Training prescription in running activities have benefited from power output (P W ) data obtained by new technologies. Nevertheless, to date, the suitability of P W data provided by these tools is still uncertain. The present study aimed to: (i) analyze the repeatability of five commercially available technologies for running P W estimation, and (ii) examine the concurrent validity through the relationship between each technology P W and oxygen uptake (VO 2 ). On two occasions (test-retest), twelve endurance-trained male athletes performed on a treadmill (indoor) and an athletic track (outdoor) three submaximal running protocols with manipulations in speed, body weight and slope. P W was simultaneously registered by the commercial technologies Stryd App , Stryd Watch , RunScribe, Garmin RP and Polar V , while VO 2 was monitored by a metabolic cart. Test-retest data from the environments (indoor and outdoor) and conditions (speed, body weight and slope) were used for repeatability analysis, which included the standard error of measurement (SEM), coefficient of variation (CV) and intraclass correlation coefficient (ICC). A linear regression analysis and the standard error of estimate (SEE) were used to examine the relationship between P W and VO 2 . Stryd device was found as the most repeatable technology for all environments and conditions (SEM ≤ 12.5 W, CV ≤ 4.3%, ICC ≥ 0.980), besides the best concurrent validity to the VO 2 (r ≥ 0.911, SEE ≤ 7.3%). On the contrary, although the Polar V , Garmin RP and RunScribe technologies maintain a certain relationship with VO 2 , their low repeatability questions their suitability. The Stryd can be considered as the most recommended tool, among the analyzed, for P W measurement.

Hernández-Belmonte, A, Courel-Ibáñez, J, Conesa-Ros, E, Martínez-Cava, A, and Pallarés, JG. Level of effort: A reliable and practical alternative to the velocity-based approach for monitoring resistance training. J Strength Cond Res 36(11): 2992–2999, 2022—This study analyzed the potential of the level of effort methodology as an accurate indicator of the programmed relative load (percentage of one-repetition maximum [%1RM]) and intraset volume of the set during resistance training in the bench press, full squat, shoulder press, and prone bench pull exercises, through 3 specific objectives: (a) to examine the intersubject and intrasubject variability in the number of repetitions to failure (nRM) against the actual %1RM lifted (adjusted by the individual velocity), (b) to investigate the relationship between the number of repetitions completed and velocity loss reached, and (c) to study the influence of the subject's strength level on the aforementioned parameters. After determining their individual load-velocity relationships, 30 subjects with low (n = 10), medium (n = 10), and high (n = 10) relative strength levels completed 2 rounds of nRM tests against their 65, 75, 85, and 95% 1RM in the 4 exercises. The velocity of all repetitions was monitored using a linear transducer. Intersubject and intrasubject variability analyses included the 95% confidence intervals (CIs) and the the standard error of measurement (SEM), respectively. Coefficient of determination (R2) was used as the indicator of relationship. nRM showed a limited intersubject (CI ≤ 4 repetitions) and a very low intrasubject (SEM ≤1.9 repetitions) variability for all the strength levels, %1RM, and exercises analyzed. A very close relationship (R2 ≥ 0.97) between the number of repetitions completed and the percentage of velocity loss reached (from 10 to 60%) was found. These findings strengthen the level of effort as a reliable, precise, and practical strategy for programming resistance training.

This experiment investigates the validity of six thermometers with different measuring sensors, operation and site of application, to estimate core temperature (T) in comparison to an ingestible thermometric sensor based on quartz crystal technology. Measurements were obtained before, during and after exercise in the heat, controlling the presence of air-cooling and skin sweating. Twelve well-trained men swallowed the ingestible thermometer 6 h before the trial. After pre-exercise resting measurements at 20 °C, subjects entered a heat chamber held at 40 °C. Exercise in the heat consisted of 60 min of pedalling on cycle ergometer at 90% of the individually determined first ventilatory threshold. Results reveal that wind and skin sweat invalidate the use of skin infrared thermometry to estimate T during exercise in the heat. However, better T estimations were obtained in wind-restricted situations. We detected important differences between same-technology devices but different models and brands. In conclusion, there are important limitations to assess T accurately using non-invasive thermometers during and after exercise in the heat. Because some devices showed better validity than others did, we recommended using tympanic Braun, and non-contact skin infrared Medisana or Visiofocus in wind-restricted and no sweat conditions to estimate T during exercise in the heat.

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