
  • Considerations
    Its important to ascertain the conditions and chain of events with the rider and observations before making any judgement based on data

  • The horse’s temperament for example can be crucial to your analysis.  Horses who are “skittish” by nature for instance may react to birds, traffic, the behaviour or other horses and exhibit spikes in HR which ordinarily might suggest a problem but if they can be rationalised or attributed to the horse’s typical behaviour, you may react differently

 

Stride Analysis

Stride Basics
Analysing Stride data involves first selecting an exercise to focus your analysis on. The first view, Summary, gives a detailed overview of the exercise including: Horse details, Work/Recovery time (including recovery intervals), distance, average stride count (and average length) per furlong/200m, maximum speed/HR/strides, local weather details and sectional times.

Stride1.gif

This Summary view contains two elements of stride analysis, both of which are key measures as they are easy to understand and work with for future analysis. First we have the Stride Count (Avg) which gives the average stride count and length per furlong.  Average stride length in particular is a good choice to base analysis on as it involves a single number (much like Recovery Time or Peak HR)

Stride2.png

The second area we can analyse from this screen is in the table in the bottom right corner.  Here we can see the number of strides taken in each section throughout the exercise.  As you would expect, fewer steps are taken in faster sectionals as the stride length is longer to achieve the higher speeds.

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Understanding Stride Length
The Speed/Stride chart allows us to view the correlation between Strides per Second (sps) or Stride Length with speed. As a general guide, Stride Length is the recommended metric to work with as its extremities have more scope than SPS (which will typically vary by small fractions).  So for instance a change from 5.3m stride length to 7.3m is clear to see whereas measuring the same with SPS is a change from 2.00 to 2.13


Using Stride data effectively
With this data available to us, how do we use it in a meaningful way?   

For any comparison, we should always be looking at comparable exercises - similar distances, weather conditions, same surface and similar speed – there is little value in comparing entirely different exercises with each other. Once we have identified suitable data sets, to look for improvement we look for either a stride length increasing (representing more free movement) or at least staying consistent (physical limitations mean stride length will plateau although research does prove it can be affected through manipulation and other techniques). 

Following rest periods, we now know the stride lengths the horse should exhibit once in peak fitness or free from injury. 

The real power of stride length analysis is when we are looking for the opposites signs i.e a stride length becoming shorter.  When the horse feels pain, it cannot move freely and this is what stride length tells us.  To reduce the pain, the horse will compensate by not stretching as far as it would ordinarily and if you can spot this pattern in your data, you can intervene and potential prevent a small injury becoming much worse

 

Troubleshooting Data Issues

When analysing data, erroneous data can result in false positives when looking for certain conditions.  Elements of the data can often be red flags to this and this document looks at some common ones and how you can avoid them.

GPS Errors
GPS errors can have an impact on speed, in particular you might witness a spike which suggests a speed which you are suspicious of such as the example below where the horse achieving this speed is highly unlikely. 

Error1.png

Or you may find a sectional time which seems incomprehensibly fast.  In both cases, this is usually down to GPS impairment which may be cause by local infrastructure such as buildings or trees but in most cases, it will simply be that the positional accuracy was affected by the start-up procedure not being followed correctly.  Always ensure your device is powered up outside, with clear line of sight to the sky and avoid taking the device indoors to keep the positional accuracy at its most optimal which in turn will give you reliable speed measurement.

Another effect of GPS impairment can be “teleportation” whereby the device moves from one location to another, often far away, in a second. 

Error2.png


In reality, this effect is when the GPS receiver loses signal for a short time and then regains connection.  The net effect of this would again be a sectional time that is impossibly fast and if you encounter such a time, looking at the Map view will often highlight this problem.  As you can see, there are almost no data points between the 2f and 1f pole.  If you see this consistently, you should contact support for further assistance.

Indoor Use
Using the equipment indoors is not supported and no positional accuracy can be guaranteed if used in this way.  To analyse the effectiveness under cover/indoors, using the map view will show you the position of the detected data versus the physical location (the photograph).  If the tracking is inconsistent, such as this example where all 3 lines are in different locations, you should not use the device in this environment as your data will be inconsistent and difficult to analyse in any meaningful way.

Error3.png

Poor Conductivity affecting Heart Rate Data
Heart Rate errors can lead to incorrect diagnosis of problems or equally the indication that the horse is much fitter or more able than it is in fact.   There are several tell-tale signs, all of which are easy to analyse and identify as erroneous (and you can then discard this data from your analysis)

As a rule, heart rate should be responsive and have good correlation to speed such as this example:

Error4.png

When it does not, as with this example:

Error5.png

… this is usually an indication of poor conductivity.  Ensure the “Tacking Up” video is followed closely to ensure optimal conductivity and that the horse is clipped such that the heart rate monitor electrodes are in as direct contact with the horse’s skin as possible.

Optimal HRM Usage
Partial or sudden loss of conductivity can be seen in the form of “bucket” shapes in HR data such as this example (between the 5f and 6f markers). 

Error6.png

With no obvious correlation to the horse’s movement, the HR will drop and then rise again almost immediately.  This is most often because the girth has slipped back on the horse (only a very small amount, which happens during most exercises, especially at higher speeds) and if this is onto an area of the skin which is dry, the signal quality is greatly affected. In this example, because the area was correctly soaked, the loss of signal is only a few seconds and the overall impact is minimised, with no significant effect on the data.

However, when movement occurs onto dry areas, the impact can be much greater.  Avoiding this is simple, following the Tacking Up video closely and ensure an area 6-8 inches wider than the original girth position is soaked before you begin exercise.  The goal is to ensure than no matter where the tack may end up, this area is wet, providing optimal conductivity.

HRM Battery Degradation
“Steps” in HR data (contiguous seconds of the same HR reading, forming a flat section) are another pointer to poor conductivity but it can also be and early indication that the battery needs replacing in the HRM.  Following the Tacking Up video closely can rule out conductivity and if that has no effect, the instructions to change the battery can be found in the Help section.

A more obvious sign of a failing HRM battery is the presence of partial or complete flat HR data. 

In both cases you should change the battery in your HRM immediately to avoid further data loss.  It is recommended to change your HRM batteries regularly to avoid any lost data.

Static Build-Up
The presence of static can cause HR readings to increase without an obvious cause, often until eventually maxing out the HRMs range.  This image shows a typical illustration of this effect. 

Error9.png

The point at which this occurs in the exercise is often an indicator of the root cause.  When it occurs post-exercise, the cause of this can be insufficient tension (for instance when the rider slackens the girth post exercise, resulting in the HRM electrodes being able to move and the rubbing creates static build-up which is the case in the example) or damage to the girth sleeve which allows the HRM to move around during exercise (having the same effect as a loose girth). 

When this effect occurs inconsistently at any stage of the exercise, this usually points to sleeve damage which means the HRM electrodes are not held firmly in place and are moving around.  In this case, the Sleeve should be replaced.

This effect at the beginning of a data set is usually a pointer to insufficient moisture (which will reduce as the exercise goes on due to a build-up of sweat).

Spiking Stride Data
Stride errors in the form of spikes in stride length are usually cause by the Monitoring Device being bumped. More often than not the rider will kick the stirrup into the pocket.  The result is a maximum stride length which is askew from the rest of the data set.

Stride Data Missing at low speed
Stride length detection is not possible at walking speed but if you see stride data is entirely missing from a data set, this usually points to a hardware malfunction and you should refer it to equinITy Support as soon as possible.  Whilst under warranty or covered by a Premium Service Plan, you will be given a new device, free of charge, once it is returned.  Please do not return any hardware without contacting Support first.