Changes

{{DISPLAYTITLE: Heart Rate Variability (HRV)GPS Accuracy of Garmin, Polar, and other Running Watches}}<div style="float:right;">__TOC__</div>Heart Rate Variability (HRV) can be used to measure stress, either to evaluate recovery status or exercise intensity.=What is HRV?=Heart Rate Variability (HRV) is a measure I evaluated the real-world accuracy of GPS watches while running over 12,000 miles/19,000Km and recording over 50,000 data points as part of the irregularity my evaluation of the [[Heart RateBest Running Watch]]es. The time between heartbeats varies slightlyUnder good conditions most of the watches are remarkably good, even but when things get a little tough the average [[Heart Rate]] is steadydifferences become more apparent. For exampleHowever, a [[Heart Rate]] '''none of 60 BPM the watches have GPS accuracy that is an average of one beat per secondgood enough to be used for displaying your current pace'''. HoweverAs a result, I've added the actual time between heartbeats could vary so that some beats occur after 0.8 secondstest results for various [[Footpod]]s as they can be far more accurate than GPS, and some after 1but more importantly they tend to have far less moment-to-moment variation so they can give a far better display of your current pace.2 seconds. In (Note that my accuracy tests focus on the context of HRVability to measure distance, this irregularity is a good thingnot the moment in time position, and lower HRV indicates an increased level of stressthough the two are obviously related. ) =HRV to Measure Recovery Status=* HRV can be measured during exercise or at rest[[File:GPS Accuracy. * There are various ways png|none|thumb|800px|An infographic of the accuracy of analyzing HRV that provide different values, and these methods have different benefitsthe GPS running watches. The top right corner represents the most accurate watches. (This graphic uses ISO 5725 terminology.)]]* Resting HRV tends to decline with training stressThe table below is a simplified summary of the results, but there are wide variations between individuals and there are other factors that can influence HRV on where a daily basis. * There is evidence that HRV can '10' would be used to detect [[Overtraining Syndrome]], but only by comparison with prior HRV dataa perfect device.* Generally(For an explanation of the ISO 5725 terms 'trueness', HRV is greatest at rest 'precision' and the variability declines as the heart rate rises. Therefore'accuracy', looking at HRV to Heart Rate ratios is important rather than looking at raw HRV valuessee below. )* HRV is linked to aerobic fitness, with the fittest individuals having {{:GPS Accuracy-summary}}The values used are simply 10 minus the value for trueness (average) and precision (standard deviation from true). The overall is the greatest variability, combination of trueness and this can be used to predict [[VO2max|V̇O₂max]] <ref name="Hottenrott-2006"/>precision. Repeatability is how consistent a watch is in providing the same value for the same course segment.* Lower HRV is associated with greater risk of death after heart attacks<ref name="Lombardi2000"/>'''Important''': Manufacturers do not typically release the type of GPS chipset used, so the information in this table is based the best available data, but it should be treated with caution.* Some =Methodology=''Main article: [[Best Running Watch| Running WatchesGPS Testing Methodology]] can record or display HRV, and some have software '' Simply taking a GPS watch on a single run does not provide sufficient data to use HRV to predict recovery or [[VO2max|V̇O₂max]]. =HRV and Overtraining Syndrome=[[Overtraining Syndrome]] is a serious long term problem reasonably evaluate its accuracy. To gather the data for athletesthis test I ran the same route repeatedly, recording laps every quarter mile. The science around HRV and Overtraining Syndrome course is tricky to interpret challenging for several reasons:* Many GPS, with lots of the studies evaluate the change in HRV with increasing training load (overload). This overload is quite different from Overtraining Syndrome twists, tree cover, power lines, turn arounds and the results do not necessarily transfergoes under a bridge. By comparisonHowever, few studies look at large groups I believe that it's reasonably representative of athletes to see what happens as some of them suffer Overtraining Syndromereal-world conditions, and probably less challenging than running in the city with skyscrapers. * Differing HRV metrics =Accuracy, Trueness and Precision (see belowplus Repeatability) are used in different studies, making comparison difficult=For this evaluation I'll use the ISO 5725 definition of[http://en.wikipedia.org/wiki/Accuracy_and_precision Accuracy as the combination of trueness and precision]. * The HRV is often measured while resting but awake, and HRV can be sensitive to changes in mood or stress which are more variable while conscious. * Relatively short time periods are used, and Overtraining Syndrome typically requires a longer study period. {| class="wikitable" |- valign=HRV Metrics="top"There are a number of mathematical approaches to evaluating HRV|[[File:High precision Low accuracy. Most svg|none|thumb|x200px|This is an example of these metrics do not adjust for heart ratehigh precision, so HRV appears disproportionately higher at lower heart ratesas all the hits are tightly clustered. However, the trueness is poor as all the hits are off center, confounding analysisso accuracy is low. These include]]|[[File:* '''rMSSD'''High accuracy Low precision. This is svg|none|thumb|x200px|This shows good trueness, as all the square root of hits are around the mean sum of center. On average they are on target, but there is poor precision, as the squared differences between R–R intervalshits are scattered. Using rMSSD typically has less measurement error ]]|}We can look at trueness by measuring the average lap length and is less influenced precision by breathing rate than other metricsmeasuring the standard deviation. It is also used as I use the basis of the next two metrics. * '''Ln rMSSD'''traditional approach to standard deviation (variation from mean) as well as a modified approach that uses variation from the true value. This (It is the natural logarithm rMSSD, and this produces a smaller number which tends more common in many fields to be in use "accuracy" to mean closeness to true value and "validity" to mean the range 3combination of accuracy and precision.0-8However, I feel that the meanings used by ISO 5725 are closer to the common usage.0. * If a company sold 'accurate''Ln rMSSD to R-R Interval Ratio'''. Using 12 inch pipes and shipped half of them as 6 inches and half as 18 inches, they would meet the ratio traditional definition of Ln rMSSD to accuracy, but few people would be happy with the heart rate (interval between beats or R-R Intervalproduct. ) adjusts for changes in [[Resting Heart Rate]] (RHH). An athlete could have In addition, I calculate a value for "repeatability", which is a measure of how likely a reduced HRV purely due watch is to give the same distance measurement for a slightly elevated RHHspecific course. * '''SDNN'''. The I calculate the standard deviation for each segment of R-R intervals. The problem with SDNN is that if the heart rate is changing, (going up or down steadily)course, and then take the SDNN will be inappropriately average. A highrepeatability score can mask poor accuracy and can convince users they have a good device. * '''High Frequency Power (HF)'''=Accuracy=The table below shows summary data for each device. Spectral analysis can provide the power in the high frequenciesThe count field is how many measurements I have for that combination of condition and device, typically 0with each measurement being a quarter mile distance.15 I generally aim for over 1,000 data points to 0even out the effects of weather, satellite position and other factors.4 Hz (high frequency here The Trueness is relative.)* '''Low Frequency Power (LF)'''. Like HF but for the low frequenciesabsolute of the mean, typically 0.04 though nearly all watches tend to 0read short.15 Hz,* '''Normalized LF power (LFn)'''The standard deviation is provided based on the variance from the mean and the variance from the known true value. This The average pace error is LF/(LF+HF).* shown to give a sense of how much error you'''pNN50'''. The percentage re likely to see in the display of R-R intervals that differ by more than 50mscurrent pace. I find this This is far too sensitive to heart rate to be of much usean average error not a worst case. =Watches with HRV Recording=There are The data shown below is a number of watches that will record HRV, or summary the accuracy based on all the sections. If you'd like more accuratelydetailed information, will record I've split off the beat-to-beat time [[Detailed Statistics for GPS Running Watches]] for later HRV analysisthe results under different conditions. * '''Recent Garmin Watches'''. require you to download [https{{://fellrnrGPS Accuracy-statistics}}The "Accuracy (Combined)" column has an indication of statistical significance compared with the most accurate entry.com/enable_hrv_settings_fileThe key to this indication is: † p<0.fit enable_hrv_settings_file05, * p< 0.fit] that you copy onto the watch. You must connect the watch to a computer and copy the file to the folder "GARMIN\NEWFILES"01, which on Windows may require you to show hidden folders** p< 0. Simply disconnect and the watch will restart001, processing the FIT file*** p< 0. You can disable HRV with this file [https://fellrnr0001, **** p< 0.com/disable_hrv_settings_file00001, ***** p< 0.fit disable_hrv_settings_file.fit]]. The 000001==Progress of newer watches include [[Garmin Epix]]==I expected GPS watches to improve with time, [[but the opposite appears to be happening. With the Garmin 920XT]]devices especially, [[Garmin 620]], [[Garmin 235]], [[Garmin Fenix 3]], [[Garmin 920XT]]you can see that the older watches generally do far better than the newer ones. I suspect this is due to compromises to get better battery life and smaller packaging and the cost of GPS accuracy.* '''==Smartphone Accuracy==There are various things you will need to do in order to get the level of accuracy I found with Smartphones. See [[Garmin 910XTRunning With A Smartphone#Optimizing GPS Accuracy| Optimizing Smartphone GPS Accuracy]]'''for details. ==Interpretation and Conclusions==What do these statistics mean? This requires you to cycle power off and then on again, then hit is my interpretation:* Under normal conditions the up button, then the down button, repeating 10 times until you get the diagnostic menuGPS accuracy is quite good for most devices. * '''Fenix 5X'''. The accuracy of a calibrated [[Garmin Fenix 5XFootpod]] has a menu option to enable and disable HRVis far better than any GPS device. * '''Suunto Watches'''. These simply record HRV data automaticallyWithout calibration the Footpod is more accurate than any watch currently on the market with the exception of the 310XT/910XT with a Footpod backing up the GPS.* '''The [[Polar V800'''. The M400]], [[Polar V800Garmin Fenix 2]] will display HRV, though and [[Garmin 10]] are noticeably poorer than the other devices. I found the details accuracy of the calculation are not provided. You can use the V800 M400/Fenix2/10 in general usage to record HRV databe rather grim, but not as part of a normal workout which limits and I did some testing pairing them up with the 610 or the value310XT. =Software to Analyze HRV=There are a number of ways you can use HRV as an athleteIn all cases the Fenix2/10 would have poor accuracy compared with the 610 or 310XT on the same run. * There are a number of [[HRV Apps]] for smartphones that are cheap and easy The Fenix2 would repeated loose satellite reception, something I've not seen (the M400 has done this once). The statistics do not reflect just how bad the Fenix2 is, as some of the data is too bad to useanalyze. * Firstbeat has a system that measures HRV overnight and includes analysis software. This is probably The results of the Garmin 610 & 620 indicate the problems with the best solution, but it's also rather expensive for the recreational athlete, costing over $1,00010 are not inherent in a smaller device.* Some [[Best Running Watch| Running Watches]] The improvement in GPS accuracy of the 620 with updated firmware shows just how important the software can record HRV for use in Firstbeat algorithms or other analysisbe.With the earlier firmware the 620 lost over a mile over a 20 mile run! * A number '''The accuracy of running watches have the Firstbeat software built all devices is better in a straight line than on curves or twisty routes'''. My course is a tough test for calculating aerobic training load GPS devices with many curves and recovery timeonly a few relatively straight sections. * Running watches also include algorithms Not surprisingly, for estimating aerobic fitness or training intensities based on HRVmany devices accuracy drops going under the bridge. [[File:Fenix 5X HRV RunalyzeHowever, some devices do great in this section, probably because it's fairly straight.jpg|center|thumb|700px|HRV from * More interestingly the trueness just after the Fenix 5X in RUNALYZE]]=References=<references><ref name="Hottenrott-2006">K. Hottenrottbridge is even lower, Osuggesting that the GPS watches are struggling to reacquire the satellites. Hoos* The turnarounds are even less accurate than going under a bridge, HDbut Power Lines do not seem to impact accuracy noticeably. Esperer, * The [[Heart rate variability and physical exerciseFootpod]] improves the accuracy of the 310XT. Current status]** Note that I'm intentionally using an uncalibrated Footpod (factor = 1., Herz, volume 31, issue 6, pages 544-52, Sep 2006, doi [http://dx000) to gather data for a comparison of Foodpod and GPS.doi* The older Garmin 205 does remarkably well.org/10.1007/s00059-006-2855-1 10=Footpod Accuracy=The accuracy of a Footpod is far higher than GPS, as well as more consistent and quicker to react to changes in pace.1007For any given run, the average pace error from the Footpod is only 7 seconds/s00059-006-2855-1], PMID [httpmile (at a 9:00 min/mile pace) or 5 seconds/www.ncbi.nlm.nih.govKm (at a 5:30 min/pubmed/17036185 17036185]</ref><ref name="Lombardi2000">FKm pace). LombardiIn practical terms, Chaos Theory, Heart Rate VariabilityI've found that I always have to use a Footpod to pace a marathon or for critical speedwork. For details of how the Footpod calibration was done, and Arrhythmic Mortality, Circulation, volume 101, issue 1, 2000, pages 8–10, ISSN see [[http://www.worldcat.org/issn/0009-7322 0009-7322GPS Testing Methodology]], doi [http://dx.doi=Which Chipset? =While the specific chipset used in a GPS watch will impact its accuracy, there are many other factors that come into play.org/10.1161/01.CIR.101.1.8 10The physical packaging of the chipset, the antenna used, the particular features that are implemented, and the software that interprets the raw data will influence the overall accuracy.1161/01.CIR.101.1.8]</ref> It's important to note that the SiRF chipsets such as "SIRFstarIV" are not a single chipset, but rather an overall architecture with several specific chipsets bearing the same name. =Even GPS Watches have Bad Days=</references>While it's tempting to take the various GPS watches on a single run and simply compare the totals, this is a flawed approach. Evaluating the devices GPS accuracy on the basis of a single sample does not tell you much. It's a bit like evaluating an athlete's ability on the basis of one event; everyone has good days and bad days, and that applies to GPS watches as well. To illustrate this, the images below are from two runs, recorded on 9/20 and 9/22. In each run I recorded data on both the 310 and 910 watches, hitting the lap button on both at as close to the same time as is humanly possible. On 9/20 the 910XT was far more accurate than the 310XT, but on 9/22 the situation is reversed. If you were to have evaluated the two watches on the basis of a single run, you would conclude that one is much better than the other. But which device would win would depend on the particular day. This is why I've accumulated a lot of data to do a statistical analysis to work out which is really better. {| class="wikitable" |- valign="top"|[[File:310XT Bad.jpg|none|thumb|x500px| The {{Garmin 310XT}} having a bad day. You can see on the upper half of the course where it got a little confused and off track. ]]|[[File:910XT Good.jpg|none|thumb|x500px|The {{Garmin 910XT}} on the same run having no problems, and only the standard, expected level of inaccuracy.]]|- valign="top"|[[File:310XT Good.jpg|none|thumb|x500px|Two days later and it's the turn of the {{Garmin 310XT}} to have a good day.]]|[[File:910XT Bad.jpg|none|thumb|x500px|Again, this track is recorded on the same run as the image to the left. The {{Garmin 910XT}} gets a little confused at the start, and then again around lap 27.]]|}=Some Devices Are Better Than Others=Below is a section of two runs showing the same section of the course, both taken at the same time, one from the Garmin 310XT and the other from the Garmin 620 with the early firmware. (With the later firmware the tracks from the 620 look like the 310XT.) {| class="wikitable" |- valign="top"|[[File:ExampleGarmin310.jpg|none|thumb|x500px| You can see the GPS tracks (thin red line) are close together and the lap markers (yellow diamonds) are clustered nicely. The blue dots on the GPS tracks are the actual GPS recordings.]]|[[File:ExampleGarmin620.jpg|none|thumb|x500px|By contrast, the 620 has much wider GPS tracks and dispersed lap markers. ]]|}=GPS Short and long measurements=As you can see from the images below, the GPS track tends to take shortcuts around bends, reducing the length of the measured track. This cutting of the corners indicates the devices are doing some post-hoc smoothing to try to overcome the GPS errors. The more smoothing they do, the better the accuracy is likely to be in a straight line and the worse it is around corners or twisty courses. In my discussions with engineers working on GPS systems, this type of smoothing is often performed with a[http://en.wikipedia.org/wiki/Kalman_filter Kalman filter]. (When I tested using software without smoothing I found the measurements were long on my course rather than short, which is almost always the case.)[[File:GPS Shortcuts.jpg|none|thumb|500px|The GPS tracks in red showing the tendency to cut the corners on the curves.]]Often GPS measurements of races, especially marathons record a longer distance than the race. This is partly because the USATF technique for measuring the distance takes a path that is no more than 12 inches away from the tangent (corner), and few runners are able to run that close. In a large marathon you can be forced to take a line that is a long way from the tangent. The other factor is that on a straight line, the GPS error tends to give a slightly longer measurement. {| class="wikitable" |- valign="top"[[File:GPS Marathon.jpg|none|thumb|500px|Here you can see the GPS line is not following the straight road, giving a longer reading on the Thunder Road Marathon. Notice that the GPS is also cutting the corner at the top (we didn't run through the building).]]|[[File:GPS MarketSt.jpg|none|thumb|x300px|Here's another example of running down Market Street in San Francisco, where you can see the errors that would add to the distance. ]]|}=GPS Accuracy and Weather=GPS Accuracy is slightly better with clear skies than with cloud cover. The difference between completely clear and fully overcast is generally less than 0.1% and my testing includes a similar mix of cloud cover for each watch, so I ignore this difference. However, rain can degrade accuracy by 0.3-3.1%, with the better watches being impacted the least. Because it does not rain that frequently where I test, this has created some potential bias in my testing so I now ignore measurements taken during the rain. This has only made a slight difference to the results, but it ensures consistence. =GPS Accuracy and Seasons=I run in a wooded area with mostly deciduous trees, so the foliage varies by season. This foliage can have a noticeable impact on GPS accuracy, with better accuracy during the bare winter months than the rest of the year. This difference is mostly 0.1-1.5%, but in some cases can be as large as 2.5%. Because of this, my testing now ignores data from the winter months when the trees are bare. The short winter here in the south of the US means that the impact on the overall results are small, but like the weather impacts noted above, this does ensure greater consistency. =GPS Accuracy and Pace=[[File:AccuracyAndPace.jpg|none|thumb|500px| A plot of GPS precision against pace. The red line is the correlation.]]There have been reports of GPS accuracy changing with pace, but as you can see from the graph above, my testing does not show this. =GPS and GLONASS=I have found that GPS plus GLONASS produces less accuracy than GPS alone, something that is a little counterintuitive. I have no definitive explanation for this, and I do have a working hypothesis. My thought is that enabling both GPS and GLONASS will increase the number of satellites above the horizon, and a modern chipset can have over 50 channels. This means the chipset will have access to far more satellites with both systems enabled. However, I don't believe that the chipset will use all the available satellites when calculating its position. In an urban, or wooded environment, the satellites nearest the horizon will have the weakest signal, and the satellites closest to directly overhead will have the strongest signal. If the chipset were to use only the strongest 5-6 signals, then it's likely to choose the satellites that are closest to being directly overhead. That means the satellites chosen are relatively close together, which is a poor geometry that reduces accuracy. (In GPS terms this is called Dilution of Precision, or DoP.) I've talked to a GPS specialist who tells me that they have seen this in GPS systems they've tested (though not necessarily consumer grade systems.) What this means in the real world is that if you're in an environment with a partial view of the sky due to tree cover for low buildings then GPS on its own is likely to provide better accuracy. If you're in an environment with a clear view of the sky from horizon to horizon, then it's less clear to me which system is likely to provide better accuracy, and I've not tested this in practice. Given that the theoretical accuracy of GLONASS is not quite as good as GPS I'm not sure that enabling both systems will improve matters. It's possible that GLONASS will do relatively better at extreme polar latitudes due to its different orbital patterns.==Garmin 920XT and GLONASS==The [[Garmin 920XT]] is significantly worse with GLONASS enabled. {| class="wikitable"!Device!Accuracy!Trueness!Precision!Repeatability|-|Garmin 920XT|style="background-color: #FAE983;"|6.6|style="background-color: #D2DE81;"|7.5|style="background-color: #FED680;"|5.9|style="background-color: #D1DD81;"|7.5|-|Garmin 920XT (GLONASS)|style="background-color: #FEC77D;"|5.5|style="background-color: #FAE983;"|6.6|style="background-color: #FCA777;"|4.6|style="background-color: #E1E282;"|7.2|}==Suunto Spartan Ultra and GLONASS==The [[Suunto Spartan Ultra]] seems to do particularly poorly with GLONASS enabled. {| class="wikitable"!Device!Accuracy!Trueness!Precision!Repeatability|-|Suunto Spartan Ultra 1.6.14|style="background-color: #E2E282;"|7.1|style="background-color: #79C47C;"|9.5|style="background-color: #FED881;"|6.0|style="background-color: #D8DF81;"|7.4|-|Suunto Spartan Ultra 1.6.14.GLONASS|style="background-color: #FCB179;"|4.9|style="background-color: #D4DE81;"|7.5|style="background-color: #F9756E;"|3.3|style="background-color: #FDB57A;"|5.0|}==Garmin Epix and GLONASS==The [[Garmin Epix]] has slightly better accuracy with WAAS than without it, and GLONASS didn't degrade the accuracy the way it does with other devices. My belief is that enabling WAAS effectively disables GLONASS, as WAAS is GPS specific (and only available in North America.) There is EGNOS Ground Segment is the equivalent of WAAS for GLONASS/GPS/Galileo in Europe.{| class="wikitable" |- valign="top"!Device!Accuracy!Trueness!Precision!Repeatability|-|Garmin Epix with GLONASS+WAAS|style="background-color: #FFE082;"|6.2|style="background-color: #D6DF81;"|7.4|style="background-color: #FDBE7C;"|5.3|style="background-color: #D6DF81;"|7.4|-|Garmin Epix with WAAS|style="background-color: #FFDF82;"|6.2|style="background-color: #C8DB80;"|7.7|style="background-color: #FDB77A;"|5.1|style="background-color: #F7E883;"|6.7|-|Garmin Epix|style="background-color: #FDC37D;"|5.4|style="background-color: #F3E783;"|6.8|style="background-color: #FB9C75;"|4.4|style="background-color: #F2E783;"|6.8|}==Garmin Fenix 5X and GLONASS==Continuing the theme of poor accuracy with GLONASS enabled, the [[Garmin Fenix 5X]] demonstrates even worse performance than its peers. The values shown below are rather dramatically worse with GLONASS enabled than without. My anecdotal observation is that sometimes the Fenix 5X does a little worse with GLONASS than normal, possibly in line with other Garmin devices, and sometimes it seems to just get lost and produce dramatically worse results. {| class="wikitable sortable"!Device!Accuracy!Trueness!Precision!Repeatability|-|Fenix 5X 4.30|style="background-color: #FEC97E;"|5.6|style="background-color: #EDE683;"|6.9|style="background-color: #FCA377;"|4.5|style="background-color: #F3E783;"|6.8|-|Fenix 5X 4.30 GLONASS|style="background-color: #F97B6F;"|3.5|style="background-color: #FFE082;"|6.2|style="background-color: #F8696B;"|1.6|style="background-color: #F97B6F;"|3.5|}Below you can see a visual representation of the problems. Many of the tracks are a little worse than normal, but you generally follow the path. A small subset of the tracks are dramatically worse, either showing and offset from the actual path, or sometimes it looks like the sampling frequency has dropped, suggesting that the watch is only periodically able to get a location fix. This latter phenomenon is rather surprising to me and goes against my hypothesis of why GLONASS has worse accuracy. I would expect there would be more satellites available with GLONASS enabled, which would result in the watch selecting the subset with the strongest signal that are more likely to have a narrow angle of separation, which would result in increased Dilution of the Precision. These tracks suggest that the Fenix 5X is unable to get any location fix for brief periods. {| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"|- valign="top"|[[File:BridgeFenix 5X 4.30 GLONASS.jpg|center|thumb|x300px| The GPS tracks from the Fenix 5X with GLONASS enabled. This diagram has tracks color coded with green indicating good accuracy through to red indicating poor accuracy, and the lap markers as blue dots.]]|- valign="top"|[[File:BridgeFenix 5X 4.30.jpg|none|thumb|x300px|Here's the tracks from testing with GLONASS disabled for comparison.]]|}=GPS Accuracy and Sampling Rate=GPS watches default to recording a sample frequently enough that accuracy is not compromised. However, several devices offer the option of recording less frequently to improve battery life at the cost of accuracy. These devices actually turn off the GPS receiver, turning it on periodically for just long enough to get a fix. The images below are from the [[2014 Badwater 135]] using the [[Suunto Ambit2| Suunto Ambit2 R]] with recording set to one minute intervals. As you can see, accuracy suffers on curves, but is fine on the straights. For a course like Badwater, the one minute recording interval was fine as the course has few turns. {| class="wikitable" |- valign="top"|[[File:GPS Sampling Curve.jpg|none|thumb|x300px|On a curve, the infrequent samples tend to 'cut the corners' and are quite inaccurate.]]|[[File:GPS Sampling Straight.jpg|none|thumb|x300px|On the straight sections, the one minute sampling does not lose any accuracy.]]|[[File:GPS Sampling Comparison.jpg|none|thumb|x300px|Here's a comparison of 1 minute sampling (red) with 1 second sampling (blue). On my GPS testing course the 1 minute sampling lost nearly 2 miles over a 16 mile run.]]|}=GPS Accuracy and Recording Rate (Smart/1-Second)=While the GPS sampling rate mentioned above has a huge impact on GPS accuracy, the same isn't true for recording rate. These two ideas seem to get confused. GPS sampling rate allows a watch to turn off the GPS receiver for short periods to conserve battery life while sacrificing GPS accuracy. Some Garmin watches can be configured to either record every second, or only record when something happens, such a change in heart rate or change in direction, something they call "smart recording." With a smart recording in normal GPS mode, the GPS system is continually active, so there's no loss in accuracy. To verify this, I tested the [[Garmin Fenix 5X]] in both the smart recording mode I normally use, and one second recording mode for comparison. As you can see, the two modes are virtually identical, and the differences are most likely due to chance (p=0.72). {| class="wikitable sortable"!Device!Accuracy!Trueness!Precision!Repeatability|-|Fenix 5X 4.30 Smart Recording|style="background-color: #FEC97E;"|5.6|style="background-color: #EDE683;"|6.9|style="background-color: #FCA377;"|4.5|style="background-color: #F3E783;"|6.8|-|Fenix 5X 4.30 One Second Recording|style="background-color: #FDBF7C;"|5.3|style="background-color: #E5E382;"|7.1|style="background-color: #FB9073;"|4.0|style="background-color: #FBE983;"|6.6|}=Device Specific Notes=For those interested in some of the details of how devices are configured for testing, here are some additional notes. * Garmin devices are set to 'smart recording'. I did try an informal test with the 620 using 1-second recording, but it appeared to make no difference. * For details of the calibration of the [[Footpod]] see [[GPS Testing Methodology]].* The Fenix 2 was tested with and without WAAS support activated; WAAS helped slightly. * The [[Garmin 920XT]] was tested with Watch Firmware 2.50, GPS Firmware 2.70 using smart recording. =Garmin 620 Issues=The Garmin 620 had some notorious problems with its GPS accuracy. The table below shows the changes with various firmware versions, culminating in the GPS-3.30 firmware that resolved the issues. I've including some testing I did without EPO data (NoEPO row below) and with a Footpod (+FP row below). {{:GPS Accuracy-g620}}{| class="wikitable" |- valign="top"|[[File:Garmin620 Offset1.jpg|none|thumb|x500px|Here you can see the last repeat is offset. Starting at lap marker 49, the track follows the same outline as the more accurate tracks, but is offset. So marker 50 should be near 4, 51 near 37, 52 near 2, 53 near 1, and the finish near the start.]]|[[File:Garmin620 Offset2.jpg|none|thumb|x500px|This is a simple out and back run of ~3 miles/5 Km, but you can see after the turn around the Garmin 620 records a gradually widening gap, even though it follows the right overall shape. (The outbound track is fairly accurate, the return is messed up.)]]|}=Garmin Fenix 2 Issues=Like the Garmin 620, I've had similar GPS accuracy issues with the Fenix 2. In fact, the Fenix 2 is the only device I've ever had that has given the "lost satellite reception" message on my usual running route. Because of these issues Garmin replaced my Fenix 2 under warranty, and below are the results for the original and new watches. The replacement watch also gave "lost satellite reception" repeatedly and the error values for the Fenix 2 do not reflect these problems as the data from those runs was useless for analysis. I suspect there are three (possibly related) problems with the Fenix 2:# The MediaTek GPS chipset is not as accurate as the SiRF chipset. The best results from the Fenix 2 are generally mediocre. # The Fenix 2 records the right shape track, but offset by some distance. This does not look like a typical accuracy problem that would manifest itself randomly. # Occasionally the Fenix 2 will report "lost satellite reception", and I have several instances of this where the date and time were wrong after reception was lost. If a GPS device has the wrong time, then it will expect the satellites to be in different positions and will be unable to acquire a position fix. I have four instances where the workout file was stored with a date in April 2019, indicating that was the date when I terminated the workout and attempted to reacquire satellite lock. In one case I noticed the date and time was set incorrectly on the watch display after the satellite lost message. There are also reports from various users about lost satellite reception and the 2019 date. This problem might also explain the offset track above, but only if the clock was out by a very small amount.{{:GPS Accuracy-Fenix2}}{| class="wikitable" |- valign="top"|[[File:Fenix2 Getting Lost.jpg|none|thumb|x400px|This is an example of just how bad the Fenix 2 can be. This is a short run, with the start and finish in the same place. The track up to marker 18 is not bad, but then the Fenix 2 loses reception for a couple of miles. When it gets reception back, it tracks wildly off course, ending up with a position that's out by around a mile.]]|[[File:Fenix2 Getting Lost3.jpg|none|thumb|x400px|Another example of the Fenix 2 getting lost. You can see marker 41 is a long way off the route, probably about half a mile off. Notice how messy the rest of the track is as well.]]|[[File:Fenix2 Getting Lost4.jpg|none|thumb|x400px|Here you can see the Fenix 2 track is a confused mess.]]|- valign="top"|[[File:Fenix2 Getting Lost5.jpg|none|thumb|x400px| The first part of this run goes okay, but at marker 61 things to go a little astray, and at marker 65 the GPS lock is lost, then briefly regained until marker 70. Not unreasonably, the Fenix 2 assumes straight-line movement until GPS lock is reacquired, but then rather bizarrely seems to assume that the straight-line movement is correct and records a track that is about half a mile/1 Km off.]]|[[File:Fenix2 Short1.jpg|none|thumb|x400px| This is more how the GPS track should look, but even on this run the Fenix 2 lost nearly a mile in a 20 mile run.]]|[[File:Fenix2 Getting Lost6.jpg|none|thumb|x400px|This GPS track looks reasonable until marker #54, and then the track gets offset, but strangely it stays offset until the last marker.]]|}