تأثیر تمرین جسمانی و تمرین ذهنی بر تغییرپذیری الگوی هماهنگی و نرمی حرکت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 بخش علوم ورزشی، دانشکده علوم تربیتی و روانشناسی، دانشگاه شیراز، شیراز، ایران

2 گروه رفتار حرکتی، دانشکده علوم ورزشی، دانشگاه فردوسی، مشهد، ایران

چکیده
هدف این پژوهش بررسی تأثیر تمرین جسمی و ذهنی بر تغییرپذیری الگوی هماهنگی حرکتی و نرمی حرکت در ضربه گلف بود؛ بر این اساس، 30 نفر (میانگین سنی 3/4±25 سال) به صورت تصادفی به سه گروه تمرین جسمانی، تمرین ذهنی و کنترل تقسیم شدند. افراد برای پیش‌آزمون 10 ضربه را انجام دادند. سپس براساس گروه­بندی خود در هر روز 180 کوشش (10 بلوک 18 کوششی) را تکمیل کردند. تمرین به مدت شش روز ادامه داشت. شرکت­کنندگان گروه جسمانی به اجرای تکلیف به صورت جسمانی و شرکت­­کنندگان در گروه تمرین ذهنی فقط به مرور ذهنی تکلیف بدون انجام حرکت آشکار پرداختند، اما گروه کنترل فقط در آزمون­­ها شرکت کرد و تکلیف را تمرین نکرد. هفت روز بعد از آخرین روز اکتساب، افراد مجدد 10 ضربه را به‌عنوان یادداری اجرا کردند. دقت ضربه و کینماتیک حرکت در حین اجرای آزمون­­ها ثبت شد. تغییرپذیری الگوی هماهنگی حرکتی و جرک حرکت از داده­های کینماتیک محاسبه شد. نرمال بودن داده­ها با آزمون شاپیرو-ویلک تأیید شد (05/0<P). به‌منظور تحلیل داده­ها از آزمون تحلیل واریانس استفاده شد. نتایج نشان داد، تمرین جسمانی و تمرین ذهنی در یادگیری ضربه گلف مؤثر بودند، اما این تأثیر برای تمرین جسمی بیشتر بود (20/13=(27 و 2)F، 001/0>P، 49/0=η2p). همچنین تمرین ذهنی مشابه با تمرین جسمانی موجب افزایش نرمی حرکت شد، اما این بهبود به اندازه تمرین جسمانی نبود (26/15=(27 و 2)F، 001/0>P، 53/0=η2p). دلیل احتمالی برای این یافته­­ها ممکن است وجود بازخورد واقعی در اجرای تمرین جسمانی باشد که موجب اصلاح و به‌روزرسانی مدل­‌های درونی می­­شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله English

Effect of Physical and Mental Practice on Variability of Movement Coordination and Smoothness

نویسندگان English

Davoud Fazeli 1
Hamidreza Taheri 2
Alireza Saberi Kakhki 2
Fatemeh Shakeri Chenari 1
1 Department of Sport Sciences, Faculty of Education and Psychology, Shiraz University, Shiraz, Iran
2 Department of Motor Behavior, Faculty of Sport Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
چکیده English

Extended Abstract
Background and Purpose
The positive effect of mental practice on skill learning is considered a piece of evidence for similar underlying mechanisms of physical and mental practice. According to Newell’s model of motor learning, at the first stage of learning, the physical practice would enhance coordination and in the second stage practice would enhance control of that coordination pattern. In line with this argument, it has been shown that movement variability would reduce as a result of skill enhancement. Also, research showed that movement jerk would reduce as a result of skill improvement. According to the abovementioned argument, if the underlying mechanisms of mental and physical practice are similar, then mental practice should have a similar effect on movement variability and movement jerk. As this argument was not considered widely in previous studies, this study aimed to compare the effect of physical and mental practice on movement variability and movement jerk.
 Methods
30 males (mean = 25 ± 4.3) participated in this study according to a convenience sampling method. Participants were divided into three different groups (physical, mental, and control) according to their pre-test scores (10 trials from 244 cm away from the target). Also, before participating in the practice sessions, all participants completed the movement imagery questionnaire-revised. Then, participants practiced a golf putting task for 6 consecutive days (10 blocks—18 trials each). The physical practice group performed 180 trials each day (10 blocks) from 244 cm away from the target. The mental practice group completed the mental putting task while standing on the start point holding the putter, without any observable movement. The control group did not practice and just completed the pre- and retention tests. A retention test (similar to the pre-test) was performed seven days from the last practice session (10 trials from 244 cm from the target). Movement kinematics were recorded using a SIMI motion capture system to calculate the coordination and smoothness indexes. Putting accuracy (distance from the edge of the landed ball from the edge of the target), variability of coordination pattern, and movement jerk were calculated as the dependent variables. The imagery data were analyzed using a One-way ANOVA. All other data were analyzed using a mixed ANOVA model 3 (group; physical, mental, and control) × 2 (test; pre- and post-tests) with the repeated measures on the last factor.
Results
Results of One-way ANOVA for imagery data showed no significant difference between groups,
F < 1. For the accuracy data, results showed no significant main effect of group, F (2, 27) = 0.98, p = 0.38, η²p = 0.068. However, significant main effects for test, F (1, 27) = 10.21, p = 0.004, η²p = 0.27, and the interaction of group with test, F (2, 27) = 13.20, p < 0.001, η²p = 0.49, were found. The results of post-hoc test for the interaction effect showed that there was no significant difference between groups during the pre-test, all p > 0.05. However, the physical practice showed higher accuracy than the imagery practice group during the post-test, p < 0.05. Also, accuracy improvements were observed for physical and imagery groups from pre to post-test, all p < 0.05; no such effect was observed for the control group, p > 0.05. Results for variability of coordination pattern showed no significant main effect for group, F (2, 27) = 1.08, p = 0.35, η²p = 0.07. However, significant effects were observed for test, F (1, 27) = 63.63, p < 0.001, η²p = 0.7, and interaction of group × test, F (2, 27) = 15.38, p < 0.001, η²p = 0.53. Post-hoc test for the interaction effect showed that there was no significant difference between groups during the pre-test, all p > 0.05. Results showed that during the retention test physical and imagery groups significantly outperformed the control group, all p < 0.05. The difference between the physical and imagery groups was not significant during the retention test, p > 0.05. Also, results showed improvement from pre-test to retention test for physical and imagery groups, all p < 0.05; such effect was not observed for the control group, p > 0.05. Results of ANOVA for the jerk measure showed significant main effects for group, F (2, 27) = 5.68, p = 0.009, η²p = 0.29, and test, F (1, 27) = 33.78, p < 0.001, η²p = 0.55. Also, the interaction effect of group × test was significant, F (2, 27) = 15.26, p < 0.001, η²p = 0.53. Results of post-hoc test for the interaction showed no significant difference between groups during the pre-test, all p > 0.05. However, results showed that the physical group had significantly lower movement jerk than the imagery and control groups, all p < 0.05. Also, results showed improvement from pre-test to retention test for physical and imagery groups, all p < 0.05; like other measures, such effect was not observed for control group, all p > 0.05.

 Conclusion
Although mental practice improved movement accuracy, this improvement was not equal to or more than improvements by physical practice. These findings were considered as evidence for different underlying mechanisms for physical and mental practice (8,9,10). It is argued that internal models would not update during motor imagery (11), and as a result, learning may suffer. In contrast to the previous study (12), this study showed that mental practice would improve the variability of movement coordination similar to physical practice. In the previous study, a discrete measure of variability was used which has some limitations to show differences between groups (13,14); however, in this study a continuous measure was used. Also, in the previous study participants just performed 18 trials, in this study participants performed 1080 practice trials. The difference in the amount of practice could serve as a possible reason for contradicting findings. Besides, results showed that motor imagery practice improved movement smoothness but was lower than physical practice. The lack of real visual feedback could be the possible reason for this finding (8).
Article Message
The results of this study showed that mental practice, like physical practice, leads to learning the golf stroke. The results also indicated that mental practice improves movement smoothness; however, this improvement was not as significant as that achieved through physical practice.
Ethical Considerations
This study was reviewed and approved by the Ethics Committee of Shiraz University.
Authors’ Contributions
Conceptualization: Davoud Fazeli, Hamidreza Taheri, Alireza Saberi Kakhki
Data Collection: Davoud Fazeli
Data Analysis: Davoud Fazeli, Hamidreza Taheri, Alireza Saberi Kakhki, Fatemeh Shakeri Chenari
Manuscript Writing: Davoud Fazeli, Hamidreza Taheri, Alireza Saberi Kakhki, Fatemeh Shakeri Chenari
Review and Editing: Davoud Fazeli, Hamidreza Taheri, Alireza Saberi Kakhki, Fatemeh Shakeri Chenari
Responsible for funding: No funding.
Literature Review: Davoud Fazeli, Hamidreza Taheri, Alireza Saberi Kakhki, Fatemeh Shakeri Chenari
Project Manager: Davoud Fazeli
Any other Contributions: No other contributions
Conflict of Interest
The author(s) declare that there is no conflict of interest regarding the publication of this article.
 
Acknowledgments
The author(s) would like to express their sincere gratitude to the participants who made this study possible.
 

کلیدواژه‌ها English

Golf Stroke, Movement Jerk, Coordination, Internal Models
 
1.       Schmidt RA, Lee TD, Winstein C, Wulf G, Zelaznik HN. Motor control and learning: a behavioral emphasis. Human kinetics; 2018.
2.       Driskell JE, Copper C, Moran A. Does mental practice enhance performance? Journal of Applied Psychology. 1994;79(4):481.
3.       Jeannerod M. Neural simulation of action: a unifying mechanism for motor cognition. Neuroimage. 2001;14(1):S103-S9.
4.       Newell KM. Coordination, control and skill. Advances in psychology. 27: Elsevier; 1985. p. 295-317. https://doi.org/10.1016/S0166-4115(08)62541-8
5.       Kugler PN, Kelso JS, Turvey MT. On the concept of coordinative structures as dissipative structures: I. theoretical lines of convergence. Advances in psychology. 1: Elsevier; 1980. p. 3-47. https://doi.org/10.1016/S0166-4115(08)61936-6
6.       Fitts PM, Posner MI. Human performance. Brooks/Cole. Oxford, England; 1967.
7.       Dai B, Leigh S, Li H, Mercer VS, Yu B. The relationships between technique variability and performance in discus throwing. Journal of Sports Sciences. 2013;31(2):219-28. https://doi.org/10.1080/02640414.2012.729078
8.       Tucker CB, Hanley B. Gait variability and symmetry in world-class senior and junior race walkers. Journal of Sports Sciences. 2017;35(17):1739-44. https://doi.org/10.1080/02640414.2016.1235793
9.       Serrien B, Ooijen J, Goossens M, Baeyens J-P. A Motion analysis in the volleyball spike—Part 2: Coordination and performance variability. International Journal of Human Movement and Sports Sciences. 2016;4(4):83-90. https://doi.org/10.13189/saj.2016.040404
10.    Palmer HA, Newell KM, Gordon D, Smith L, Williams GK. Qualitative and quantitative change in the kinematics of learning a non-dominant overarm throw. Human Movement Science. 2018;62:134-42. https://doi.org/10.1016/j.humov.2018.10.004
11.    Palmer HA, Newell KM, Mulloy F, Gordon D, Smith L, Williams GK. Movement form of the overarm throw for children at 6, 10 and 14 years of age. European Journal of Sport Science. 2021;21(9):1254-62. https://doi.org/10.1080/17461391.2020.1834622
12.    Chow JY, Davids K, Button C, Koh M. Variation in coordination of a discrete multiarticular action as a function of skill level. Journal of Motor Behavior. 2007;39(6):463-79. https://doi.org/10.3200/JMBR.39.6.463-480
13.    Wilson C, Simpson SE, Van Emmerik RE, Hamill J. Coordination variability and skill development in expert triple jumpers. Sports Biomechanics. 2008;7(1):2-9. https://doi.org/10.1080/14763140701682983
14.    Latash ML. Fundamentals of motor control. Academic Press; 2012.
15.    Choi A, Joo S-B, Oh E, Mun JH. Kinematic evaluation of movement smoothness in golf: relationship between the normalized jerk cost of body joints and the clubhead. Biomedical Engineering Online. 2014;13(1):1-12. https://doi.org/10.1186/1475-925X-13-20
16.    Lee M-H, Newell KM. Visual feedback of hand trajectory and the development of infant prehension. Infant Behavior and Development. 2012;35(2):273-9. https://doi.org/10.1016/j.infbeh.2011.12.004
17.    Ganzevles SP, Beek PJ, Daanen HA, Coolen BM, Truijens MJ. Differences in swimming smoothness between elite and non-elite swimmers. Sports Biomechanics. 2019:1-14. https://doi.org/10.1080/14763141.2019.1650102
18.    Holmes P, Calmels C. A neuroscientific review of imagery and observation use in sport. Journal of Motor Behavior. 2008;40(5):433-45. https://doi.org/10.3200/JMBR.40.5.433-445
19.    Kilteni, K., Andersson, B. J., Houborg, C., & Ehrsson, H. H. (2018). Motor imagery involves predicting the sensory consequences of the imagined movement. Nature Communications, 9(1), 1-9.
20.    Dahm, S. F., & Rieger, M. (2019). Is imagery better than reality? Performance in imagined dart throwing. Human Movement Science, 66, 38-52. https://doi.org/10.1016/j.humov.2019.03.005
21.    Kraeutner, S. N., Cui, A. X., Boyd, L. A., & Boe, S. G. (2022). Modality of practice modulates resting state connectivity during motor learning. Neuroscience Letters, 781, 136659. https://doi.org/10.1016/j.neulet.2022.136659
22.    Ruffino C, Truong C, Dupont W, Bouguila F, Michel C, Lebon F, et al. Acquisition and consolidation processes following motor imagery practice. Scientific Reports. 2021;11(1):1-12.
23.    Fazeli D, Taheri H, Kakhki AS. Utilizing the variability of practice in physical execution, action observation, and motor imagery: similar or dissimilar mechanisms? Motor Control. 2021;25(2):198-210. https://doi.org/10.1123/mc.2020-0021
24.    Mohammed Suberi N, Razman R, Callow N, editors. Does Imagery Facilitate a Reduction in Movement Variability in a Targeting Task? International Conference on Movement, Health and Exercise. Springer; 2016. https://doi.org/10.1007/978-981-10-3737-5_31
25.    Rein R. Measurement methods to analyze changes in coordination during motor learning from a non-linear perspective. The Open Sports Sciences Journal. 2012;5(1). https://doi.org/10.2174/1875399X01205010036
26.    Balasubramanian S, Melendez-Calderon A, Burdet E. A robust and sensitive metric for quantifying movement smoothness. IEEE Transactions on Biomedical Engineering. 2011;59(8):2126-36. https://doi.org/10.1109/TBME.2011.2179545
27.    Balasubramanian S, Melendez-Calderon A, Roby-Brami A, Burdet E. On the analysis of movement smoothness. Journal of Neuroengineering and Rehabilitation. 2015;12(1):1-11. https://doi.org/10.1186/s12984-015-0090-9
28.    Sohrabi M, Farsi A, Fouladian J. Validation of the Iranian translation of the movement imagery questionnaire revised. Journal of Studies in Sport Sciences. 2010;5(1):13-24. [In Persian].
29.    Sidaway B, Heise G, Schoenfelder-Zohdi B. Quantifying the variability of angle-angle plots. Journal of Human Movement Studies. 1995;29:181-97.
30.    Stergiou N. Nonlinear analysis for human movement variability. CRC Press; 2016.
31.    Coelho CJ, Nusbaum HC, Rosenbaum DA, Fenn KM. Imagined actions aren't just weak actions: task variability promotes skill learning in physical practice but not in mental practice. Journal of Experimental Psychology: Learning, Memory, and Cognition. 2012;38(6):1759. https://doi.org/10.1037/a0028065
32.    Fazeli D, Moradi N. Effect of different methods of practice a pre-performance routine on mental representation and performance levels of vollyball overhand float serve. Sport Psychology Studies. 2019;8(29):88-104. https://doi.org/10.22089/spsyj.2019.7153.1762 [In Persian].
33.    Hird JS, Landers DM, Thomas JR, Horan JJ. Physical practice is superior to mental practice in enhancing cognitive and motor task performance. Journal of Sport and Exercise Psychology. 1991;13(3):281-93.
34.    Simonsmeier BA, Andronie M, Buecker S, Frank C. The effects of imagery interventions in sports: a meta-analysis. International Review of Sport and Exercise Psychology. 2021;14(1):186-207. https://doi.org/10.1080/1750984X.2020.1780627         
35.    Lei Y, Bao S, Wang J. The combined effects of action observation and passive proprioceptive training on adaptive motor learning. Neuroscience. 2016;331:91-8. https://doi.org/10.1016/j.neuroscience.2016.06.011
36.    Ong NT, Hodges NJ. Absence of after-effects for observers after watching a visuomotor adaptation. Experimental Brain Research. 2010;205(3):325-34. https://doi.org/10.1007/s00221-010-2366-4
37.    Ong NT, Larssen BC, Hodges NJ. In the absence of physical practice, observation and imagery do not result in updating of internal models for aiming. Experimental Brain Research. 2012;218(1):9-19. https://doi.org/10.1007/s00221-011-2996-1
38.    Frank C, Land WM, Popp C, Schack T. Mental representation and mental practice: experimental investigation on the functional links between motor memory and motor imagery. PloS One. 2014;9(4):e95175. https://doi.org/10.1371/journal.pone.0095175
39.    Bernardi NF, De Buglio M, Trimarchi PD, Chielli A, Bricolo E. Mental practice promotes motor anticipation: evidence from skilled music performance. Frontiers in Human Neuroscience. 2013;7:451. https://doi.org/10.3389/fnhum.2013.00451
40.    Marshall B, Wright D, Holmes P, Williams J, Wood G. Combined action observation and motor imagery facilitates visuomotor adaptation in children with developmental coordination disorder. Research in Developmental Disabilities. 2020; 98:103570. https://doi.org/10.1016/j.ridd.2019.103570
دوره 17، شماره 61
پاییز 1404
صفحه 49-66

  • تاریخ دریافت 04 آبان 1401
  • تاریخ بازنگری 09 مرداد 1402
  • تاریخ پذیرش 03 آبان 1402