No abstract

Background Elite athletes and recreational runners rely on the accuracy of global navigation satellite system (GNSS)–enabled sport watches to monitor and regulate training activities. However, there is a lack of scientific evidence regarding the accuracy of such sport watches. Objective The aim was to investigate the accuracy of the recorded distances obtained by eight commercially available sport watches by Apple, Coros, Garmin, Polar, and Suunto when assessed in different areas and at different speeds. Furthermore, potential parameters that affect the measurement quality were evaluated. Methods Altogether, 3 × 12 measurements in urban, forest, and track and field areas were obtained while walking, running, and cycling under various outdoor conditions. Results The selected reference distances ranged from 404.0 m to 4296.9 m. For all the measurement areas combined, the recorded systematic errors (±limits of agreements) ranged between 3.7 (±195.6) m and –101.0 (±231.3) m, and the mean absolute percentage errors ranged from 3.2% to 6.1%. Only the GNSS receivers from Polar showed overall errors <5%. Generally, the recorded distances were significantly underestimated (all P values <.04) and less accurate in the urban and forest areas, whereas they were overestimated but with good accuracy in 75% (6/8) of the sport watches in the track and field area. Furthermore, the data assessed during running showed significantly higher error rates in most devices compared with the walking and cycling activities. Conclusions The recorded distances might be underestimated by up to 9%. However, the use of all investigated sport watches can be recommended, especially for distance recordings in open areas.

The provision of aF about GCT seems to be a promising approach that should be considered during training practice of well-trained runners.

Background Sport watches and fitness trackers provide a feasible way of obtaining energy expenditure (EE) estimations in daily life as well as during exercise. However, today’s popular wrist-worn technologies show only poor-to-moderate EE accuracy. Recently, the invention of optical heart rate measurement and the further development of accelerometers in wrist units have opened up the possibility of measuring EE. Objective This study aimed to validate the new multisensory wristwatch Polar Vantage and its EE estimation in healthy individuals during low-to-high-intensity activities against indirect calorimetry. Methods Overall, 30 volunteers (15 females; mean age 29.5 [SD 5.1] years; mean height 1.7 [SD 0.8] m; mean weight 67.5 [SD 8.7] kg; mean maximal oxygen uptake 53.4 [SD 6.8] mL/min·kg) performed 7 activities—ranging in intensity from sitting to playing floorball—in a semistructured indoor environment for 10 min each, with 2-min breaks in between. These activities were performed while wearing the Polar Vantage M wristwatch and the MetaMax 3B spirometer. Results After EE estimation, a mean (SD) of 69.1 (42.7) kcal and 71.4 (37.8) kcal per 10-min activity were reported for the MetaMax 3B and the Polar Vantage, respectively, with a strong correlation of r=0.892 (P<.001). The systematic bias was 2.3 kcal (3.3%), with 37.8 kcal limits of agreement. The lowest mean absolute percentage errors were reported during the sitting and reading activities (9.1%), and the highest error rates during household chores (31.4%). On average, 59.5% of the mean EE values obtained by the Polar Vantage were within ±20% of accuracy when compared with the MetaMax 3B. The activity intensity quantified by perceived exertion (odds ratio [OR] 2.028; P<.001) and wrist circumference (OR −1.533; P=.03) predicted 29% of the error rates within the Polar Vantage. Conclusions The Polar Vantage has a statistically moderate-to-good accuracy in EE estimation that is activity dependent. During sitting and reading activities, the EE estimation is very good, whereas during nonsteady activities that require wrist and arm movement, the EE accuracy is only moderate. However, compared with other available wrist-worn EE monitors, the Polar Vantage can be recommended, as it performs among the best.

Purpose: To quantify gait asymmetry in well-trained runners with and without previous injuries during interval training sessions incorporating different distances. Methods: Twelve well-trained runners participated in 8 high-intensity interval-training sessions on a synthetic track over a 4-wk period. The training consisted of 10 × 400, 8 × 600, 7 × 800, and 6 × 1000-m running. Using an inertial measurement unit, the ground-contact time (GCT) of every step was recorded. To determine gait asymmetry, the GCTs between the left and right foot were compared. Results: Overall, gait asymmetry was 3.3% ± 1.4%, and over the course of a training session, the gait asymmetry did not change (F 1,33 = 1.673, P = .205). The gait asymmetry of the athletes with a previous history of injury was significantly greater than that of the athletes without a previous injury. However, this injuryrelated enlarged asymmetry was detectable only at short (400 m), but not at longer, distances (600-1000 m). Conclusion: The gait asymmetry of well-trained athletes differed, depending on their history of injury and the running distance. To detect gait asymmetries, high-intensity runs over relatively short distances are recommended.Keywords: imbalance, field condition, fatigue, inertial measurement unit, high performance Athletes and coaches assume that gait asymmetry affects athletic performance, as 1 of the lower limbs is exposed to more stress than the other. 1,2 Gait asymmetry can be the primary cause of an injury and it can be responsible for an injury. 1,3,4 Previously, gait asymmetries ranging from 3% for knee angle at touchdown to 54% for hip-angle velocity were reported in female runners, 5,6 suggesting that a single threshold level of normal to problematic gait asymmetry does not exist and that there are wide variations in gait mechanics and asymmetries. 1,18 Also, gait asymmetry may not be evident at the beginning of a race but may emerge with fatigue. Regarding injury history, some earlier studies of athletes with and without a previous injury found no differences in gait asymmetry. 1,7,8 However, all the subjects in the aforementioned studies were either novice runners, 7 the assessments took place in a laboratory setting (on a treadmill) at submaximal speeds only, 1,7-9 and only 1 trial 10 or a few gait cycles 9 were analyzed. Consequently, it is unclear whether these results are congruent with real practice during training or competition on realistic floor conditions. For instance, a previous study provided evidence that gait asymmetry is reduced on a treadmill. 11 Hence, to better understand the occurrence of gait asymmetry, data from well-trained runners over entire runs over various distances, at high speeds, and at high intensities need to be obtained in field measurements.The purpose of this study therefore was threefold: to quantify gait asymmetry in healthy well-trained runners during high-intensity track runs of different lengths and speeds (400-1000 m), to evaluate the effect of an injury in the previous 24 months on gait as...