Running power meters and theoretical models based on laws of physics: Effects of environments and running conditions - Cerezuela-Espejo, V.; Hernández-Belmonte, A.; Courel-Ibanez, J.; Conesa-Ros, E.; Martinez-Cava, A.; Pallarés, J. G. (Physiology & Behavior, 2020)
Training prescription and load monitoring in running activities have benefited from power output (PW) data offered by new technologies. Nevertheless, to date, the sensitivity of PW data provided by these tools is still not completely clear. The aim of this study was to analyze the level of agreement between the PW estimated by five commercial technologies and the two main internationally theoretical models based on laws of physics, in different environments and running conditions. Ten endurance-trained male athletes performed three submaximal running protocols on a treadmill (indoor) and an athletic track (outdoor), with changes in speed, body weight, and slope. PW was simultaneously registered by the commercial technologies Stryd (StrydApp and StrydWatch), RunScribe, GarminRP and PolarV, whereas theoretical power output (TPW) was calculated by the two mathematical models (TPW1 and TPW2). Statistics included, among others, the Pearson's correlation coefficient (r) and standard error of measurement (SEM). The PolarV, and above all Stryd, showed the closest agreement with the TPW1 (Stryd: r = 0.947, SEM = 11 W; PolarV: r = 0.931, SEM = 64 W) and TPW2 (Stryd: r = 0.933, SEM = 60 W; PolarV: r = 0.932, SEM = 24 W), both indoors and outdoors. On the other hand, the devices GarminRP (r = 0.765, SEM = 59 W) and RunScribe. (r = 0.508, SEM = 125 W) showed the lowest agreement with the TPW1 and TPW2 models for all conditions and environments analyzed. The closest agreement of the Stryd and PolarV technologies with the TPW1 and TPW2 models suggest these tools as the most sensitive, among those analyzed, for PW measurement when changing environments and running conditions.