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Inter-Segmental Coordination of the Swimming Start among Paralympic Swimmers: A Comparative Study between S9, S10, and S12 Swimmers

Faculty of Sports Science, Ningbo University, Ningbo 315211, China
Faculty of Engineering, University of Pannonia, 8201 Veszprém, Hungary
Department of Kinesiology, University of Physical Education, Alkotás u. 44, 1123 Budapest, Hungary
Faculty of Engineering, University of Szeged, 6720 Szeged, Hungary
Authors to whom correspondence should be addressed.
Appl. Sci. 2023, 13(16), 9097;
Submission received: 9 July 2023 / Revised: 25 July 2023 / Accepted: 6 August 2023 / Published: 9 August 2023
(This article belongs to the Special Issue Performance Analysis in Sport and Exercise Ⅱ)


The swimming start, which involves interactions with both water and air, has predominantly been studied primarily in terms of spatio-temporal parameters, while its motor control aspects have received limited attention. This study aims to investigate and compare the coordination patterns between the arm and trunk, as well as the thigh and trunk, in S9, S10, and S12 Paralympic swimmers using the continuous relative phase. The study included twenty-one Paralympic swimmers, and the results showed significant differences (p < 0.05) from spm1d (ANOVA) in both arm-trunk and thigh-trunk CRP among the three classes of swimmers. Significant differences were observed in the arm-trunk CRP during the initial (0–8% of time) and end (30–41% of time) parts of the block phase. Both of these two differences are from the comparison of S10 and S12. The thigh-trunk CRP also showed significant differences at the end of the block phase (35–41% of time) and during the flight phase before entry (58–61% of time). Significant differences were observed in post hoc tests between S9 and S10 and between S12 and S10 for the first significant difference. The second significant difference was found between S12 and S10. The results indicate that Paralympic swimmers classified as S9, S10, and S12 tend to exhibit distinct inter-segmental coordination patterns during the dive start. By recognizing different patterns of motor coordination, coaches and trainers can develop individualized training methods to optimize the start performance for swimmers with different impairments (different classifications) and maximize their competitive potential.

1. Introduction

Swimming is a highly competitive sport; only a small time difference can affect the outcome of a race. Start performance is a crucial aspect of a swimmer’s performance, especially in elite competitions [1]. It has been reported that the start time can contribute nearly 30% of the swimming time in sprinting events [2]. Furthermore, it has been observed that this percentage contribution tends to increase as the race distance becomes shorter [3]. The swimming start is defined as the distance to the 15 m mark in the race [4]. In a study conducted by Vantorre et al., the start phase was further segmented into six distinct phases: the block phase, flight phase, entry phase, glide phase, leg kicking phase, and swimming phase [5]. Currently, the majority of sports biomechanics research in the field of swimming relies on traditional statistical and theoretical methods. Most of the research on swim starts has aimed to identify the most optimal technique for maximizing performance [6,7,8]. Previous studies have primarily focused on analyzing factors such as foot placement, body position, dive angle, and force production [9,10,11]. These investigations typically employ straightforward and easily interpretable data, including time, distance, speed, block height, and other related metrics. While straightforward data analysis of start performance can be helpful for coaches and swimmers to quickly identify areas for improvement and make necessary adjustments [12,13,14], it often fails to fully capture the intricate interplay between different body segments and the coordination patterns that underlie efficient movement execution [9,15]. It only focuses on the external observable aspects of the technique, without considering the intricate inter-limbs or segment adjustments [16,17,18]. Such inter-segmental coordination involves the relative behavior of one body segment about another [19]. For example, during a ball throw, various body segments, such as the shoulder, arm, and trunk, collaborate in a coordinated manner. The arm extends, the shoulder rotates, and the trunk shifts weight to generate power and accuracy in the throw. Continuous relative phase (CRP) is a measure used in motor control research to analyze the coordination between two or more segments during a movement pattern [20]. It is derived from the phase plots of the segments, which show the relationship between their movement over time [21]. Since Kelso reported the dynamics of finger oscillations, many other types of behavior have been described by using CRP [20]. Primarily utilized in the study of cyclic movements, such as walking or running, CRP analysis enables the assessment of coordination patterns among joints or limbs [22,23]. However, the application of CRP in investigating discrete movements has received relatively limited attention [24,25]. Discrete movements often involve nonlinear dynamics, where the relationship between segments is not linear or predictable. CRP analysis could capture and analyze these nonlinear dynamics, offering a deeper understanding of the complex interplay between different body segments. Julian Schardens et al. used it to characterize the inter-segment coordination (i.e., shank-thigh and thigh-sacrum pairs) during the take-off in ski jumping [26], and the authors reveal the correlation between lower inter-segmental coordination and jump length during take-off extension. There is a need for a detailed description regarding inter-segmental coordination during the swimming start. Calculating the CRP between segments and trunk during the swimming start can help identify any coordination or timing issues between different body segments that may affect their ability to generate power and propulsion during the swimming start.
Previous studies on swimming start are commonly based on able-bodied swimmers, while there is very little relevant research for disabled swimmers. The disabled swimmers may differ depending on the nature of their impairment in start performance. However, the International Paralympic Committee (IPC) has established classification systems to ensure that swimmers with disabilities compete on an equal platform, and the classification system is used at all sanctioned Paralympic competitions to determine which swimmers are eligible to compete and in which events. Swimmers are evaluated based on their level of impairment and are then assigned to a classification group that reflects their functional ability in the water. In swimming (freestyle, backstroke, and butterfly strokes), there are several sections, including one for the physically impaired swimmers (S1–S10) who have impairments such as amputations, spinal cord injuries, or muscle weakness. Swimmers with more severe physical disabilities (lower class numbers) have reduced muscle function, which can affect their ability to generate the required propulsion and power [27]. Among swimmers with visual impairments (S11–S13), the direct impact of their impairments on muscular strength may not be significant. However, their stroke technique is influenced by the absence of visual feedback during swimming [28]. The S14 swimmers have mild to moderate disabilities at the intellectual level. These swimmers tend to exhibit poor leg explosiveness [29]. The S15 swimmers have minimal impairments, which means they may not face significant limitations in muscular strength compared to other classes [30]. In the context of Paralympic swimmers, where individuals may have varying impairments, the assessment of inter-segmental coordination becomes significant. This is due to swimmers with different impairments often relying on distinct strategies and movements to generate power and propulsion during the start. A study by Conor D. Osborough et al. used the Index of Coordination by Chollet et al. [31] to examine the effect of swimming speed on inter-arm coordination in unilateral arm amputee front crawl swimmers [32]. However, there is currently a dearth of investigations specifically focusing on limb coordination during swimming starts for Paralympic swimmers. Given the diverse impairments present among Paralympic swimmers, understanding how these swimmers coordinate their segment movements during the start is important. For example, a Paralympic swimmer with lower limb impairment may rely more on upper body strength and trunk movements to compensate for limited leg functionality.
The purpose of this study is to understand the dynamic changes in the movement of arm-trunk and thigh-trunk coordination and explore whether the disability level could influence this dynamic change during the start of Paralympic swimming by using the continuous relative phase. The findings of this study will contribute to advancing our knowledge of how Paralympic swimmers coordinate their upper and lower body segments to initiate efficient propulsion and optimize their start performance.

2. Materials and Methods

2.1. Participants

Twenty-one Paralympic swimmers were categorized into three groups of their classes (S9, S10, S12) according to the classification system established by the Swimming Sports Committee of the International Paralympic Committee (IPC) [33]. Their main characteristics are presented in Table 1. All swimmers participated in the 2021 National Games and all qualified for the 2023 Asian Games. They engaged in 11 training sessions per week, with an average duration of 2.5 h per session, and had the same training program, relaxation, treatment, diet, and living conditions. All subjects were in good physical condition and exercise capacity and had no musculoskeletal system injuries or related disorders in the past 6 months. There was no muscle soreness or fatigue on the day of testing, and all tests were completed at the same time on these dates. All swimmers obtained written informed consent prior to voluntary participation in the study

2.2. Measurement System

Four Zcam E2 high-speed cameras (shooting frequency: 60 fps, resolution: 1920 × 1080, China). Three of them were placed at the edge of the pool at distances of 5 m, 10 m, and 15 m from the starting platform. The other camera was installed on the poolside 0.5 m away from the starting platform to capture the aerial action during the starting phase. A synchronizer was used to synchronize the video captured by the four cameras (Figure 1). A self-made stitching space calibration device and machine learning algorithms were used to realize seamless stitching of movement pictures captured by four cameras.

2.3. Experimental Protocol and Procedures

All tests were conducted in a 50 m pool and at the same time each day. Before the formal testing, testers arrived at the pool 2 h early, set up the apparatus and equipment, and arranged for the swimmers to perform a 15 min warm-up. The warm-up was based on their pre-competition routine so that they could perform to their maximum ability. All swimmers used kick start except for swimmers with lower body disabilities. At the beginning of the test, the tester issued a signal, and the swimmers heard the signal to start a 15 m sprint with maximum power. Each participant started five times with a 2 min rest time between each start to ensure adequate recovery of the athlete’s body. Finally, the best of the five starts was taken as the final experimental data and used for analysis.

2.4. Data Processing

The segmental angles of the trunk, arm, and thigh to horizontal in the sagittal plane are processed in Kinovea [34]. The start movement in this study is divided into phases according to J. Vantorre et al. [6]. to measure the sagittal angle (Figure 2) and sagittal angular velocity of the first four phases (block, flight, entry, and glide phases). The measurement starts when the swimmer first moves after hearing the starting signal and finishes before the swimmer starts the underwater leg downbeat. A Butterworth lowpass filter was used to process the angle and angular velocity (sample rate 100 hz, cut off 5 hz).

2.5. Statistical Analysis

Statistical analyses were conducted in Python 3.9, Anaconda 3 using the one-way ANOVA in the open-source spm1d package (version 0.4.8, available at, 25 June 2023, developed by Pataky [35]). Specifically, we used spm1d to investigate the differences in CRP between the three classes of swimmers (S9, S10, and S12). The statistical significance threshold for the analysis of variance (ANOVA) was set at 0.05. In addition, we conducted Bonferroni post hoc tests to determine whether there were significant differences between each pair of groups.

2.6. Continuous Relative Phase

The continuous relative phase is derived from the phase diagram of two segments in a motion pattern. As the segments may have different amplitudes and velocities, it has been suggested that the components of the phase diagram be normalized to avoid one segment dominating the continuous relative phase pattern [22,25,36] and make the trajectory of the phase plot smoother.
The angle and angle velocity were normalized to the interval [−1; +1] according to Equations (1) and (2)
θ n o r m = 2 θ θ m a x θ m i n θ m a x + θ m i n θ m a x θ m i n
where θ m a x is the maximum angular within start time and θ m a x is the minimum angular within start time.
ω n o r m = 2 ω ω m a x ω m i n ω m a x + ω m i n ω m a x ω m i n
where ω m a x is the maximum angular velocity within start time and ω m a x is the minimum angular velocity within start time.
After normalization procedures, calculate the phase angle according to four different quadrant formulas (Figure 3).
Finally, the continuous relative phase (CRP) of the arm-trunk and thigh-trunk was calculated using Equation (3)
C R P = D i s t a l p r o x i m a l
The coordination patterns are distinguished by the in-phase (value of 0°) and anti-phase (value of 180° or −180°) behavior. In-phase mode means that two segments rotate or move in the same direction; conversely, two segments rotate or move in different directions in anti-phase. When the value is 0° or ±180° the speed is identical [37]. However, the study by Bardy et al. [38,39] accepted a lag of ±30° to determine the coordination modes. Thus, it belongs to the in-phase mode in the case of 30° < CRP < 30°, while the anti-phase mode is considered between −180 °< CRP < −150° or 150° < CRP < 180°. In addition, Seifert, L. [39] also added the concept of an intermediate coordination mode. The intermediate phase is a term used to describe the transitional phase between the anti-phase and in-phase coordination patterns. Analyzing the peak of CRP can provide a description of the dynamic changes (Figure 4), and analysis of CRP peaks can also provide a better understanding of the leading mechanisms between the segments. When CRP is positive, it means that the phase angle of the arm or thigh is ahead of the trunk; conversely, a negative CRP represents that trunk is leading the arm or thigh.

3. Results

Figure 5 and Figure 6 provide the arm-trunk and thigh-trunk continuous relative phase (CRP) in the sagittal plane for three different groups of Paralympic Swimmers at four phases during the start. The spm1d graphs in these figures demonstrate the variations in CRP among the three classes of subjects. The plot displays the mean and standard deviation of CRP for three classes (S9, S10, S12) of swimmers in this study. Meanwhile, graph b shows the results of a spm1d (ANOVA) of these three groups. The shaded area indicates a significant difference between the groups. The following three plots c, d, and e in the figures present the Bonferroni post hoc test plots based on ANOVA.
The CRP curves in Figure 5 indicate the coordination pattern between the arm and trunk of swimmers throughout the start period for three different classes of swimmers. The CRP curve for S9 swimmers exhibits values close to zero, meaning the arm and trunk rotating synchronously for the first two-fifth of the time domain, with negative slope and values observed between 36% to 63% of the time, which reflects the trunk beginning to take the lead in the movement. Eventually, the value of CRP was still negative from 63% to 100% of the time, but with a positive slope, which indicates that there was a trend towards an in-phase mode of coordination between the arm and trunk. The CRP curve for S10 swimmers gradually changes from negative to positive values (becoming positive at 18% of the time) with a positive slope in the first 37%. This means that the trunk leads the arm until 18% of the time, after which the arm starts to lead the trunk. The CRP value begins to become negative at 44% of the time, and the slope from 36% to 58% of the time domain is negative, which implies that the trunk rotates faster at 36% of the time and leads the arm at 44% of the time. In the last two-fifths of the time, the CRP curve has a negative value with a positive slope. This period signifies the two segments gradually change from anti-phase mode to in-phase mode of coordination. The CRP curve for S12 has positive values for the first 23% of the time, a positive slope for the first 57% of the time, and negative values for the 23–57% of the time. This shows that S12 swimmers shifted from arm lead to trunk lead in the first 57% of the time. The slope of the last 40% of the time domain is similar to the trend of the S9 and S10 swimmers with positive slope and negative value. It is worth noting that the variation of S12 swimmers is larger than the other two classes.
The spm1d (Figure 5b) demonstrates significant differences between the groups at first 6% (p = 0.012) and 34–42% (p = 0.006) of the entire start time. The differences were found mainly in S10 and S12 by post hoc test plots (Figure 5e).
The CRP curves display a consistent positive slope for the initial 40% of the time among all three classes of swimmers. This gradual increase in thigh speed was reflected in the gradual change in values from negative to positive. For S9 and S12 swimmers, the CRP remains close to 0 in the 40–60% interval, indicating an in-phase rotation of the thighs and trunk. On the other hand, the CRP curve for S10 swimmers peaked at 41% and displays a negative slope in this stage afterward, combining the phase angle of an S10 athlete in Figure 4. This suggests that the phase angle of the thighs is decreasing during this period while the phase angle of the trunk is increasing. It signifies that the trunk and thighs move towards the in-phase coordination mode. During the final two-fifths of the time, all three groups showed a positive slope and value in their CRPs, suggesting that the thighs and trunk moved in a coordinated mode of anti-phase, with the thighs leading and increasing in amplitude.
The spm1d (Figure 6b) showed a significant difference in the thigh-trunk CRP curves at 35–41% (p = 0.030) and 58–61% (p = 0.037) of time. The post hoc tests revealed that the significant difference observed in the first time period was attributed to the comparisons between S9 and S10(p = 0.027), as well as between S10 and S12 (p = 0.018). In the second time period, the significant difference was found to originate from the comparisons between S10 and S12 (p = 0.030).
Table 2 shows the duration percentages of the four phases at the start for each group of swimmers, combined with the timing of the CRP curves in Figure 5 and Figure 6 that can correspond to the respective phases of the start.

4. Discussion

This study utilized CRP analysis to evaluate the arm-trunk and thigh-trunk coordinates of Paralympic swimmers. The objective was to understand the biomechanics of swimming start for Paralympic swimmers. These results show that during the start of swimming, the coordination between segments is related to the disability level.
The arm-trunk CRP (Figure 5a) shows that S12 swimmers in the first 20% of the time are significantly larger (p = 0.013) than the other two groups. These swimmers have difficulty executing their movements with external focus and visual feedback. It has been shown that visual cues can aid in timing movements and coordinating body segments [28] and visual impairment will affect the swimmer’s ability to monitor their cadence [40], and S12 swimmers are unable to accurately identify the external environment through visual cues. Thus, S12 swimmers may rely more on proprioceptive feedback to guide their movements. This can lead to a premature focus of attention on the arm in the block phase from 0% to 20% in Figure 5, causing S12 swimmers to be more likely to extend their arms earlier compared to swimmers with normal vision (S9 and S10). Additionally, the analysis of the thigh-trunk CRP for the lower limbs (Figure 6) revealed that the S10 and S9 swimmers used the anti-phase coordination mode at the initial block phase (0–12%), while the S12 swimmers’ thigh and trunk were in the intermediate-phase coordination mode during the same time duration. More likely, they do not require the level of trunk extension as much as the other two groups. This is because their flight time, as indicated in Table 2, is shorter. Their primary objective is to enter earlier rather than cover a greater distance, suggesting they may not rely too much on trunk strength before 12% of the time domain. S12 swimmers exhibited an in-phase coordinated mode during 36% to 65% of the period. Considering the information presented in Table 2, this phase can be identified as the transition point. A study by Ravensbergen et al. showed that visually impaired swimmers often earlier to reduce the risk of deviating into the lane beside them [41]. This is similar to our finding that S12 swimmers exhibit an arm-leading motion at the start of the block phase, suggesting a potential early entry strategy.
Previous studies have suggested that swimmers with lower levels of disability may perform better during the start [42]. Accordingly, the in-phase coordination mode for S9 during the initial block phase (0–5%), in which S10 and S12 showed significantly different arm-trunk CRP (p = 0.012) of intermediate-phase coordination mode, may be attributed to their more severe physical disabilities compared to the S10 and S12 swimmers. The more severe physical disabilities of S9 swimmers affected their inter-segmental coordination, leading to a limited ability to fully extend their arms. Additionally, due to the higher level of disability of S9 in the lower limbs, they may have a greater need to maintain their balance, further limiting their ability to fully extend their segments. This may explain why the thigh-trunk CRP of S9 is significantly lower than S10 at the end of block phase just before toe-off. The results of the study showed that S10 swimmers had larger CRP for both their arm-trunk and thigh-trunk during the end of the block phase (35–41%) compared to the other two groups. In particular, the thigh-trunk CRP of S10 (Figure 6) peaked in this period, which could be because S10 swimmers do not need extra attention on balance control so they can focus on maximizing their leg pushing off the block. Burkett found that S10 swimmers can maintain a better-streamlined position than S9 swimmers during the underwater phase [42]. Our study revealed that S10 swimmers exhibited more frequent transitions in segmental leading, reflected in both arm-trunk and thigh-trunk CRP curves. This suggests that S10 swimmers dynamically adjusted their segmental leading modes to optimize their starting performance and maintain streamlined in various positions. Therefore, S10 has a peak, whereas both S9 and S12 swimmers do not show a distinct peak and instead demonstrate an in-phase coordination mode during this period. According to Trembley and Fielder, the most effective swim-starts involve leaving the block quickly, covering a significant distance in the air, and executing a clean entry into the water [43]. S10 swimmers exhibited a larger percentage of the flight phase compared to the other two groups (Table 2) and employed a thigh-leading coordination pattern during the flight phase, while the S9 and S12 swimmers adopted two segments of synchronously rotating in the in-phase coordination mode. Consequently, the utilization of a thigh-leading coordination pattern during the start may facilitate swimmers in achieving longer flight distances.
A previous study has shown the importance of distance visual acuity in physical activity [44]. Without this visual feedback, it is difficult to synchronize the timing of limb and trunk actions effectively. To compensate for the limitations in visual feedback, S12 swimmers may rely on alternative sensory cues, such as kinesthetic awareness and auditory feedback [45], to gather information about their body position and movement. However, this alternative feedback may not provide the same level of accuracy and timing precision as visual feedback, leading to increased variability in their movement coordination patterns. The highest variability of the arm-trunk and thigh-trunk CRP in our study was found at S12 (Figure 5 and Figure 6). Conversely, S9 swimmers exhibited comparatively lower variability in their CRP curves (Figure 5 and Figure 6). The reduced variability observed in S9 swimmers may be attributed to their higher level of disability in comparison to the other two groups. The higher degree of disability may lead to a limited range of motion [46], which suggests that individuals with greater levels of disability tend to exhibit decreased segmental variability.
By analyzing the arm-trunk and thigh-trunk CRP among three groups, S9, S10, and S12 swimmers chose different starting strategies due to their degree of disability or type of disability. In the case of S9 swimmers, their disability resulted in a very limited range of motion in their limbs. In Cavaggioni L’s study, the S9 swimmer underwent specific preventive dry-land training based on postural alignment and slow-velocity resistance training to enhance his lower body muscle strength and improve dive start [47]. It is aligned with the present study, highlighting the importance for S9 swimmers of augmenting their thigh strength while maintaining proper balance, and emphasizing the need for the thighs to lead the trunk during the flight phase of the coordination mode. This study suggests that S12 swimmers adopted an arm-leading coordination pattern at the beginning of the block phase (Figure 5), possibly due to a lack of trunk strength training. AA Dingley performed prone bridge and swimmer’s roll for visually impaired swimmers to increase trunk strength and improve core activation and control, and found a significant improvement in swimmers’ start performance after the intervention [48]. Therefore, it is necessary to direct the swimmer to activate their trunk muscles. Subsequently, the power can gradually be transferred to the limbs, potentially increasing the duration of the flight phase. By emphasizing the importance of trunk engagement and coordinated limb movements, S12 swimmers may be able to optimize their performance during the start and enhance their airborne phase. These training strategies aim to address the specific needs and challenges faced by swimmers in different disability classes, facilitating their dive start performance.
One limitation of this study is the small number of Paralympic swimmers who participated, as only three classes (S9, S10, S12) were included. In future perspectives, further investigations could expand the understanding of inter-segmental coordination in Paralympic swimmers during the start by exploring comparisons between physically impaired swimmers and intellectually impaired swimmers. Furthermore, incorporating physiological measures, such as heart rate monitoring, in combination with inter-segmental coordination analysis during the swimming phase may yield interesting findings. Heart rate during physical activity is an indicator of an individual’s physical fitness level, which can reflect energy requirements and physiological responses during swimming [49]. Integrating heart rate monitoring into the analysis could help establish connections between movement coordination, physical effort, and stroke efficiency [50]. On the other hand, as with most CRP analyses, the calculation of CRP curves can be altered by low-frequency components in the raw data, resulting in errors in the mean [51]. However, the normalization procedure used in the present study was able to reduce this error. Therefore, this factor is unlikely to bias the results of this study.

5. Conclusions

This study revealed notable differences in both arm-trunk and thigh-trunk CRP of the three groups. Compared to the other two groups, S10 swimmers exhibited a more frequent transition of segmental leading between both arm-trunk and thigh-trunk. On the other hand, S9 swimmers displayed more in-phase movement in arm-trunk CRP, which can be attributed to their higher level of physical disability compared to S10 and S12 swimmers. These in-phase coordination patterns may help them maintain balance and streamline entering the water. Lastly, S12 swimmers appeared to be more arm-leading while pushing off the block and adopting an earlier water entry strategy. This study underscores the importance of a personalized approach to training and coaching, which takes into account the unique requirements of Paralympic swimming, and provides valuable insights for coaches to design effective training programs by tailoring training programs to individual swimmers’ specific needs and abilities.

Author Contributions

All authors have made substantial contributions to the manuscript. Z.Z., S.L. and Y.G. were responsible for the conception and design of the study. Z.Z. and L.Y. were responsible for data acquisition and data processing. Z.Z., L.Y., S.L., Y.L. and Z.R. were responsible for data analysis and interpretation and drafting the article. S.L., Z.G. and Y.G. revised the manuscript critically. All authors have read and agreed to the published version of the manuscript.


This work was supported by the Zhejiang Provincial Natural Science Foundation of China for Distinguished Young Scholars (LR22A020002), the Zhejiang Provincial Key Research and Development Program of China (2021C03130), the Zhejiang Provincial Natural Science Foundation (LTGY23H040003), Ningbo key R&D Program (2022Z196), the Ningbo Natural Science Foundation (20221JCGY010532, 20221JCGY010607), and the Zhejiang Rehabilitation Medical Association Scientific Research Special Fund (ZKKY2023001).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Human Ethics Committee in the Research Institute of Ningbo University (GACIA20210051).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data that support the findings of this study are available on reasonable request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Equipment layout diagram regarding camera set-up.
Figure 1. Equipment layout diagram regarding camera set-up.
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Figure 2. Diagram of swimmer’s segmental angle.
Figure 2. Diagram of swimmer’s segmental angle.
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Figure 3. Phase angle (Φ) definition based on a phase plot of normalized angle (θ) and normalized angular velocity (ω).
Figure 3. Phase angle (Φ) definition based on a phase plot of normalized angle (θ) and normalized angular velocity (ω).
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Figure 4. The workflow for data analysis.
Figure 4. The workflow for data analysis.
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Figure 5. (a) CRP curves of arm-trunk. (b) The results of the spm1d (one-way ANOVA). (c) Post hoc test plots between S9 and S10. (d) Post hoc test plots between S9 and S12. (e) Post hoc test plots between S10 and S12.
Figure 5. (a) CRP curves of arm-trunk. (b) The results of the spm1d (one-way ANOVA). (c) Post hoc test plots between S9 and S10. (d) Post hoc test plots between S9 and S12. (e) Post hoc test plots between S10 and S12.
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Figure 6. (a) CRP curves of thigh-trunk. (b) The results of the spm1d (one-way ANOVA). (c) Post hoc test plots between S9 and S10. (d) Post hoc test plots between S9 and S12. (e) Post hoc test plots between S10 and S12.
Figure 6. (a) CRP curves of thigh-trunk. (b) The results of the spm1d (one-way ANOVA). (c) Post hoc test plots between S9 and S10. (d) Post hoc test plots between S9 and S12. (e) Post hoc test plots between S10 and S12.
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Table 1. Demographic characteristics of the study group.
Table 1. Demographic characteristics of the study group.
GroupType of DisabilityNumberAge (Year)Weight (kg)Height (cm)
S9Lower limb/Upper limb617.2 ± 2.352.2 ± 6.9170.4 ± 4.3
S10Lower limb/Upper limb723.4 ± 5.975.4 ± 6.2179.4 ± 2.8
S12Visual impairments820.8 ± 3.771.8 ± 7.6180.7 ± 7.9
Table 2. Percentage of time for the four phases (mean ± SD) (* p < 0.05).
Table 2. Percentage of time for the four phases (mean ± SD) (* p < 0.05).
Phase Duration (%)/GroupsS9S10S12p-Value
Block phase40.33% ± 2.3038.83% ± 1.7538.07% ± 4.460.219
Flight phase21.35% ± 1.2322.04% ± 2.7114.39% ± 9.130.000 *
Entry water phase20.56% ± 1.6623.38% ± 1.9325.24% ± 1.990.856
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MDPI and ACS Style

Zhou, Z.; Li, S.; Yang, L.; Gao, Z.; Lin, Y.; Radak, Z.; Gu, Y. Inter-Segmental Coordination of the Swimming Start among Paralympic Swimmers: A Comparative Study between S9, S10, and S12 Swimmers. Appl. Sci. 2023, 13, 9097.

AMA Style

Zhou Z, Li S, Yang L, Gao Z, Lin Y, Radak Z, Gu Y. Inter-Segmental Coordination of the Swimming Start among Paralympic Swimmers: A Comparative Study between S9, S10, and S12 Swimmers. Applied Sciences. 2023; 13(16):9097.

Chicago/Turabian Style

Zhou, Zhanyi, Shudong Li, Luqi Yang, Zixiang Gao, Yi Lin, Zsolt Radak, and Yaodong Gu. 2023. "Inter-Segmental Coordination of the Swimming Start among Paralympic Swimmers: A Comparative Study between S9, S10, and S12 Swimmers" Applied Sciences 13, no. 16: 9097.

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