Could spontaneous interpersonal synchronization enhance athletes’ performance? A case report on the Japanese 100-m record race

doi:10.21203/rs.3.rs-4661387/v1

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Case Report

Could spontaneous interpersonal synchronization enhance athletes’ performance? A case report on the Japanese 100-m record race

https://doi.org/10.21203/rs.3.rs-4661387/v1

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Athletes’ performances are determined not only by individual abilities but also by environmental states, especially the behavior of competitors. Previous studies suggest that spontaneous interpersonal synchronization occurs when individuals can see/hear each other. Varlet and Richardson (2015) reported spontaneous interpersonal synchronization between Usain Bolt and Tyson Gay in the 100-m race in which Bolt broke the world record and Gay broke the US record. This report suggests that interpersonal synchronization may in some instances enhance an athlete’s performances. Here we report a new case of the potential positive effect of interpersonal synchronization on athletes’ performance. At the men’s 100-m final of the Fuse sprint held in Japan in 2021, the first-place sprinter, Yamagata, broke the Japanese 100-m record, and the second-place sprinter, Tada, set his new personal record. These two sprinters ran side-by-side throughout the race. To investigate whether interpersonal synchronization occurred between the two sprinters, we analyzed the video of the final race, which we compared to the chance level of synchronization determined from the preliminaries in which the sprinters ran in different races. Our results showed that the relative phase between the two sprinters was more consistently attracted towards inphase synchrony in the final race compared to the chance level synchronization determined from the preliminary races. This result supports the hypothesis that spontaneous interpersonal synchronization can occur between sprinters running next to each other. It is noteworthy that both world and Japanese 100-m records were set in races in which the first- and second-place sprinters synchronized their running movements. Our study provides further evidence that suggests interpersonal synchronization could enhance sprinters’ performance.

Cognitive Neuroscience

Psychology

Interpersonal synchronization

entrainment

running

gait

performance

competition

In athletic competition, performance depends not only on individual abilities but also on environmental conditions, most often including interactions with others (e.g., other athletes, spectators). In track and field running, for instance, it has been reported that the performance of athletes in the 60 m, 1500 m and 3000 m time trials is typically better in head-to-head competition compared to solo performance contexts ^1–3. Indeed, previous studies has repeatedly demonstrated that that the factors involved in this improvement are various, including aerodynamic effects ^4–6, changes in arousal level ^7,8, attentional focus ^9,10, and pacing strategy ^2,11.

In addition to these factors, the natural tendency for co-present individuals to synchronize their limb movements has also attracted attention as a potential factor influencing running performance. Varlet & Richardson (2015) investigated this possibility by examining the step-by-step synchrony that occurred between Usain Bolt and Tyson Gay in the 100 m final at the 2009 World Championships in Athletics in Berlin. In this race, Usain Bolt set a world record with a time of 9.58 seconds, while Tyson Gay, who ran next to him in second place, set a new personal record with a time of 9.71 seconds. The results revealed that the two runners’ steps were significantly synchronized during the race. Given that each runner had a unique (preferred) step frequency (SF) due to different heights and optimal stride lengths ^12,13, the emergence of such interpersonal synchronization between runners likely changed their step frequency (most likely Tyson Gay’s given he was slightly behind Usain Bolt), and therefore, their performance.

However, further work is needed to confirm and understand the occurrence of spontaneous synchronization between elite sprinters. Indeed, spontaneous synchronization between Bolt and Gay in the 100 m final at the 2009 World Championships does not seem to be consistently observed across varying video and movement analyses ¹⁴. Moreover, while interpersonal synchronization can easily be observed during comfortable walking and daily stepping activities ^15,16, synchronization is less likely to occur at faster walking speed ¹⁷. This suggests that synchronization in athletic situations that require higher movement speeds than walking is less likely to occur.

Here, we examined potential spontaneous interpersonal synchronization in the 100 m final of the Fuse Sprint 2021 (Tottori, Japan) held on June 6, 2021, in which Yamagata set a new Japanese record with a time of 9.95 seconds, and Tada, who ran in the next lane, set a new personal record of 10.01 seconds. Interestingly, the situation in this race is similar to the men's 100 m world record race in Berlin in which Bolt and Gay ran next to each other and set a historic record. Examining this race can help determine the robustness of interpersonal synchronization in high-performance contexts and identify factors that could modulate, and possibly enhance, athletic performance.

2.1 Subjects and videos

We analyzed the final race video of the Fuse sprint men's 100-m race held on June 6, 2021 in Japan. As control conditions we also analyzed the preliminary race videos. The frame rate of all videos was 30 fps. We received the videos from the videographers. In the final, Yamagata was in lane 6 and Tada in lane 5 so that both runners were in adjacent lanes. In the preliminary races, both competitors were in different heats, with Yamagata in lane 4 and Tada in lane 4. Videos in all races were taken from the side of the finish line. The videos of the final and the preliminaries can be viewed on the video-sharing site YouTube (Data S1). This study was approved by the Ethics Committee of the Graduate School of Arts and Sciences of the University of Tokyo (permit number: 865-2).

All videos were recorded with a home-use video camera (iVIS HF R62, Canon Inc., Tokyo, Japan). In general, video camera photography causes distortion at the edges of the image. The resolution of the videos was 1280×720px, and the x-coordinates of the target coordinates (right ankle and neck) were between 490px and 1085px, and the y-coordinates were between 250px and 524px, ensuring that the target coordinates were largely unaffected by distortion.

2.2 Procedure

To obtain the timing of each sprinter's steps from the videos, we digitized the joint coordinates of each sprinter's entire body using OpenPose (v1.7.0), which uses deep learning techniques to estimate human joint coordinates on images ¹⁸. The right ankle marker, which appeared most stable in the images, was used for the foot movements. Neck coordinates were used to standardize the displacement of the right ankle in the body coordinate system ¹⁹. Any apparent discrepancies between the estimated positions using OpenPose and the actual right ankle/neck positions were complemented using the manual annotation software Frame-DIAS V (Ver. 2.30R3, Q'sfix, Tokyo, Japan). From the right ankle/neck coordinates we obtained time series data of right ankle y-coordinate (vertical direction) displacement according to the neck coordinates.

Next, low-pass FIR filtering was performed on these time series in MATLAB (R2022a, MathWorks, Massachusetts). The cutoff frequency was set to 5 Hz based on the results of the residual analysis ²⁰. The start time of each race was defined as the frame rewound by the race time from the frame when the torso crossed the finish line, because the starting pistol light was not shown in the video. The start time was adjusted after upsampling the time series data of each right ankle to 300 Hz, which was achieved by spline interpolation using the interp1 function in MATLAB (R2022a), because the discrepancy from the actual start time is larger at 30 Hz.

Similar to previous studies that examined synchronization between Bolt and Gay (Blikslager & de Poel, 2017; Varlet & Richardson, 2015), the first eight steps of both athletes were excluded from the analysis. This exclusion operation was performed to align with Tada in the preliminaries, who took the slowest eighth step among the final and preliminaries of both athletes. In addition, the data after the last step before crossing the finish line were also excluded from the analysis, because the torso-thrusting motion may have affected the step periodicity just before the finish line.

The displacement of the y-coordinate of the right ankle of the two sprinters is shown in Fig. 1, where A represents the final and B the preliminaries. The horizontal axis represents the time (in seconds) elapsed from the start and the vertical axis representing the displacement. An increase in the y- coordinate displacement implies an increase in the distance between the ankle and neck, with each maximum value corresponding to the grounding of the right foot. The section analyzed is the one between the two single-dashed lines. The period of the right ankle y-coordinate displacement was similar between the two runners in both the final and the preliminaries, meaning that their stride interval remained close whether they ran separately in different races or in the same races in adjacent lanes.

2.3 Relative phase

We used relative phase to examine the relationship between the step timings of the two sprinters. In periodic movements, such as walking or running, one cycle of motion can be represented as a phase angle from 0 to 360 degrees (°), or 2π radians. Thus, the phase difference between two periodic movements (i.e., human movements) at any given time can be calculated as the difference between the phase angles of the two movements. The relative phase was calculated as:

$$\varPhi =\frac{{t}_{T}-{t}_{Y}}{{T}_{T}}\times 360^\circ$$

where ${t}_{T}$and ${t}_{Y}$ are the times at which Tada and Yamagata stepped, respectively, and ${T}_{T}$is the time between two consecutive steps by Tada. Thus, one relative phase value was obtained for each step of Yamagata. Perfect step synchronization corresponds to a relative phase of 0°. Consistent relative phase values occurring overt time can be interpreted as spontaneous synchronization.

The relative phases were calculated using the following combinations: between Yamagata and Tada in the final, and between Yamagata and Tada in the preliminaries. The preliminaries in which they ran in separate heats were used to obtain a control synchronization (i.e., a synchronization that does not occur because of a perceptual coupling but simply because the two sprinters performed the same task at the same time), as used in Varlet & Richardson (2015). Additionally, to further evaluate synchrony that may occur by chance without any interaction between the two sprinters, we also included the following data: the data combining one final and one preliminary for different sprinters (Yamagata final and Tada preliminary/Tada final and Yamagata preliminary), and the data combining the final and the preliminary for each individual sprinter. The finish time for the combination between Tada in the final and Yamagata in the preliminary was the same (10.01 seconds), and this combination allowed us to evaluate the synchronization that occurs by chance when two runners run at the same speed, regardless of the interaction between them. Although both runners had different times in the final and the preliminaries, the intrapersonal (i.e., between Yamagata final and Yamagata preliminary) time difference between the final (Yamagata: 9.95 seconds, Tada: 10.01 seconds) and the preliminaries (Yamagata: 10.01 seconds, Tada: 10.07 seconds) was 0.06 seconds, and the ratio of speed change in the final to the preliminaries was almost identical for both runners. If the change in the running phase transition from preliminary to final depended only on the change in running speed, the relative phase transition would also be the same in the preliminaries and the final, and the relative phase would have a similar distribution in the preliminaries and the final. Therefore, by analyzing the degree of synchrony in the above listed ‘control’ conditions helped validate whether any synchronization that occurred in the final was speed-dependent.

2.4 Wind speed in final and preliminaries

The wind speed data at the time each video was recorded showed a tailwind of 2.0 m/s in the final, and in the preliminaries, a tailwind of 1.7 m/s for Yamagata's heat and a tailwind of 2.6 m/s for Tada's heat (Data S2).

2.5 Statistical analysis

We conducted an independent samples T-test to compare the means of the final and preliminaries, using MATLAB R2022a (MathWorks, Inc., Natick, MA). Given the assumption of unequal variances between the two groups, we opted for Welch's T-test, a more robust version of the standard T-test that does not assume equal population variances. To perform this test, we used the ttest2 function in MATLAB. The significance level was set at 0.05. We were interested in whether the relative phase in the final was significantly different compared to the other five conditions. Therefore, we conducted pairwise comparisons between the final and the other conditions using Holm's method.

3.1 Relative phase time series

Figure 2 shows data from the final and the preliminaries depicting typical relative phase time series. The relative phase was calculated by subtracting Tada's running phase from Yamagata's, so a positive value indicates Yamagata was ahead of Tada in phase.

3.2 Relative phase distributions

Figure 3 shows the occurrence distribution of the relative phase values for each combination. It shows that relative phase values in the final were more centered and concentrated around 0° than in the preliminaries and other combinations suggesting spontaneous synchronization might have occurred. The mean absolute relative phase and the standard deviation of relative phase (SD) were summarized in Table 1.

Table 1

Mean absolute relative phase and Standard deviation of relative phase
	Mean absolute relative phase (°)	Standard deviation of relative phase
Final	13.76	8.34
Preliminaries	28.42	8.75
Tada Final - Yamagata Preliminary	47.59	22.97
Tada Preliminary - Yamagata Final	89.01	13.25
Yamagata Final - Yamagata Preliminary	60.53	15.94
Tada Final - Tada Preliminary	75.78	19.48

To determine whether the relative phase in the final was significantly different from the other five conditions, we conducted pairwise comparisons using Holm's method. The results showed that the final condition had a significantly lower mean absolute relative phase compared to each of the other five conditions. The t-values, p-values, and effect sizes (Cohen's d) for each comparison were summarized in Table 2.

Table 2

Statistical values of each combination vs. Final
Final vs.	t-value	df	Adjusted p-value	Cohen's d
Preliminaries	-5.11	33.92	< 0.001	-1.7
Tada Final - Yamagata Preliminary	10.3	21.41	< 0.001	3.43
Tada Preliminary - Yamagata Final	-19.9	28.65	< 0.001	-6.63
Yamagata Final - Yamagata Preliminary	-10.79	25.66	< 0.001	-3.6
Tada Final - Tada Preliminary	-12.13	23.03	< 0.001	-4.04

These results indicate a significantly lower mean absolute relative phase in the final condition compared to all preliminary conditions, with large effect sizes in each comparison.

Our results show that the relative phase in the final was more concentrated around 0° than in the preliminaries and the other combinations. This suggests that there was some interaction between the two sprinters in the final when they ran side-by-side, possibly resulting in phase locking.

A phase difference of 0° (in phase) is considered as the most stable point in the Haken-Kelso-Bunz (HKB; Haken et al., 1985) model of biological coordination, and the periodic movements of two individuals tend to stabilize in phase in interpersonal coordination tasks ^22,23. In the time series of relative phases reported here, the tendency to converge to 0° in the final in which the two sprinters ran side-by-side was greater than in other control combinations, indicating that a synchronization may have occurred. Furthermore, the localization of the relative phase around 0° in the final was stronger than in the other control conditions. This indicates that the shift in the relative phase distribution from the preliminaries to the final was not simply speed-dependent (i.e., not due to increased speed), suggesting that an interaction between the two sprinters in the final may have caused phase locking.

Interpersonal synchronization has been reported for a variety of movements such as clapping ²⁴, foot swinging ²⁵, hand pendulum ²⁶, rocking chair ²³, postural movement ^27–29, competitive tapping ³⁰, and side-by-side walking ^15,19,31,32. The present study supports that spontaneous interpersonal synchronization is a ubiquitous phenomenon that also occurs in non-laboratory sport competitive settings.

Importantly, growing evidence shows that auditory rhythmic stimulation can powerfully modulate and enhance human gait and running performance. Synchronization with auditory stimuli such as music or simple metronomes during exercise can improve contraction efficiency of active muscles ³³, metabolic cost ³⁴, stability of interlimb coordination ^35–37, stride interval stability ³⁸, and running performance ^34,38,39. In particular, it has been reported that auditory stimulation synchronized with the runner's stride interval improved performance in 400 m, which is classified as a sprint race ³⁹. When two sprinters run side by side each other footsteps might become auditory rhythmic stimulation influencing and enhancing performance. In the present study the footsteps tempo of Yamagata and Tada were very close in their stride interval, and each other footstep sounds might have become useful synchronized auditory stimuli that contributed to the historical records in the final.

Interpersonal synchronization and changes in performance might have also been supported by visual information. Interpersonal synchronization occurring through visual information has been shown to influence individual motor performance ^28,29. In the case of Yamagata and Tada who ran side-by-side, synchronization between the sprinters may have occurred via visual information exchanged peripherally, which may have affected their running performance. Further research will be needed to clarify the exact nature of sensory information that could potentially modify and improve individual performance in maximum effort exercises such as a 100-m race.

4.2 Limitations and Future work

These were only case observations, and the phenomenon of synchronization among top sprinters has not been statistically proven. To scientifically elucidate this phenomenon, it is necessary to analyze the running performance of sprinters in various races in the future

In this analysis, we cannot deny the possibility that noise caused by camera oscillation may have distorted the peak time of the right ankle y-coordinate displacement and affected the relative phase. Although we tried to deal with such data drift and noise as much as possible, the above limitation cannot be eliminated in the analysis of videos shot in a natural environment. In the future, we will be able to evaluate the movements of actual athletes, unaffected by data drift or other factors that distort results from ordinary private video cameras by placing objects of defined size in the video and quantifying and eliminating the effects of camera movement.

It can also be noted that other factors (changes in arousal level, attention, and others) may have contributed to the two sprinters' historic records, independent of the interpersonal synchronization.

Furthermore, the findings of this study provide important suggestions for coaching athletes. Even in track and field running, which has been regarded as an individual sport, each runner is affected by interpersonal influences. Among these interpersonal influences, synchronization, which is difficult to perceive, can affect performance without the athlete’s conscious awareness. This study provides athletes and coaches with a new perspective of synchronization as an interpersonal influence. By clarifying the relationship between interpersonal synchrony and performance, it may be possible to improve performance through training and strategic use of synchronization.

The purpose of this study was to evaluate whether interpersonal synchronization occurred between the first- and second-place sprinters in the race in which the Japanese record was set in 2021. In the final race, the synchrony between the two sprinters was higher than in the preliminaries or across separate races, suggesting that synchronization occurred between the top sprinters by running next to each other. This case of synchronization between the first- and second-place finishers in a historic record-setting race adds to the case report of Varlet & Richardson (2015) and indicates that synchronization may be a contributing factor to sprint performance. It is noteworthy that interpersonal influences also occur in an "individual sport," and quantification of interpersonal influences may contribute to improving the performance and coaching of various sports athletes in the future.

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. Video recordings of the 100-meter run analyzed in this study are available via the link in Supplementary Material Data S1. For any additional information regarding the data, please contact Hiroaki Furukawa at [email protected].

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The authors declare no competing interests.

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Could spontaneous interpersonal synchronization enhance athletes’ performance? A case report on the Japanese 100-m record race

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Abstract

Figures

1 Introduction

2 Methods

2.1 Subjects and videos

2.2 Procedure

2.3 Relative phase

2.4 Wind speed in final and preliminaries

2.5 Statistical analysis

3 Results

3.1 Relative phase time series

3.2 Relative phase distributions

4 Discussion

4.2 Limitations and Future work

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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