Is Running Power a Useful Metric? Quantifying Training Intensity and Aerobic Fitness Using Stryd Running Power Near the Maximal Lactate Steady State

e sought to determine the utility of Stryd, a commercially available inertial measure- ment unit, to quantify running intensity and aerobic tness. Fifteen (eight male, seven female) runners (age = 30.2 [4.3] years; V O 2max = 54.5 [6.5] mL kg 1 min 1 ) performed moderate- and heavy-intensity step transitions, an incremental exercise test, and constant-speed running trials to establish the maximal lactate steady state (MLSS). Stryd running power stability, sensitivity, and reliability were evaluated near the MLSS. Stryd running power was also compared to running speed, V O 2, and metabolic power measures to estimate running mechanical ef ciency (EFF) and to deter- mine the ef cacy of using Stryd to delineate exercise intensities, quantify aerobic tness, and estimate running economy (RE). Stryd running power was strongly associated with V O 2(R 2 = 0.84;p< 0.001) and running speed at the MLSS (R 2 = 0.91;p< 0.001). Stryd running power measures were strongly correlated

estimate running mechanical ef ciency (EFF) and to deter- mine the ef cacy of using Stryd to delineate exercise intensities, quantify aerobic tness, and estimate running economy (RE). Stryd running power was strongly associated with V O 2(R 2 = 0.84;p< 0.001) and running speed at the MLSS (R 2 = 0.91;p< 0.001). Stryd running power measures were strongly correlated with RE at the MLSS when combined with metabolic data (R 2 = 0.79;p< 0.001) but not in isolation from the metabolic data (R 2 = 0.08;p= 0.313). Measures of running EFF near the MLSS were not different across intensities (~21%;p> 0.05). In conclusion, although Stryd could not quantify RE in isolation, it provided a stable, sensitive, and reliable metric that can estimate aerobic tness, delineate exercise intensities, and approximate the metabolic requirements of running near the MLSS. Keywords:wearable technology; running economy; critical intensity; human performance; inertial measurement unit; treadmill 1. Introduction A consensus regarding an approach to evaluate mechanical running power output (PO) is lacking, resulting in a range of PO values for a given running speed, depending on the method [1,2]. During level running, the working muscles transfer energy to produce and absorb the forces needed to move body segments. As a result, there is no dissipative load external to the body that can be measured to quantify mechanical PO. Instead, running mechanical PO measurements may be derived from “external” or “internal” work per- spectives by evaluating the centre of mass (CoM) or the body segments, respectively [1–3]. Such approaches require sophisticated laboratory assessments of joint kinetics and/or kine- matics based on ground reaction force and motion-capture data. Several methodological challenges also limit the utility of running mechanical PO to approximate the metabolic work rate [1,3], and, in contrast to cycling, where there is a strong relationship between mechanical and metabolic PO [4,5], many factors complicate the relationship between me- chanical and metabolic PO when running [6–8]. Nevertheless, a wearable running device that can quantify and monitor training intensity, analogous to a cycling power meter [9,10], would be useful to guide training and maximize running performance. Sensors2023,23, 8729.

contrast to cycling, where there is a strong relationship between mechanical and metabolic PO [4,5], many factors complicate the relationship between me- chanical and metabolic PO when running [6–8]. Nevertheless, a wearable running device that can quantify and monitor training intensity, analogous to a cycling power meter [9,10], would be useful to guide training and maximize running performance. Sensors2023,23, 8729.

Sensors2023,23, 8729 2 of 19 Several consumer technologies providing a running power metric have been devel- oped [11,12]. These technologies derive a measurement of mechanical PO using estimates of ground reaction forces, CoM velocity, and/or vertical displacement from global position- ing system (GPS) and/or inertial measurement unit (IMU) sensor data [11–13]. Previously, the Stryd running power device (a portable IMU), has provided the closest relationship with V O2when compared to other available commercial devices [11]. Possibly by gen- erating a running power metric based on estimates of horizontal velocity and vertical displacement using acceleration data, it is purported that Stryd power can be used as a proxy for metabolic PO, despite changes in external conditions such as air resistance or gradient [13]. Thus, Stryd running power can theoretically quantify training intensity in a manner analogous to cycling mechanical PO and could be superior to conventional measurement approaches using running speed. Despite evidence of repeatability [11], reliability [14,15], stability during prolonged running [16], and strong linear correlations with running speed [17,18], limited research has investigated the Stryd running metric at stable metabolic work rates relative to exercising thresholds. Thus, to determine the utility of Stryd power to indicate relative exercise intensity and assess running tness and performance, the relationship between Stryd mechanical power and metabolic power needs to be established using an exercise intensity domain training approach (i.e., evaluating running power metrics during steady-state exercise relative to the gas exchange threshold (GET) and maximal metabolic steady state (MMSS)). Prior to determining whether Stryd running power can monitor training, like cycling power output, in uncontrolled environments (e.g., variable inclines, wind speeds, and surfaces), the primary purpose of the present study was to evaluate the Stryd power metric in a controlled environment (i.e., in situ). Using an exercise intensity domain approach, we assessed the stability, sensitivity, and reliability of Stryd at stable metabolic work rates to (i) determine the ef cacy of Stryd running power as a training intensity and running performance metric, (ii) explore the relationship between running power and running economy (RE), (iii) estimate mechanical ef ciency during constant-speed treadmill running,

in situ). Using an exercise intensity domain approach, we assessed the stability, sensitivity, and reliability of Stryd at stable metabolic work rates to (i) determine the ef cacy of Stryd running power as a training intensity and running performance metric, (ii) explore the relationship between running power and running economy (RE), (iii) estimate mechanical ef ciency during constant-speed treadmill running, and (iv) contrast steady-state measurements with measurements derived from incremental exercise. We hypothesized that Stryd running power would be repeatable across two visits, stable during a 30-min run, and sensitive to running speeds near the maximal lactate steady state (MLSS)—a proxy measure of the MMSS. In addition, we hypothesized that Stryd power would be strongly associated with running speed, V O2, and RE measurements, thereby providing a tool to guide exercise training and assess running tness. 2. Materials and Methods 2.1. Participants Fifteen (8 male; 7 female) recreationally active or trained/developmental runners [19] (mean [SD]; age = 30.2 [4.3] years; body mass = 68.8 [8.2] kg; height = 173.2 [8.4] cm; V O2max, 54.5 [6.5] mL kg 1 min 1 ) were recruited using convenience sampling. Partic- ipants were included if they were healthy, uninjured, and between 18 and 45 years of age, with recent 10-km performances of 50 min and 55 min for males and females, respectively. Within the 3 months prior to testing, runners reported exercising an average of 3.5 [1.4] days per week, running an average of 27.7 [17.1] km each week, and having 10-km best performance times of 44.6 [6.5] min. Written informed consent was provided by the runners to participate in the experimental procedures, which were approved by the University of Calgary Conjoint Health Research Ethics Board (REB20-0111) and conducted in accordance with the declaration of Helsinki, except for pre-trial registration. Participants had the option to cease participation at any time during the experimental procedures. Prior to test administration, runners completed the physical activity readiness questionnaire (PAR-Q+) to identify contraindications to exercise testing and to ensure that participants were free of medical conditions and injuries that could interfere with metabolic and car-

of Helsinki, except for pre-trial registration. Participants had the option to cease participation at any time during the experimental procedures. Prior to test administration, runners completed the physical activity readiness questionnaire (PAR-Q+) to identify contraindications to exercise testing and to ensure that participants were free of medical conditions and injuries that could interfere with metabolic and car-

Sensors2023,23, 8729 3 of 19 diorespiratory exercise responses. All runners provided their own lightweight running shoes and wore the same shoes for all testing sessions. 2.2. Experimental Design Runners visited the laboratory for ve to six exercise testing sessions, with a minimum of 48 h between visits. The exercise sessions included: (1) a “Step-Ramp-Step” (SRS) exercise test to determine maximal exercising parameters [20]; (2) a series of 3–4 constant-speed bouts to determine the MLSS; and (3) a repeated trial at the MLSS running speed. Runners were asked to refrain from smoking, eating, or consuming caffeine within 2 h prior to their testing sessions. Runners did not engage in strenuous exercise on the same day as the testing sessions. A manuscript validating the SRS approach to identify the running speed and Stryd running power associated with the MLSS has been published [20]; however, despite the overlap in experimental procedures, the results presented herein are distinct. 2.3. Exercise Protocols 2.3.1. Step-Ramp-Step (SRS) Protocol As described in detail in our previous study [20], runners performed an SRS exercise protocol during their rst testing visit to establish their maximal exercising values and estimate the running speed associated with the MLSS. This SRS protocol was modi ed for treadmill running from a cycle ergometer-based method [21]. Of relevance to the present study, the SRS protocol involved a moderate-intensity step-transition (MOD; 6 min at 1.9 m s 1 , 6 min at 2.4 m s 1 , and 6 min at 1.9 m s 1 ); an incremental treadmill running test (an initial speed of 1.9 m s 1 , increasing by ~0.2 m s 1 (i.e., 0.5 mph) per min, until volitional exhaustion); and a heavy-intensity step transition (HVY; 4 min of treadmill running at 1.9 m s 1 , followed by 12 min of treadmill running at a speed associated with the heavy-intensity exercise domain). The incremental treadmill test immediately preceded the MOD step, but the participants recovered passively for 30 min between the incremental test and the HVY step. The SRS protocol facilitated the identi cation of the MLSS in 2–3 constant-speed trials

1.9 m s 1 , followed by 12 min of treadmill running at a speed associated with the heavy-intensity exercise domain). The incremental treadmill test immediately preceded the MOD step, but the participants recovered passively for 30 min between the incremental test and the HVY step. The SRS protocol facilitated the identi cation of the MLSS in 2–3 constant-speed trials [20]. 2.3.2. Constant-Speed Treadmill Running—MLSS Determination Following the initial SRS testing visit, runners completed the constant-speed exercise sessions during 4 to 5 separate visits to the lab. These visits consisted of 5 min of treadmill running at 1.9 m s 1 , followed by treadmill running at the predetermined testing speed. During all constant-speed testing visits, participants were encouraged to run until volitional exhaustion, up to a maximum duration of 45 min (excluding warm-up). Data collected beyond 30 min were not used in this study. All runners performed their initial constant- speed test at the running speed estimated to be the MLSS by the SRS protocol. Depending on whether the difference between the 10- and 30-min blood lactate concentrations ([BLa]) was 1 mmol L 1 or >1 mmol L 1 , the subsequent visit was performed at a treadmill speed that was 5% faster or 5% slower, respectively. The MLSS for each runner was identi ed as the highest treadmill speed whereby at least 30 min of exercise was performed and the difference between the [Bla] at 10 and 30 min was 1 mmol L 1 [22]. All participants performed constant-speed treadmill running trials at the MLSS, 5% above the MLSS, 5% below the MLSS, and once more at the MLSS. Data analysis was primarily based on data collected at the 10- and 30-min (or at task failure if <30 min) time points. 2.4. Equipment and Measurements 2.4.1. Cardiorespiratory Measurements All exercise sessions were performed on a treadmill (Desmo Pro Evo, Woodway USA Inc., Waukesha, WI, USA) with an incline set to a 1% gradient [23]. Adjustments to treadmill speed could be made in 0.1 mph increments (i.e., ~0.04 m s 1 ); however, all running speed data were reported

min) time points. 2.4. Equipment and Measurements 2.4.1. Cardiorespiratory Measurements All exercise sessions were performed on a treadmill (Desmo Pro Evo, Woodway USA Inc., Waukesha, WI, USA) with an incline set to a 1% gradient [23]. Adjustments to treadmill speed could be made in 0.1 mph increments (i.e., ~0.04 m s 1 ); however, all running speed data were reported in SI units (i.e., m s 1 ). Ventilatory and gas exchange variables were measured using the Quark CPET metabolic cart (COSMED, Rome, Italy), with a mixing

Sensors2023,23, 8729 4 of 19 chamber (COSMED), facemask (7450 Series V2, Hans-Rudolph, Shawnee, KS, USA), 2-way non-rebreathing valve (Hans-Rudolph), and gas collection hose. The metabolic cart system was calibrated using a 3 L syringe and gas mixture of known composition (5% CO2, 16% O2, and N2for the balance) prior to each testing visit. For the analysis, 10-s average ventilatory and gas exchange data were used. Heart rates were recorded during all testing sessions using a Polar H10 chest strap (Polar Electro Oy, Kempele, Finland). The V O2associated with a disproportionate increase in the rate of carbon dioxide production ( V CO2) and minute ventilation ( VE ) relative to the increase in V O2was used to identify the GET [24]. The V O2associated with a second disproportionate increase in VE and a disproportionate increase in VE / V CO2relative to the increase in V O2was used to identify the respiratory compensation point (RCP) [24,25]. V O2max was identi ed as the highest 30-s average V O2achieved during the incremental test. All incremental tests were considered maximal, based on the observation of a V O2plateau (de ned as a change in V O2of less than 150 mL min 1 , despite an increased intensity) or any of the following criteria: maximum HR within 10 bpm of the age-predicted maximal value, a respiratory exchange ratio (RER) greater than 1.15, or [Bla] 8 mmol L 1 upon test completion. 2.4.2. Blood Lactate Measurements All [Bla] data were collected using capillary blood drawn from a pinprick of the nger and analyzed for [Bla] using the Biosen C-Line (EKF Diagnostics, Cardiff, Wales;n= 7) or Lactate Plus (Nova Biomedical, Waltham, MA, USA;n= 8) lactate analyzer. Runners straddled the treadmill (~60–75 s) during [Bla] measurements at 10 and 30 min (or at task failure if <30 min). 2.4.3. Perceptual Responses After familiarization with the scale, the rating of perceived exertion (RPE) was mea- sured every 5 min during constant-speed running, using the Borg RPE scale (6–20) [26]. 2.4.4. Running Power—Stryd Running power measurements were made using the Stryd Summit Running Pod (Stryd, Boulder, CO, USA). The Stryd

and 30 min (or at task failure if <30 min). 2.4.3. Perceptual Responses After familiarization with the scale, the rating of perceived exertion (RPE) was mea- sured every 5 min during constant-speed running, using the Borg RPE scale (6–20) [26]. 2.4.4. Running Power—Stryd Running power measurements were made using the Stryd Summit Running Pod (Stryd, Boulder, CO, USA). The Stryd pod, which is a lightweight (8.0 g) and unobtrusive (4.0 cm in length) wearable sensor (Model v.19, rmware v.2.1.16, software v.4), was af xed to the runner's left shoe, approximately equidistant between the runner's malleoli and the shoe's toe. A unique Stryd user pro le was created for each runner that included their respective height and body mass, which was kept constant for all testing sessions. The iPhone Stryd application (Apple Inc., Cupertino, CA, USA) was used to pair the Stryd device and collect the Stryd running power data during the testing sessions. Running power data were sampled at 1 Hz (see Figure). 2.5. Data Analysis 2.5.1. Cardiorespiratory, Running Speed, and Stryd Running Power Data The average V O2and running power, measured between minutes 4 and 6 of the MOD step and between minutes 10 and 12 of the HVY step, were calculated from the SRS test. Maximal aerobic speed (MAS) and maximal aerobic power (MAP) were determined as the running speed associated with the highest completed 1-min stage during the incremental test and the average running power during that stage, respectively. Cardiorespiratory and running power data used for analysis from the constant-speed MLSS-determination running trials included the 10- and 30-min V O2, V CO2, RER, VE , HR, and running power measures for running trials 5% below, at, and 5% above MLSS. To align with the timing of [BLa] measurement (i.e., a short pause in running), mean values

Sensors2023,23, 8729 5 of 19 for V O2, V CO2, RER, VE , HR, and Stryd running power were calculated from the 2 min of data collected prior to the 10-min and the 30-min (or at task failure if <30 min) time points. Although the MLSS is thought to represent the highest intensity at which energy provision is supplied exclusively via oxidative metabolism [27], data collected at 5% above the MLSS were included in the analysis due to the similarly stable V O2measurements between the 10- and 30-min values across the three intensities (i.e., differences between 10- and 30-min V O2measures were ~50 mL min 1 at intensities of 5% below, at, and 5% above the MLSS)—with similar ndings previously being reported [28]—and to provide a more comprehensive dataset for the analyses.Sensors 2023, 23, x FOR PEER REVIEW 5 of 20 Figure 1. Example of the running power signal during constant-speed treadmill running at different intensities for one participant. Data are shown for the moderate (MOD; 6 min) and heavy (HVY; 12 min) intensity steps, and during 30 min of running at 5% below the maximal lactate steady state (MLSS), at the MLSS, 5% above the MLSS, and during a repeat trial at the MLSS, preceded by run- ning power data recorded for 3–4 min at a running speed of 1.9 m·s −1 . Running power data were not collected during the first ~1–2 min of each exercise protocol (i.e., warm-up) to allow for synchroni- zation with other measurements. Note that the repeat MLSS trial is obscured by the first MLSS trial. 2.5. Data Analysis 2.5.1. Cardiorespiratory, Running Speed, and Stryd Running Power Data The average V̇O 2 and running power, measured between minutes 4 and 6 of the MOD step and between minutes 10 and 12 of the HVY step, were calculated from the SRS test. Maximal aerobic speed (MAS) and maximal aerobic power (MAP) were determined as the running speed associated with the highest completed 1-min stage during the incremental test and the average running power during that stage, respectively. Cardiorespiratory and running power data used for analysis

This study evaluates the Stryd device's effectiveness in measuring running intensity and aerobic fitness.