Accuracy of the Babolat Pop sensor for assessment of tennis strokes in structured and match play settings
DOI:
https://doi.org/10.12922/jshp.v7i1.146Keywords:
activity tracker, wearable, sport tracker, tennis shotAbstract
The Babolat Pop sensor (POP) detects tennis stroke types (forehand, backhand, overhead, serve, volley) and spins (topspin, flat, slice), but it has not yet been validated for use. Therefore, this study’s purpose was to validate the POP in structured and match play settings. Seventeen collegiate tennis players (9 women, 8 men) wore the POP on their dominant wrist while participating in 2 sessions. Session 1 (structured) consisted of 10 drills of 5-10 shots each, each focusing on a specific shot type (forehands, backhands, serves, overheads, volleys) and spin (topspin, flat, slice). In session 2 (match play), participants played 6 games against an opponent. For both sessions, researchers observed and recorded the number and type of shot and spin hit for comparison to those recorded by the POP. Mean absolute percent error (MAPE) and bias were calculated to assess accuracy, with sub-analyes by sex and player ranking. The POP underestimated most shots and spins during the structured session, with MAPE averaging 32.0% and ranging 5.3-93.5%. MAPE was 9.4% overall but ranged 11.3-223.9% in the match play setting. MAPE and bias were significantly lower for males than females for most shots in the structured setting but only 2 shot/spin types in the match play setting. Player ranking did not affect sensor accuracy. In conclusion, the POP had lowest error for detecting major stroke types, with similar or better accuracy during match play than in structured drills.
References
Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR, Jr., Tudor-Locke C, et al. Compendium of Physical Activities: A second update of codes and MET values. Med Sci Sports Exerc. 2011; 43(8): 1575-81. DOI: 10.1249/MSS.0b013e31821ece12
Babolat. (2018). "What is piq score?", 2018, from https://piqhelp.zendesk.com/hc/en-us/articles/205504212-What-is-PIQ-Score-.
Bahamonde RE, Knudson D. Kinetics of the upper extremity in the open and square stance tennis forehand. J Sci Med Sport. 2003; 6(1): 88-101. DOI: 10.1016/S1440-2440(03)80012-9
Bastian T, Maire A, Dugas J, Ataya A, Villars C, Gris F, et al. Automatic identification of physical activity types and sedentary behaviors from 3-axial accelerometer: Lab-based calibrations are not enough. J Appl Physiol. 2015; 118(6): 716-22. DOI: 10.1152/japplphysiol.01189.2013
Brown J, Soulier C (2013). The 911 shot of tennis: The half volley. Tennis: Steps to success. Champaign, IL, Human Kinetics, Inc. 34.
Dong B, Montoye A, Moore R, Pfeiffer K, Biswas S. Energy-aware activity classification using wearable sensor networks. Proc SPIE Int Soc Opt Eng. 2013: 87230Y-Y. DOI: 10.1117/12.2018134
Gao L, Bourke A, Nelson J (2012). A comparison of classifiers for activity recognition using multiple accelerometer-based sensors. IEEE Conf Cybernetic Intel Sys. 2012: 149-53.
Gao L, Bourke AK, Nelson J. Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems. Med Eng Phys. 2014; 36(6): 779-85. DOI: 10.1016/j.medengphy.2014.02.012
Giangarra CE, Conroy B, Jobe FW, Pink M, Perry J. Electromyographic and cinematographic analysis of elbow function in tennis players using single- and double-handed backhand strokes. Am J Sports Med. 1993; 21(3): 394-9. DOI: 10.1177/036354659302100312
Gyllensten IC, Bonomi AG. Identifying types of physical activity with a single accelerometer: Evaluating laboratory-trained algorithms in daily life. IEEE Trans Biomed Eng. 2011; 58:9: 2656-63. DOI: 10.1109/TBME.2011.2160723
Imboden MT, Nelson MB, Kaminsky LA, Montoye AH. Comparison of four Fitbit and Jawbone activity monitors with a research-grade ActiGraph accelerometer for estimating physical activity and energy expenditure. Br J Sports Med. 2018; 52: 844-50. DOI: 10.1136/bjsports-2016-096990
Kos M, Jernej Z, Vlaj D, Kramberger I. Tennis stroke detection and classification using and miniature wearable IMU device. Int Conf Sys Sig Image Process. 2016: 1-4.
LaPorte RE, Kuller LH, Kupfer DJ, McPartland RJ, Matthews G, Caspersen C. An objective measure of physical activity for epidemiologic research. Am J Epidemiol. 1979; 109(2): 158-68. DOI: 10.1093/oxfordjournals.aje.a112671
Nelson MB, Kaminsky LA, Dickin DC, Montoye AH. Validity of consumer-based physical activity monitors for specific activity types. Med Sci Sports Exerc. 2016; 48(8): 1619-28. DOI: 10.1249/MSS.0000000000000933
Petkovic M, Jonker W, Zivkovic Z. Recognizing strokes in tennis videos using hidden Markov models. IASTED int Conf Visual Imaging Image Process. 2001: 512-6.
Reid M, Elliott B. The one- and two-handed backhands in tennis. Sports Biomech. 2002; 1(1): 47-68. DOI: 10.1080/14763140208522786
Reid M, Morgan S, Whiteside D. Matchplay characteristics of grand slam tennis: Implications for training and conditioning. J Sports Sci. 2016; 34(19): 1791-8.
Rogowski I, Creveaux T, Cheze L, Mace P, Dumas R. Effects of the racket polar moment of inertia on dominant upper limb joint moments during tennis serve. PLoS One. 2014; 9(8): e104785. DOI: 10.1080/02640414.2016.1139161
Safrit M, Wood T. Introduction to Measurement in Physical Education and Exercise Science. St. Louis, MO, Mosby; 1995.
Takahashi K, Elliott B, Noffal G. The role of upper limb segment rotations in the development of spin in the tennis forehand. Aust J Sci Med Sport. 1996; 28(4): 106-13.
Tanabe S, Ito A. A three-dimensional analysis of the contributions of upper limb joint movements to horizontal racket head velocity at ball impact during tennis serving. Sports Biomech. 2007; 6(3): 418-33. DOI: 10.1080/14763140701491500
Thompson WR. Worldwide survey of fitness trends for 2016: 10th anniversary edition. Health Fitness J. 2015; 19(6): 9-18. DOI: 10.1249/FIT.0000000000000164
Thompson WR. Worldwide survey of fitness trends for 2017. Health Fitness J. 2016; 20(6): 8-17. DOI: 10.1249/FIT.0000000000000252
Thompson WR. Worldwide survey of fitness trends for 2018: The crep edition. Health Fitness J. 2017; 21(6): 10-9. DOI: 10.1249/FIT.0000000000000341
Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008; 40(1): 181-8. DOI: 10.1249/mss.0b013e31815a51b3
Welk GJ (2002). Use of accelerometry-based activity monitors to assess physical activity. Physical Activity Assessments for Health-Related Research. G. J. Welk. Champaign, IL, Human Kinetics, Inc.: 125-42.
Whiteside D, Cant O, Connolly M, Reid M. Monitoring hitting load in tennis using inertial sensors and machine learning. Int J Sports Physiol Perform. 2017; 12(9): 1212-7. DOI: 10.1123/ijspp.2016-0683
Wong TC, Webster JG, Montoye HJ, Washburn R. Portable accelerometer device for measuring human energy expenditure. IEEE Trans Biomed Eng. 1981; 28(6): 467-71.
Woods RA. (2017). "Men’s and women’s participation in sports and exercise, 2003–15." from https://www.bls.gov/spotlight/2017/sports-and-exercise/pdf/sports-and-exercise.pdf.
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