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{{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 test results for various [[Footpod]]s as they can be far more accurate than GPS, but more importantly they tend to have far less moment-to-moment variation so they can give a far better display of your current pace. (Note that some beats occur after 0.8 secondsmy accuracy tests focus on the ability to measure distance, not the moment in time position, and some after 1though the two are obviously related.2 seconds) [[File:GPS Accuracy. In png|none|thumb|800px|An infographic of the context accuracy of HRV, this irregularity the GPS running watches. The top right corner represents the most accurate watches. (This graphic uses ISO 5725 terminology.)]]The table below is a good thingsimplified summary of the results, and lower HRV indicates where a '10' would be a perfect device. (For an increased level explanation of stressthe ISO 5725 terms 'trueness', 'precision' and 'accuracy', see below. )=HRV to Measure Recovery Status={{:GPS Accuracy-summary}}* HRV can be measured during exercise or at restThe values used are simply 10 minus the value for trueness (average) and precision (standard deviation from true). * There are various ways The overall is the combination of analyzing HRV that provide different values, trueness and these methods have different benefitsprecision. * Resting HRV tends to decline with training stressRepeatability is how consistent a watch is in providing the same value for the same course segment. '''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 there are wide variations between individuals and there are other factors that can influence HRV on a daily basisit should be treated with caution. * There is evidence that HRV can be used to detect =Methodology=''Main article: [[Overtraining SyndromeGPS Testing Methodology]], but only by comparison with prior HRV '' Simply taking a GPS watch on a single run does not provide sufficient datato reasonably evaluate its accuracy.* Generally, HRV is greatest at rest and To gather the variability declines as data for this test I ran the heart rate risessame route repeatedly, recording laps every quarter mile. ThereforeThe course is challenging for GPS, looking at HRV to Heart Rate ratios is important rather than looking at raw HRV valueswith lots of twists, tree cover, power lines, turn arounds and goes under a bridge. * HRV is linked to aerobic fitnessHowever, with the fittest individuals having the greatest variabilityI believe that it's reasonably representative of real-world conditions, and probably less challenging than running in the city with skyscrapers. =Accuracy, Trueness and Precision (plus Repeatability)=For this can be used to predict evaluation I'll use the ISO 5725 definition of[[VO2max|V̇O<sub>2<http://sub>maxen.wikipedia.org/wiki/Accuracy_and_precision Accuracy as the combination of trueness and precision]] <ref name. {| class="Hottenrott-2006wikitable"/>.* Lower HRV is associated with greater risk of death after heart attacks<ref name|- valign="Lombardi2000top"/>.* Some |[[Best Running WatchFile:High precision Low accuracy.svg|none|thumb|x200px| Running Watches]] can record or display HRVThis is an example of high precision, and some have software to use HRV to predict recovery or as all the hits are tightly clustered. However, the trueness is poor as all the hits are off center, so accuracy is low.]]|[[VO2maxFile:High accuracy Low precision.svg|V̇O₂maxnone|thumb|x200px|This shows good trueness, as all the hits are around the center. On average they are on target, but there is poor precision, as the hits are scattered.]]. =HRV and Overtraining Syndrome=|}[[Overtraining Syndrome]] is a serious long term problem for athletes. The science around HRV We can look at trueness by measuring the average lap length and Overtraining Syndrome is tricky to interpret for several reasons:* Many of precision by measuring the studies evaluate standard deviation. I use the change in HRV with increasing training load traditional approach to standard deviation (overloadvariation from mean)as well as a modified approach that uses variation from the true value. This overload (It is quite different from Overtraining Syndrome more common in many fields to use "accuracy" to mean closeness to true value and "validity" to mean the results do not necessarily transfercombination of accuracy and precision. By comparisonHowever, few studies look at large groups of athletes I feel that the meanings used by ISO 5725 are closer to see what happens as some the common usage. If a company sold 'accurate' 12 inch pipes and shipped half of them suffer Overtraining Syndrome. * Differing HRV metrics (see below) are used in different studiesas 6 inches and half as 18 inches, they would meet the traditional definition of accuracy, making comparison difficultbut few people would be happy with the product. * The HRV is often measured while resting but awake) In addition, I calculate a value for "repeatability", and HRV can be sensitive to changes in mood or stress which are more variable while consciousis a measure of how likely a watch is to give the same distance measurement for a specific course. * Relatively short time periods are used, and Overtraining Syndrome typically requires I calculate the standard deviation for each segment of the course, and then take the average. A high repeatability score can mask poor accuracy and can convince users they have a longer study periodgood device. =HRV MetricsAccuracy=There are a number of mathematical approaches to evaluating HRVThe table below shows summary data for each device. Most The count field is how many measurements I have for that combination of these metrics do not adjust condition and device, with each measurement being a quarter mile distance. I generally aim for heart rateover 1, so HRV appears disproportionately higher at lower heart rates000 data points to even out the effects of weather, confounding analysissatellite position and other factors. These include:* '''rMSSD'''. This The Trueness is the square root absolute of the mean sum of the squared differences between R–R intervals, though nearly all watches tend to read short. Using rMSSD typically has less measurement error and The standard deviation is less influenced by breathing rate than other metricsprovided based on the variance from the mean and the variance from the known true value. It The average pace error is also used as the basis shown to give a sense of how much error you're likely to see in the next two metricsdisplay of current pace. * '''Ln rMSSD'''This is an average error not a worst case. This The data shown below is the natural logarithm rMSSD, and this produces a smaller number which tends to be in summary the range 3accuracy based on all the sections.0-8.0. * If you'd like more detailed information, I''Ln rMSSD to R-R Interval Ratio'''. Using ve split off the ratio of Ln rMSSD to the heart rate (interval between beats or R-R Interval) adjusts for changes in [[Resting Heart Rate[[Detailed Statistics for GPS Running Watches]] for the results under different conditions. {{:GPS Accuracy-statistics}}The "Accuracy (RHHCombined). An athlete could have a reduced HRV purely due " column has an indication of statistical significance compared with the most accurate entry. The key to a slightly elevated RHHthis indication is: † p<0. 05, * '''SDNN'''p< 0. The standard deviation of R-R intervals01, ** p< 0. The problem with SDNN is that if the heart rate is changing001, (going up or down steadily)*** p< 0.0001, then the SDNN will be inappropriately high. * '''High Frequency Power (HF)'''*** p< 0. Spectral analysis can provide the power in the high frequencies00001, typically ***** p< 0.15 000001==Progress of newer watches==I expected GPS watches to 0improve with time, but the opposite appears to be happening.4 Hz (high frequency here is relative.)* '''Low Frequency Power (LF)'''. Like HF but for With the Garmin devices especially, you can see that the older watches generally do far better than the low frequencies, typically 0newer ones.04 I suspect this is due to compromises to 0.15 Hz,get better battery life and smaller packaging and the cost of GPS accuracy. * '''Normalized LF power (LFn)'''. This is LF/(LF+HF).==Smartphone Accuracy==* '''pNN50'''. The percentage of R-R intervals that differ by more than 50ms. I find this is far too sensitive There are various things you will need to heart rate do in order to be get the level of much useaccuracy I found with Smartphones. See [[Running With A Smartphone#Optimizing GPS Accuracy| Optimizing Smartphone GPS Accuracy]] for details. =Watches with HRV Recording=Interpretation and Conclusions==What do these statistics mean? This is my interpretation:There are a number of watches that will record HRV, or more accurately, will record * Under normal conditions the beat-to-beat time GPS accuracy is quite good for later HRV analysismost devices. * '''Recent Garmin Watches'''. require you to download The accuracy of a calibrated [[https://fellrnrFootpod]] is far better than any GPS device.com/enable_hrv_settings_file.fit enable_hrv_settings_file.fit] that you copy onto Without calibration the Footpod is more accurate than any watch. You must connect currently on the market with the exception of the watch to 310XT/910XT with a computer and copy the file to Footpod backing up the folder "GARMIN\NEWFILES", which on Windows may require you to show hidden foldersGPS. Simply disconnect and the watch will restart, processing the FIT file. You can disable HRV with this file * The [[https://fellrnr.com/disable_hrv_settings_file.fit disable_hrv_settings_file.fitPolar M400]]. The watches include , [[Garmin EpixFenix 2]], and [[Garmin 920XT10]]are noticeably poorer than the other devices. I found the accuracy of the M400/Fenix2/10 in general usage to be rather grim, [[Garmin 620]]and I did some testing pairing them up with the 610 or the 310XT. In all cases the Fenix2/10 would have poor accuracy compared with the 610 or 310XT on the same run. * The Fenix2 would repeated loose satellite reception, [[Garmin 235]], [[Garmin Fenix 3]]something I've not seen (the M400 has done this once). The statistics do not reflect just how bad the Fenix2 is, [[Garmin 920XT]]as some of the data is too bad to analyze.* '''[[The results of the Garmin 910XT]]'''. This requires you to cycle power off and then on again, then hit 610 & 620 indicate the up button, then problems with the down button, repeating 10 times until you get are not inherent in a smaller device. * The improvement in GPS accuracy of the diagnostic menu620 with updated firmware shows just how important the software can be. With the earlier firmware the 620 lost over a mile over a 20 mile run! * '''Fenix 5XThe accuracy of all devices is better in a straight line than on curves or twisty routes'''. [[Garmin Fenix 5X]] has My course is a menu option to enable tough test for GPS devices with many curves and disable HRVonly a few relatively straight sections. * '''Suunto Watches'''Not surprisingly, for many devices accuracy drops going under the bridge. These simply record HRV data automaticallyHowever, some devices do great in this section, probably because it's fairly straight.* '''Polar V800'''. The [[Polar V800]] will display HRVMore interestingly the trueness just after the bridge is even lower, though suggesting that the details of GPS watches are struggling to reacquire the calculation satellites. * The turnarounds are not provided. You can use the V800 to record HRV dataeven less accurate than going under a bridge, but Power Lines do not as part of a normal workout which limits the valueseem to impact accuracy noticeably. =Software to Analyze HRV=There are a number of ways you can use HRV as an athlete. * There are a number of * The [[HRV AppsFootpod]] for smartphones that are cheap and easy to useimproves the accuracy of the 310XT. * Firstbeat has a system * Note that measures HRV overnight and includes analysis software. This is probably the best solution, but itI's also rather expensive for the recreational athlete, costing over $m intentionally using an uncalibrated Footpod (factor = 1,.000.* Some [[Best Running Watch| Running Watches]] can record HRV ) to gather data for use in Firstbeat algorithms or other analysisa comparison of Foodpod and GPS.* A number The older Garmin 205 does remarkably well. =Footpod Accuracy=The accuracy of running watches have the Firstbeat software built a Footpod is far higher than GPS, as well as more consistent and quicker to react to changes in for calculating aerobic training load and recovery timepace. * Running watches also include algorithms for estimating aerobic fitness For any given run, the average pace error from the Footpod is only 7 seconds/mile (at a 9:00 min/mile pace) or training intensities based on HRV. [[File5 seconds/Km (at a 5:Fenix 5X HRV Runalyze30 min/Km pace).jpg|center|thumb|700px|HRV from In practical terms, I've found that I always have to use a Footpod to pace a marathon or for critical speedwork. For details of how the Fenix 5X in RUNALYZEFootpod calibration was done, see [[GPS Testing Methodology]]. =ReferencesWhich Chipset? =<references><ref name="Hottenrott-2006">K. HottenrottWhile the specific chipset used in a GPS watch will impact its accuracy, Othere are many other factors that come into play. Hoos, HD. Esperer, [Heart rate variability and The physical exercise. Current status].packaging of the chipset, Herzthe antenna used, volume 31the particular features that are implemented, issue 6, pages 544-52, Sep 2006, doi [http://dxand the software that interprets the raw data will influence the overall accuracy.doi.org/10.1007/s00059-006-2855-1 10.1007/s00059-006-2855-1]It's important to note that the SiRF chipsets such as "SIRFstarIV" are not a single chipset, PMID [http://wwwbut rather an overall architecture with several specific chipsets bearing the same name.ncbi.nlm.nih.gov/pubmed/17036185 17036185]</ref><ref name="Lombardi2000">F. Lombardi, Chaos Theory, Heart Rate Variability, =Even GPS Watches have Bad Days=While it's tempting to take the various GPS watches on a single run and Arrhythmic Mortalitysimply compare the totals, Circulation, volume 101, issue 1, 2000, pages 8–10, ISSN [http://wwwthis is a flawed approach.worldcatEvaluating the devices GPS accuracy on the basis of a single sample does not tell you much.org/issn/0009-7322 0009-7322]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, doi [http:the images below are from two runs, recorded on 9/20 and 9/dx22.doi.org/10In 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.1161On 9/0120 the 910XT was far more accurate than the 310XT, but on 9/22 the situation is reversed.CIR.101.1If 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.8 10But which device would win would depend on the particular day.1161/01.CIR.101.1This is why I've accumulated a lot of data to do a statistical analysis to work out which is really better.8]</ref> </references>{| 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 (EGNOS Ground Segment is the equivalent of WAAS for GLONASS.){| 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|}=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.]]|}=Next Steps=This is an initial analysis of the data I have, and there are a number of further evaluations to do.* Check how GPS accuracy changes over the course of a run, as I've seen a distinct tendency for the watches to say they are good to go when they don't really have an optimal lock on the satellites. I wait for 5+ minutes between the watches saying they have sufficient satellites locked in, so this should not be a problem with the data shown here, but I could do some tests where I turn on the watch from a cold state, then start running as soon as they claim they have a lock. * Look at how accurate the GPS watches are for measuring elevation, and compare with barometric data.* Write up general GPS accuracy.