SECTION I - KINESIOLOGY / RESEARCH PAPER
Analysis of Fluency of Movement in Parkour Using a Video and Inertial Measurement Unit Technology
 
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1
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
 
2
Department of Radiology, Ausl Romagna, S. Maria delle Croci Hospital, Ravenna, Italy.
 
3
Department of Translational Medicine and for Romagna, Università degli Studi di Ferrara, Ferrara, Italy.
 
4
Department of Industrial Engineering (DII), University of Padua, Padova, Italy.
 
5
UCLA Department of Orthopaedic Surgery, David Geffen School of Medicine, Los Angeles, California, USA.
 
 
Submission date: 2022-08-18
 
 
Acceptance date: 2023-02-13
 
 
Online publication date: 2023-06-05
 
 
Corresponding author
Francesco Feletti   

Dipartimento di Medicina Traslazione e per la Romagna, Università degli Studi di Ferrara, Ferrara, Italy, Italy
 
 
Journal of Human Kinetics 2023;89:5–18
 
KEYWORDS
TOPICS
ABSTRACT
Fluency is a movement parameter combining smoothness and hesitation, and its objective measurement may be used to determine the effects of practice on sports performance. This study aimed to measure fluency in parkour, an acrobatic discipline comprising complex non-cyclical movements, which involves fluency as a critical aspect of performance. Inter-individual fluidity differences between advanced and novice athletes as well as intra-individual variations of fluency between different parts and subsequent repetitions of a path were addressed. Seventeen parkour participants were enrolled and divided into two groups based on their experience. We analysed signals captured from an inertial measurement unit fixed on the back of the pelvis of each participant during three consecutive repetitions of a specifically designed parkour routine under the guidance of video analysis. Two fluency parameters, namely smoothness and hesitation, were measured. Smoothness was calculated as the number of inflexions on the so-called jerk graph; hesitation was the percentage of the drop in the centre of mass velocity. Smoothness resulted in significantly lower values in advanced athletes (mean: 126.4; range: 36–192) than in beginners (mean: 179.37; range: 98–272) during one of the three motor activities (p = 0.02). A qualitative analysis of hesitation showed that beginner athletes tended to experience more prominent velocity drops and negative deflection than more advanced athletes. In conclusion, a system based on a video and an inertial measurement unit is a promising approach for quantification and the assessment of variability of fluency, and it is potentially beneficial to guide and evaluate the training process.
 
REFERENCES (33)
1.
Bartlett, R., Wheat, J., & Robins, M. (2007). Is movement variability important for sports biomechanists? Sports Biomechanics, 6(2), 224–43. doi: 10.1080/14763140701322994.
 
2.
Camomilla, V., Bergamini, E., Fantozzi, S., & Vannozzi, G. (2018). Trends Supporting the In–Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review. Sensors, 18(3), 873. doi: 10.3390/s18030873.
 
3.
Croft, J.L., Schroeder, R.T., & Bertram, J. E. A. (2019). Determinants of optimal leg use strategy: horizontal to vertical transition in the parkour wall climb. Journal of Experimental Biology, 10, 222(1), jeb190983. doi: 10.1242/jeb.190983.
 
4.
Davids, K., Glazier, P., Araújo, D., & Bartlett, R. (2003). Movement systems as dynamical systems: the functional role of variability and its implications for sports medicine. Sports Medicine, 33(4), 245–60. doi: 10.2165/00007256-200333040-00001.
 
5.
Dion, L., Malouin, F., McFadyen, B., & Richards, C. L. (2003). Assessing mobility and locomotor coordination after stroke with the rise-to-walk task. Neurorehabilitation and Neural Repair, 17(2), 83–92. doi: 10.1177/0888439003017002002.
 
6.
Dvořák, M., Baláš, J., & Martin, A.J. (2018). The Reliability of Parkour Skills Assessment. Sports, 6(1), 6. doi: 10.3390/sports6010006.
 
7.
Grosprêtre, S., & Lepers, R. (2016). Performance characteristics of Parkour practitioners: Who are the traceurs? European Journal of Sport Science, 16(5), 526–35. doi: 10.1080/17461391.2015.1060263.
 
8.
Hogan, N. (1984). An organizing principle for a class of voluntary movements. Journal of Neuroscience, 4(11), 2745–54. doi: 10.1523/JNEUROSCI.04-11-02745.1984.
 
9.
Hreljac, A. (2000). Stride smoothness evaluation of runners and other athletes. Gait Posture, 11(3), 199–206. doi: 10.1016/s0966-6362(00)00045-x.
 
10.
Immonen, T., Brymer, E., Orth, D., Davids, K., Feletti, F., Liukkonen, J., & Jaakkola, T. (2017). Understanding Action and Adventure Sports Participation-An Ecological Dynamics Perspective. Sports Medicine - Open, 3(1), 18. doi: 10.1186/s40798-017-0084-1.
 
11.
International Gymnastics Federation. (2019). Parkour. Retrieved by: https://www.gymnastics.sport/s... (accessed on 13 October 2020).
 
12.
Kaufman, M. T., Churchland, M. M., Ryu, S. I., & Shenoy, K. V. (2015). Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex. Elife, 4, e04677. doi: 10.7554/eLife.04677.
 
13.
Kelso, J.A.S. (2005). Principles of dynamic pattern formation and change for a science of human behavior. In: Bergman, L.R., Cairns, R.B., Nilsson, L.G., Nystedt, L. (Eds.) Developmental Science and the Holistic Approach (pp. 63–81) LEA Publishers.
 
14.
Kerr, A., Pomeroy, V. P., Rowe, P. J., Dall, P., & Rafferty, D. (2013). Measuring movement fluency during the sit-to-walk task. Gait Posture, 37(4), 598–602. doi: 10.1016/j.gaitpost.2012.09.026.
 
15.
Koo TK, & Li MY. (2016). A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. Journal of Chiropractic Medicine, 15(2), 155–63. doi: 10.1016/j.jcm.2016.02.012.
 
16.
Król, H., Klyszcz-Morciniec, M., & Bacik, B. (2020). The Structure of Selected Basic Acrobatic Jumps. Journal of Human Kinetics, 75, 41–64. doi: 10.2478/hukin-2020-0036.
 
17.
Migueles, J. H., Cadenas-Sanchez, C., Ekelund, U., Delisle Nyström, C., Mora-Gonzalez, J., Löf, M., Labayen, I., Ruiz, J. R., & Ortega, F. B. (2017). Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations. Sports Medicine, 47(9), 1821–1845. doi: 10.1007/s40279-017-0716-0.
 
18.
Minami, I., Zhao, N., Oogai, K., Nemoto, T., Whittle, T., & Murray, G.M. (2011). A comparison between jerk–cost derived from a jaw–tracking system with that from an accelerometer. Journal of Oral Rehabilitation, 38(9), 661–667. doi:10.1111/j.1365-2842.2011.02200.x.
 
19.
Minetti, A. E., Cisotti, C., & Mian, O. S. (2011). The mathematical description of the body centre of mass 3D path in human and animal locomotion. Journal of Biomechanics, 44(8), 1471–7. doi: 10.1016/j.jbiomech.2011.03.014.
 
20.
Newell, K. M., & Vaillancourt, D. (2001). Dimensional change in motor learning. Human Movement Science, 20, 695–715.
 
21.
Pansiot, J., King, R., McIlwraith, D., Lo, B., & Yang, G. (2008). ClimBSN: Climber Performance Monitoring with BSN. In: The Chinese University of Hong Kong (Ed) . IEEE proceedings of the 5th International Workshop on Wearable and Implantable Body Sensor Networks IEEE, 33–36.
 
22.
Paulich M., Schepers M., Rudigkeit N., & Bellusci G. (2018). Xsens MTw Awinda: Miniature Wireless Inertial–Magnetic Motion Tracker for Highly Accurate 3D Kinematic Applications. XSENS Technologies BV (Ed). MTW Awinda Whitepaper, – MW0404P.A.
 
23.
Pavei, G., Cazzola, D., La Torre, A., & Minetti, A.E. (2014). The biomechanics of race walking: literature overview and new insights. European Journal of Sport Science, 14(7), 661–70. doi: 10.1080/17461391.2013.878755.
 
24.
Piana, S., Alborno, P., Niewiadomski, R., Mancini, M., Volpe, G., & Camurri, A. (2016). Movement Fluidity Analysis Based on Performance and Perception. CHI Extended, Abstracts, May, 7–12. doi: http://dx.doi.org/10.1145/2851....
 
25.
Pomeroy, V. M., Pramanik, A., Sykes, L., Richards, J., & Hill, E. (2003). Agreement between physiotherapists on quality of movement rated via videotape. Clinical Rehabilitation, 17(3), 264–72. doi: 10.1191/0269215503cr607oa.
 
26.
Schneider, K., & Zernicke, R. F. (1989). Jerk-cost modulations during the practice of rapid arm movements. Biological Cybernetics, 60(3), 221–30. doi: 10.1007/BF00207290.
 
27.
Seifert, L., Button, C., & Davids, K. (2013). Key Properties of Expert Movement Systems in Sport. Sports Medicine, 43, 167–178. DOI 10.1007/s40279-012-0011-z.
 
28.
Seifert, L., Orth, D., Boulanger, J., Dovgalecs, V., Hérault, R., & Davids, K. (2014). Climbing skill and complexity of climbing wall design: assessment of jerk as a novel indicator of performance fluency. Journal of Applied Biomechanics, 30(5), 619–25. doi: 10.1123/jab.2014-0052.
 
29.
Takei, Y., & Dunn, J. H. A. (1996). A comparison of techniques used by elite gymnasts in performing the basket-to-handstand mount. Journal of Sports Sciences, 14(3), 269–79. doi: 10.1080/02640419608727710.
 
30.
Van der Kruk, E., & Reijne, M. M. (2018). Accuracy of human motion capture systems for sport applications; state–of–the–art review. European Journal of Sport Science, 18(6), 806–819. doi: 10.1080/17461391.2018.1463397.
 
31.
Van Meulen, F. B., Reenalda, J., Buurke, J. H., & Veltink, P. H. (2015). Assessment of daily-life reaching performance after stroke. Annals of Biomedical Engineering, 43(2), 478–86. doi: 10.1007/s10439-014-1198-y.
 
32.
Yang, F., & Pai, Y. C. (2014). Can sacral marker approximate center of mass during gait and slip–fall recovery among community–dwelling older adults? Journal of Biomechanics, 47(16), 3807–12. doi: 10.1016/j.jbiomech.2014.10.027.
 
33.
Young, R. P., & Marteniuk, R. G. (1997). Acquisition of a multi-articular kicking task: Jerk analysis demonstrates movements do not become smoother with learning. Human Movement Science, 16(5), 677–701.
 
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