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The use of GPS wearables in Running – Latest research insights

The use of wearable technology, such as sport watches with GPS capabilities, has significantly transformed the way athletes, particularly runners, track and assess their performance. These devices provide a comprehensive array of data, including distance travelled, pace, and even route mapping, offering invaluable information for enhancing training and improving athletic performance ​(1)​. However, the accuracy of the GPS data provided by these sport watches is one of the most frequently asked questions in sports stores/tech stores and needs to be considered, as it can significantly affect the reliability of the performance metrics of the runner.

These metrics are used in running coaching and programming, and the most accurate information is often the most sought after by the runner. In the world of Sports Science research, scientific groups and researchers across the globe have investigated the accuracy of GPS-enabled sport watches in various sports, including running, with varying results (1–3). In this blog, we unpack some of the most pertinent results from the body of academic knowledge.

Micro-Electro-Mechanical Systems

One research project investigated the utility of a Micro-Electro-Mechanical Systems (MEMS) inertial motion sensing watch in determining walking and running activities (1). The authors discovered that the sports watch used in the study delivered precise measurements of speed, distance, and the nature of the activity being undertaken. This implies that GPS-enabled sport watches can serve as a useful resource for runners, offering dependable information to aid their training and performance objectives. Another study delved into the practical application of various wearable sensors, which included the assessment of inertial, force, and EMG sensors, in sport biomechanics (4). The researchers found that inertial sensors, examples of which are present in GPS-enabled sport watches, were the most frequently utilized for evaluating athletic performance, especially in the sport of running. 

 

Despite the generally positive outcomes, it is crucial to acknowledge that the accuracy of GPS-enabled sports watches can be affected by a range of variables, such as environmental circumstances, the particular sensor technology utilized, and the algorithms implemented to process the information. For instance, one study offers guidelines for evaluating the dependability, sensitivity, and validity of data provided by wearable devices, indicating that the assessment procedures should replicate the demands of the specific sport, including aspects such as slow running, straight sprints, and changes of direction (3). If these factors are not considered, inaccurate or misleading data may be produced. 

 

Comparing watch GPS accuracy in running research

An interesting study by Gilgen and colleagues (2020) directly assessed the accuracy of distance recordings in eight positioning-enabled sports watches (5). The authors of this study recruited elite athletes and recreational runners who rely on the accuracy of global navigation satellite system (GNSS) / global positioning system (GPS)–enabled sport watches to monitor and regulate training activities, with the aim of investigating the accuracy of the recorded distances in different areas namely, urban area, forest area, and track and field. These sport watches were manufactured by leading brands namely, Apple, Coros, Garmin, Polar, and Suunto ⌚️

 

Distance Urban Area 

Distance Forest Area 

Distance Track-Field 

Watch

Apple® Watch Series 4 

1951.6m 

1969.8m 

2196.4m 

 Apple Watch

 

Coros® Apex 

1899.5m 

1944.1m 

2115.7m 

Coros Apex 

Garmin® Fénix 5X Plus 

1939.9m 

1946.1m 

2165.4m 

 Garmin Fenix

 

Garmin® Forerunner 935 

1857.1m 

1983.0m 

2121.6m 

 Garmin 935

 

Polar® Vantage M 

1949.2 

1993.4m 

2142.3m 

 Polar Vantage M

 

Polar® Vantage V 

1941.9m 

2000.4m 

2134.1m 

 Polar Vantage V

 

Polar® V800 

2134.6m 

2030.6m 

2108.2m 

 Polar V800

 

Suunto® 9 Baro 

1868.7m 

1827.9m 

2150.5m 

 Suunto Baro

 

 

Overall, the recorded distances were underestimated in all watches, and the variance and some outliers were rather high. With respect to the environmental areas in which the watches were tested, an underestimation of the recorded distances in the forest and urban areas (except for the Polar V800) was observed. In these areas, the mean absolute percentage error (MAPE) ranged from –3.5% to –8.9%, and a low 5% accuracy of 0% - 75% indicated large variances in the different watch models. This was coherent with previous research that demonstrated a present underestimation of the recorded distances by -1.2% and -6.2% in both urban and forest areas, respectively. These outcomes emphasize the reality that global navigation satellite system (GNSS) or global positioning system (GPS) signals are diminished in situations where they are hindered, such as when there is dense foliage or when they are close to buildings or other objects. This is because the signals may bounce off these surfaces before reaching the GNSS/GPS receiver, which not only receives signals directly from the satellites but also from reflected surfaces (6) 

 

In contrast, in the track and field area, the recorded distances were overestimated compared with the reference distance. However, the MAPEs were all <5% and ranged from 0.9% to 4.1% only. Furthermore, a good 5% accuracy was shown in the track and field area, with 5 devices having 100% (Coros Apex, Garmin Forerunner 935, Polar Vantage M, Polar V800, Suunto 9 Baro), 2 devices having 83% (Garmin Fenix 5X+, Polar Vantage V), and 1 device having 67% (Apple Watch 4) of the distance recordings falling within the ±5% accuracy threshold. The authors assume that manufacturers may autocorrect the recorded distances in the first place to level out the underestimation in difficult areas, which may in turn result in an overestimation of the distance recordings in unobstructed conditions, such as flat and open areas (7). Needless to say, the use of all the investigated sport watches can be recommended, especially for distance recordings in an open area (5). 

 

Insights from the Two Oceans Marathon

Looking at more locally produced research in South Africa, Rebecca Johansson, Steffen Adolph, Prof Jeroen Swart and Prof Mike Lambert of the Health through Physical Activity, Lifestyle and Sport research centre at the University of Cape Town assessed the accuracy of various global positioning system (GPS) sport watches in measuring distance throughout a 56km running race (8). The race in question was the 2017 Two Oceans Ultramarathon, where the measured distance between timing mats was compared to the reported distance of GPS devices. In this study, 255 runners were divided into eight different categories based on GPS sport watch brand and model. The categories include Garmin Fenix  series (GFX), Garmin XT series (GXT), Garmin Forerunner (GFR), Activity watches (ACT), Suunto series (STO), TomTom (TOM), Polar (PLR) and cell phones (CEL) using Strava® (downloadable on the Apple Appstore or the Google Playstore®).

Device 

Participants 

Race time (h:min:sec) 

GFX: Garmin® Fenix series (1, 2, 3) 

34 

5:52:31 ± 44:39 

GXT: Garmin® XT series (305, 310, 735, 910, 920) 

58 

5:42:50 ± 42:28 

GFR: Garmin® Forerunner series (25, 35, 220, 225, 230, 235, 610, 620, 630) 

67 

5:45:04 ± 50:46 

ACT: Activity Watches: Garmin® VivoActive, Fitbit® Surge, Samsung® Gear 2 and 3, Apple® Watch 

10 

6:12:12 ± 35:13 

STO: Suunto® Watches: Ambit 2, 2 R, 2S; Ambit 3 Sport, Peak, Run; Spartan 

20 

5:42:33 ± 40:46 

TOM: TomTom® VR Series 

44 

6:02:58 ± 40:24 

PLR: Polar® M400 and V800 

8 

5:42:38 ± 52:28 

CEL: iPhones (8); Samsung (6) via Strava®

14 

6:04:10 ± 36:42 

The results of this study detail the following: 

  • The first segment of the Two Oceans Marathon was not analysed due to the different starting times of the runners, however, for segment 2 (16-24km) of the ultramarathon, the GXT, GFR, and TOM devices had lower relative and distance errors when compared to the GFX devices.  
  • In addition to this GXT, GFR, and TOM devices also had lower relative and distance errors when compared to CEL devices. In segment 3 (28-42.2km) all device categories except for CEL had lower relative distance errors, when compared to the GFX devices. All device categories except for GFX and ACT had lower relative errors and distance errors, when compared to CEL devices. TOM had a lower relative error when compared to ACT devices 
  • For segment 4 (42.2–50km), the GXT, GFR and TOM devices had higher relative and distance errors, when compared to GFX. All device categories except for PLR and GFX had significantly different relative and distance errors when compared to CEL devices. The STO and PLR devices had lower relative and distance errors, when compared to TOM. The GXT and GFR watches had higher relative and distance errors when compared to STO. GFR had a higher relative and distance errors when compared to PLR.  
  • For segment 5 (50–56 km), GXT, GFR and TOM devices had lower relative and distance errors when compared to CEL devices.  

 

This study found that GXT, GFR, STO, TOM and PLR have lower overall errors compared to CEL and GFX. Additionally, the errors appear to be greater in the hilly sections of the race with more turns (segments 3, 4 and 5) compared to the flatter and straighter section (segment 2) (8). 

 

To summarize these insights, GPS-enabled sports watches can provide valuable data for running, and their accuracy must be carefully assessed. It is important to consider the specific sport and environmental conditions in which they will be used, and from the research findings presented above, we are now more informed as to how GPS watches for running are valid and accurate under different conditions environmentally and within segments in marathon races. These devices have the potential to enhance performance optimization by offering valuable insights to both the runner and the coach. Better yet, with social media integrations such as Strava®, we are now kept motivated by each other through wearable technology integrations with the app - thus, running has never been more fun that it is currently. 

 

 

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References: 

  1. Bardyn F, Savary M, Grassi S, Farine PA, Fasel B, Aminian K. MEMS inertial motion sensing watch for measuring walking and running activities. In: IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation. Institute of Electrical and Electronics Engineers Inc.; 2016. p. 104–9.
  2. Bhargava N, Cuzzolin F. Challenges and Opportunities for Computer Vision in Real-life Soccer Analytics. 2020 Apr 13; Available from: http://arxiv.org/abs/2004.06180
  3. Düking P, Fuss FK, Holmberg HC, Sperlich B. Recommendations for assessment of the reliability, sensitivity, and validity of data provided by wearable sensors designed for monitoring physical activity. JMIR Mhealth Uhealth. 2018 Apr 1;6(4).
  4. Taborri J, Keogh J, Kos A, Santuz A, Umek A, Urbanczyk C, et al. Sport biomechanics applications using inertial, force, and EMG sensors: A literature overview. Appl Bionics Biomech. 2020;2020.
  5. Gilgen-Ammann R, Schweizer T, Wyss T. Accuracy of distance recordings in eight positioning-enabled sport watches: Instrument validation study. JMIR Mhealth Uhealth. 2020 Jun 1;8(6).
  6. Duncan S, Stewart TI, Oliver M, Mavoa S, MacRae D, Badland HM, et al. Portable global positioning system receivers: Static validity and environmental conditions. Am J Prev Med. 2013 Feb;44(2).
  7. Ranacher P, Brunauer R, Trutschnig W, Van der Spek S, Reich S. Why GPS makes distances bigger than they are. International Journal of Geographical Information Science. 2016 Feb 1;30(2):316–33.
  8. Johansson RE, Adolph ST, Swart J, Lambert MI. Accuracy of GPS sport watches in measuring distance in an ultramarathon running race. Int J Sports Sci Coach. 2020 Apr 1;15(2):212–9.