Article

# Running power meters and theoretical models based on laws of physics: Effects of environments and running conditions

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## Abstract

Highlights • Theoretical power models, based on laws of physics, would represent interesting proposals to examine the sensitivity of running power devices. • Running power output estimated by commercial technologies are particularly influenced by environment (indoor vs. outdoor) and running conditions (body weight, slope and running speed). • The PolarV, and above all the Stryd device, are the most sensitive technologies for running power measurement in different environments and running conditions Key words: endurance, accelerometer, variability, physiology, biomechanics

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... Whereas three of those studies [11,27,28] examine the PW kinetics during different running protocols, the other four studies [15,25,26,29] investigate the relationship between PW and physiological parameters such as oxygen consumption (VO2) at different intensities. Additionally, two further works [30,31] analyse the application of mathematical models, based on power laws, to predict running performance, whereas a recent study [32] ...
... Whereas three of those studies [11,27,28] examine the PW kinetics during different running protocols, the other four studies [15,25,26,29] investigate the relationship between PW and physiological parameters such as oxygen consumption (VO 2 ) at different intensities. Additionally, two further works [30,31] analyse the application of mathematical models, based on power laws, to predict running performance, whereas a recent study [32] assesses the agreement level between two mathematical models and five power meter devices through different running conditions. Other studies examined some parameters provided by the RunScribe power meter to describe the effects of the fatigue induced over a marathon [33,34] and the influence of different types of ankle treatments on running biomechanics [35]. ...
... The Stryd system showed the higher concurrent validity to the VO 2 (r ≥ 0.911) between the five wearables, and it was also found as the more repeatable and sensitive in all the conditions studied. Furthermore, the level of agreement between these 5 wearable systems was also analysed against two physics theoretical models for PW estimation [10,52] in different running conditions [32], showing that the Stryd and Polar Vantage systems are the most sensitive tools for PW estimation in running given their close agreement with both theoretical models (r > 0.93). The Stryd power meter estimates power production while running separating this metric into two parts: power and form power. Apparently, power reflects the PW associated with changes in the athlete's horizontal movement, while form power represents the power production originated by the combination of the oscillatory up and down movements of the centre of mass and lateral power as the athlete moves forward. ...
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Mechanical power may act as a key indicator for physiological and mechanical changes during running. In this scoping review, we examine the current evidences about the use of power output (PW) during endurance running and the different commercially available wearable sensors to assess PW. The Boolean phrases endurance OR submaximal NOT sprint AND running OR runner AND power OR power meter, were searched in PubMed, MEDLINE, and SCOPUS. Nineteen studies were finally selected for analysis. The current evidence about critical power and both power-time and power-duration relationships in running allow to provide coaches and practitioners a new promising setting for PW quantification with the use of wearable sensors. Some studies have assessed the validity and reliability of different available wearables for both kinematics parameters and PW when running but running power meters need further research before a definitive conclusion regarding its validity and reliability.
... 21 Since its market launch, knowing which type of power Stryd reports has been of great interest among the running community. Cerezuela-Espejo et al 7,22 determined the relationship between the power output reported from 5 commercial power meters and 2 theoretical power models varying in speed, weight, and slope. The Stryd power meter showed the greatest sensitivity to these factors among the other meters (r ≥ .947), ...
... showing that this device reported external work. 22 Thus, the power output (in watts per kilogram) reported by Stryd has shown a great relationship with VO 2 (in milliliters per kilogram per minute) and running velocity (in kilometers per hour) when measured during a GXT varying in speed as well as in the present study (r 2 = .97 and .99, ...
Purpose: The critical power (CP) concept has been extended from cycling to the running field with the development of wearable monitoring tools. Particularly, the Stryd running power meter and its 9/3-minute CP test is very popular in the running community. Locating this mechanical threshold according to the physiological landmarks would help to define each boundary and intensity domain in the running field. Thus, this study aimed to determine the CP location concerning anaerobic threshold, respiratory compensation point (RCP), and maximum oxygen uptake (VO2max). Method: A group of 15 high-caliber athletes performed the 9/3-minute Stryd CP test and a graded exercise test in 2 different testing sessions. Results: Anaerobic threshold, RCP, and CP were located at 73% (5.41%), 86.82% (3.85%), and 88.71% (5.84%) of VO2max, respectively, with a VO2max of 66.3 (7.20) mL/kg/min. No significant differences were obtained between CP and RCP in any of its units (ie, in watts per kilogram and milliliters per kilogram per minute; P ≥ .184). Conclusions: CP and RCP represent the same boundary in high-caliber athletes. These results suggest that coaches and athletes can determine the metabolic perturbance threshold that CP and RCP represent in an easy and accessible way.
... Notbaly, all of the aforementioned studies were completed in laboratories, as the comparison to the gold standard method (treadmill and motion capture) was the main goal. Recent studies shown that RunScribe outcomes are dependent on running speed (Napier et al., 2021), surface (Hollis et al., 2021) and running environment (Cerezuela-Espejo et al., 2020). Therefore, such factors need to be considered in further research and practice. ...
... Another problem with the wearable sensors mounted on the shoe is that the actual shock variables experienced by the leg appear to be overestimated (Cheung et al., 2019). Power output is another outcome that has been a subject of studies using RunScribe, both for treadmill and outdoor running (Cerezuela-Espejo et al., 2020, however, the reported validity was poor. The reliability of power was unacceptable during the half-marathon pace within the session (TE = 14.3 %), as well as in all conditions between the sessions (TE = 13.1-13.8 ...
Article
The aim of this study was to investigate the reliability of running biomechanics assessment with a wearable commercial sensor (RunScribeTM). Participants performed multiple 200-m runs over sand, grass and asphalt ground at the estimated 5-km tempo, with an additional trial with 21-km tempo at the asphalt. Intra-session reliability was excellent for all variables at 5-km pace (intra-class coefficient correlation (ICC) asphalt: 0.90–0.99; macadam: 0.94–1.00; grass: 0.92–1.00), except for shock (good; ICC = 0.83), and contact time and total power output (moderate; ICC = 0.68–0.71). Coefficient of variation (CV) were mostly acceptable in all conditions, except for horizontal ground reaction force (GRF) rate in asphalt 5-km pace trial (CV = 24.5 %), power (CV = 14.3 %) and foot strike type (CV = 30.9 %) in 21-km pace trial, and horizontal GRF rate grass trial (CV = 15.7 %). Inter-session reliability was high or excellent for the majority of the outcomes (ICC≥0.85). Total power output (ICC = 0.56–0.65) and shock (ICC = 0.67–0.75) showed only moderate reliability across all conditions. Power (CV = 12.5–13.8 %), foot strike type (CV = 14.9–29.4 %) and horizontal ground reaction force rate (CV = 12.4–36.4 %) showed unacceptable CV.
... Knowledge of the reliability and validity of these IMU devices is of paramount importance to collect and interpret data accurately. Some researchers have analyzed the Stryd's reliability and validity during running [2,5,[8][9][10][11]. However, the reliability and validity have been less investigated during walking [12,13], and never during walking on positive slopes using different backpack loads. ...
Article
Background: The Styrd Power Meter is gaining special interest for on-field gait analyses due to its low-cost and general availability. However, the reliability and validity of the Stryd during walking on positive slopes using different backpack loads have never been investigated. Research Question: Is the Stryd Power Meter reliable and valid to quantify gait mechanics during walking on positive inclines and during level walking incorporating load carriage? Methods: Seventeen participants from a police force rescue team performed 8 submaximal walking trials for 5-min at 3.6 km•h-1 during different positive slope (1, 10 and 20%) and backpack load (0, 10, 20, 30 and 40% of body mass) conditions. Two Stryd devices were utilized for reliability analyses. Validity of cadence and ground contact time (GCT) were analyzed against a gold standard device (Optojump). Results: The Stryd demonstrated acceptable reliability [mean bias: <2.5%; effect size (ES): <0.25; standard error of the mean: <1.7%; r: >0.76] for power, cadence, and GCT. Validity measures (mean bias: <0.8%; ES: <0.07; r: >0.96; Lin’s Concordance Coefficient: 0.96; Mean Absolute Percent Error: <1%) for cadence were also found to be acceptable. The Stryd overestimated (P < 0.001; ES: >5.1) GCT in all the walking conditions. A significant systematic positive bias (P < 0.022; r = 0.56 to 0.76) was found in 7 conditions. Significance: The Stryd Power Meter appears to produce reliable measurements for power output, cadence and GCT. The Stryd produced valid measurements for cadence during walking on positive slopes and during level walking with a loaded backpack. However, the Stryd is not valid for measuring GCT during these walking conditions. This study adds novel data regarding the reliability and validity of this device and might be of particular interest for scientists, practitioners, and first responders seeking reliable devices to quantify gait mechanics during walking.
... In different environments and running conditions, one study assessed the level of agreement between the power output data estimated by five commercial technologies and the two main international theoretical models based on laws of physics. The results showed that the Stryd and PolarV technologies were the most sensitive to the running conditions and environments [16]. ...
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Background: Running biomechanics have traditionally been analyzed in laboratory settings, but this may not reflect natural running gait. Wearable sensors may offer an alternative. Methods: A concurrent validation study to determine agreement between the RunScribe<sup>TM</sup> wearable sensor (triaxial accelerometer and gyroscope) and the 3D motion capture system was conducted. Twelve injury-free participants (6 males, 6 females; age = 23.1 ± 5.5 years, weekly mileage = 16.1 ± 9.3) ran 1.5 miles on a treadmill. Ten consecutive strides from each limb were collected, and the mean values were analyzed. Pronation excursion, maximum pronation velocity, contact time, and cycle time were compared between measurement platforms using intraclass correlation coefficients (ICC) and Bland-Altman analyses. Results: Excellent ICC estimates were found for maximum pronation velocity, contact time, and cycle time. Pronation excursion demonstrated fair ICC estimates. The mean differences between platforms were small with limits of agreement clustered around zero, except for contact time measures which were consistently higher with the RunScribe compared to the camera-based system. Conclusion: Our study revealed that the RunScribe wearable device showed good to excellent concurrent validity for maximum pronation velocity, contact time, and cycle time; however, direct comparisons or results between the two platforms should not be used.
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Aubry, RL, Power, GA, and Burr, JF. An assessment of running power as a training metric for elite and recreational runners. J Strength Cond Res XX(X): 000-000, 2018-Power, as a testing and training metric to quantify effort, is well accepted in cycling, but is not commonly used in running to quantify effort or performance. This study sought to investigate a novel training tool, the Stryd Running Power Meter, and the applicability of running power (and its individually calculated run mechanics) to be a useful surrogate of metabolic demand (V[Combining Dot Above]O2), across different running surfaces, within different caliber runners. Recreational (n = 13) and elite (n = 11) runners completed a test assessing V[Combining Dot Above]O2 at 3 different paces, while wearing a Stryd Power Meter on both an indoor treadmill and an outdoor track, to investigate relationships between estimated running power and metabolic demand. A weak but significant relationship was found between running power and V[Combining Dot Above]O2 considering all participants as a homogenous group (r = 0.29); however, when assessing each population individually, no significant relationship was found. Examination of the individual mechanical components of power revealed that a correlative decrease in V[Combining Dot Above]O2 representing improved efficiency was associated with decreased ground contact time (r = 0.56), vertical oscillation (r = 0.46), and cadence (r = 0.37) on the treadmill in the recreational group only. Although metabolic demand differed significantly between surfaces at most speeds, run power did not accurately reflect differences in metabolic cost between the 2 surfaces. Running power, calculated via the Stryd Power Meter, is not sufficiently accurate as a surrogate of metabolic demand, particularly in the elite population. However, in a recreational population, this training tool could be useful for feedback on several running dynamics known to influence running economy.
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Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best method- ologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the eld has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on “Monitoring Athlete Training Loads—The Hows and the Whys” was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary prac- tices in this rapidly growing eld and also to investigate where it may branch to in the future. This consensus statement brings together the key ndings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.
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Performance testing is one of the most common and important measures used in sports science and physiology. Performance tests allow for a controlled simulation of sports and exercise performance for research or applied science purposes. There are three factors that contribute to a good performance test: (i) validity; (ii) reliability; and (iii) sensitivity. A valid protocol is one that resembles the performance that is being simulated as closely as possible. When investigating race-type events, the two most common protocols are time to exhaustion and time trials. Time trials have greater validity than time to exhaustion because they provide a good physiological simulation of actual performance and correlate with actual performance. Sports such as soccer are more difficult to simulate. While shuttle-running protocols such as the Loughborough Intermittent Shuttle Test may simulate physiology of soccer using time to exhaustion or distance covered, it is not a valid measure of soccer performance. There is a need to include measures of skill in such protocols. Reliability is the variation of a protocol. Research has shown that time-to-exhaustion protocols have a coefficient of variation (CV) of >10%, whereas time trials are more reliable as they have been shown to have a CV of <5%. A sensitive protocol is one that is able to detect small, but important, changes in performance. The difference between finishing first and second in a sporting event is <1%. Therefore, it is important to be able to detect small changes with performance protocols. A quantitative value of sensitivity may be accomplished through the signal : noise ratio, where the signal is the percentage improvement in performance and the noise is the CV.
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Stages, and Garmin Vector Power Meters in Comparison With the SRM Device
• A Bouillod
• J Pinot
• G Soto-Romero
• W Bertucci
• F Grappe
• Validity
• Reproducibility Sensitivity
• Robustness Of The Powertap
A. Bouillod, J. Pinot, G. Soto-Romero, W. Bertucci, F. Grappe, Validity, Sensitivity, Reproducibility, and Robustness of the PowerTap, Stages, and Garmin Vector Power Meters in Comparison With the SRM Device, Int. J. Sports Physiol. Perform. 12 (2017) 1023-1030. https://doi.org/10.1123/ijspp.2016-0436.
Table 2 Agreement between running power (P W ) estimated by each technology and the theoretical model of Dijk and Megen (TP W1 ), in different environments (indoor and outdoor) and running conditions (increasing speed, body weight, and slope)
• Megen Dijk
Dijk, Megen, The secret of running : maximum performance gains through effective power metering and training analysis, (2017) 477. https://thesecretofrunning.com/ Table 2 Agreement between running power (P W ) estimated by each technology and the theoretical model of Dijk and Megen (TP W1 ), in different environments (indoor and outdoor) and running conditions (increasing speed, body weight, and slope). (accessed May 29, 2019).