The Use of Wearable Technology to Quantify Power and Muscle Load Differences During Running Against Varying Wind Resistances

Marissa L. Bello, Derick A. Anglin, Zachary M. Gillen, JohnEric W. Smith

Abstract


Background: Wearable technology has increased in popularity due to its live feedback and ability to adjust within training sessions. In addition to heart rate (HR) monitoring, measuring power and internal load may provide useful insight and a more comprehensive view of training differences. Objectives: Assess the efficacy of wearable technology in endurance runners to determine changes in performance variables with varying wind resistance. Methods: A quasi-experimental study was designed and recruited twelve endurance-trained runners currently running ≥120 min/week for the past 3 months. Participants completed two sessions: V̇O2peak testing, and a 20-min run at 70% V̇O2peak. The run was evenly divided into no wind resistance (W0) and 16.1 km/h wind resistance (W16). Power was assessed via a power meter and internal/external load measured via surface EMG sensor-embedded compression shorts. A HR sensor was used and V̇O2 and RER were monitored using a metabolic cart. Paired t-tests were used to compare differences and Pearson correlations were conducted for each segment. Significance was set a priori at p<0.05. Results: There were significant differences in power (W16 > W0; p=0.002), as well as a strong positive correlation between power and internal load for W0 (r=0.692; p=0.013) and W16 (r=0.657; p=0.02). Conclusions: The lack of significance changes in HR, V̇O2, and RER demonstrates a sustained similar physiological response. The significant increase observed in power suggests the power meter can be useful in differentiating wind resistance, and the positive correlations suggest a combination of these devices may be beneficial in distinguishing performance changes during fluctuating conditions.

Keywords


Wearable Electronic Devices, Electromyography, Fitness Trackers, Endurance Training, Athletic Performance

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References


Aquino, J. M., & Roper, J. L. (2018). Intraindividual variability and validity in smart apparel muscle activity measurements during exercise in men. International Journal of Exercise Science, 11(7), 516-525.

Aroganam, G., Manivannan, N., & Harrison, D. (2019). Review on wearable technology sensors ssed in consumer sport applications. Sensors, 19(9). doi:10.3390/s19091983

Cerezuela-Espejo, V., Hernandez-Belmonte, A., Courel-Ibanez, J., Conesa-Ros, E., Martinez-Cava, A., & Pallares, J. G. (2020). Running power meters and theoretical models based on laws of physics: Effects of environments and running conditions. Physiology & Behavior, 223, 112972. doi:10.1016/j.physbeh.2020.112972

Cornelissen, V. A., Verheyden, B., Aubert, A. E., & Fagard, R. H. (2010). Effects of aerobic training intensity on resting, exercise and post-exercise blood pressure, heart rate and heart-rate variability. Journal of Human Hypertension, 24(3), 175-182. doi:10.1038/jhh.2009.51

Davarzani, S., Helzer, D., Rivera, J., Saucier, D., Jo, E., Burch V, R. F., . . . Petway, A. (2020). Validity and reliability of Strive Sense3 for muscle activity monitoring during the squat exercise. International Journal of Kinesiology and Sports Science, 8(4). doi:10.7575/aiac.ijkss.v.8n.4p.1

Dijkhuis, T. B., Otter, R., Aiello, M., Velthuijsen, H., & Lemmink, K. (2020). Increase in the acute:chronic workload ratio relates to injury risk in competitive runners. International Journal of Sports Medicine, 41(11), 736-743. doi:10.1055/a-1171-2331

Drew, M. K., & Finch, C. F. (2016). The relationship between training load and injury, illness and soreness: A systematic and literature review. Sports Medicine, 46(6), 861-883. doi:10.1007/s40279-015-0459-8

El-Amrawy, F., & Nounou, M. I. (2015). Are currently available wearable devices for activity tracking and heart rate monitoring accurate, precise, and medically beneficial? Healthcare Informatics Ressearch, 21(4), 315-320. doi:10.4258/hir.2015.21.4.315

Henriksen, A., Haugen Mikalsen, M., Woldaregay, A. Z., Muzny, M., Hartvigsen, G., Hopstock, L. A., & Grimsgaard, S. (2018). Using fitness trackers and smartwatches to measure physical activity in research: Analysis of consumer wrist-worn wearables. Journal of Medical Internet Research, 20(3), e110. doi:10.2196/jmir.9157

Lynn, S. K., Watkins, C. M., Wong, M. A., Balfany, K., & Feeney, D. F. (2018). Validity and reliability of surface electromyography measurements from a wearable athlete performance system. Journal of Sports Science and Medicine, 17(2), 205-215.

Malone, S., Roe, M., Doran, D. A., Gabbett, T. J., & Collins, K. D. (2017). Protection against spikes in workload with aerobic fitness and playing experience: the role of the acute:chronic workload ratio on injury risk in elite Gaelic football. International Journal of Sports Physiology and Performance, 12(3), 393-401. doi:10.1123/ijspp.2016-0090

Pobiruchin, M., Suleder, J., Zowalla, R., & Wiesner, M. (2017). Accuracy and adoption of wearable technology used by active citizens: a marathon event field study. JMIR Mhealth Uhealth, 5(2), e24. doi:10.2196/mhealth.6395

Robergs, R. A., Pascoe, D. D., Costill, D. L., Fink, W. J., Chwalbinska-Moneta, J., Davis, J. A., & Hickner, R. (1991). Effects of warm-up on muscle glycogenolysis during intense exercise. Medicine and Science in Sports and Exercise, 23(1), 37-43. doi:10.1249/00005768-199101000-00007

Saucier, D. N., Davarzani, S., Burch, V. R., Chander, H., Strawderman, L., Freeman, C., . . . Piroli, A. (2021). External load and muscle activation monitoring of NCAA Division I basketball team using smart compression shorts. Sensors, 21(16). doi:10.3390/s21165348

Seshadri, D. R., Li, R. T., Voos, J. E., Rowbottom, J. R., Alfes, C. M., Zorman, C. A., & Drummond, C. K. (2019). Wearable sensors for monitoring the internal and external workload of the athlete. NPJ Digital Medicine, 2, 71. doi:10.1038/s41746-019-0149-2

Xie, J., Wen, D., Liang, L., Jia, Y., Gao, L., & Lei, J. (2018). Evaluating the validity of current mainstream wearable devices in fitness tracking under various physical activities: comparative study. JMIR Mhealth Uhealth, 6(4), e94. doi:10.2196/mhealth.9754




DOI: https://doi.org/10.7575/aiac.ijkss.v.10n.2p.11

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