**Simple Assessment of Height and Length of Flight in Complex Gymnastic Skills: Validity and Reliability of a Two-Dimensional Video Analysis Method**

**Christoph Schärer 1,2,\*, Luca von Siebenthal 1, Ishbel Lomax 1, Micah Gross 1, Wolfgang Taube <sup>2</sup> and Klaus Hübner <sup>1</sup>**


Received: 28 August 2019; Accepted: 18 September 2019; Published: 23 September 2019

**Abstract:** In artistic gymnastics, the possibility of using 2D video analysis to measure the peak height (hpeak) and length of flight (L) during routine training in order to monitor the execution and development of difficult elements is intriguing. However, the validity and reliability of such measurements remain unclear. Therefore, in this study, the hpeak and L of 38 vaults, performed by top-level gymnasts, were assessed by 2D and 3D analysis in order to evaluate criterion validity and both intrarater and interrater reliability of the 2D method. Validity calculations showed higher accuracy for hpeak (±95% LoA: ±3.6% of average peak height) than for L (±95% LoA: ±7.6% of average length). Minor random errors, but no systematic errors, were observed in the examination of intrarater reliability (hpeak: *CV%* = 0.44%, *p* = 0.81; L: *CV%* = 0.87%, *p* = 0.14) and interrater reliability (hpeak: *CV%* = 0.51%, *p* = 0.55; L: *CV%* = 0.72%, *p* = 0.44). In conclusion, the validity and reliability of the 2D method are deemed sufficient (particularly for hpeak, but with some limitations for L) to justify its use in routine training of the vault. Due to its simplicity and low cost, this method could be an attractive monitoring tool for gymnastics coaches.

**Keywords:** two-dimensional video analysis; validity; reliability; quantitative biomechanical parameters; artistic gymnastics

#### **1. Introduction**

Video analysis is common in elite sports and covers different areas of application. In individual sports, especially acrobatic sports, video analysis is used to compare and improve complex skills [1]. For quantifying biomechanical aspects of such skills, such as score-relevant kinematic variables of vaults in artistic gymnastics, 3D motion capture (3D video analysis) is used. [2,3]. By means of video analyses, Brehmer and Naundorf [4] created reference values for kinematic parameters, indicating the safe execution of vaults. To make use of such reference values, measuring certain kinematic parameters in routine training becomes crucial, so that gymnasts' performances can be compared with the requirements of certain vaults. In regard to monitoring training progress, using video analysis during routine training is intriguing [2,3].

The gold standard for complex kinematic analyses is 3D motion capture, with which movements can be analyzed in sagittal, frontal, and transversal planes simultaneously [5]. However, precise 3D motion capture is associated with considerable financial, spatial, and temporal issues, and is therefore uncommon in routine training settings [6]. Two-dimensional video analysis (2D analysis),

if sufficiently accurate, could offer a more practical alternative for measuring kinematics during training, especially since advancements in smartphone and tablet technology are continually making high-definition video capture and analysis more convenient. Aside from convenience while capturing motion, 2D video is faster, cheaper, and requires less prior knowledge compared to 3D analysis [1,7]. Nonetheless, although multiple studies showed moderate validity compared to 3D motion capture and high intrarater reliability of 2D analysis when examining joint angles during simple movements, such as single-leg squats and running [1,5–7], the validity and reliability of 2D video analysis for complex skills in acrobatic sports are unclear and must be scientifically assessed before this method can be recommended for gymnastics. The validity and reliability of 2D analysis were deemed sufficient for measuring the flight time and height of vertical jumps, when compared to optical measurement systems (Opto Jump, Microgate, I) [8] or to a force plate [9]. Further, 2D analysis was deemed valid (ICC = 0.8) and reliable (ICC > 0.85) for measuring joint angles during the more complex skill of baseball pitching, as long as the camera was placed properly [1], so the possibility of it being useful in gymnastics seems worthy of investigation.

In summary, the studies mentioned above offer justification for using simple, time-saving, and cost-effective 2D analysis for simple lower-extremity movements based on good validity and reliability compared to gold-standard methods. However, in contrast to movements in previous studies, artistic gymnastics involve highly complex movements that are performed with high accelerations and velocities. Therefore, the aim of this study was to investigate criterion validity (comparison of 2D to 3D analysis) and both intrarater (test-retest) and interrater (equivalence of two assessors) reliability of 2D video analysis for the peak height (hpeak) and length of flight (L) of vaults in artistic gymnastics.

#### **2. Materials and Methods**

Twenty-two junior and international elite gymnasts (female: n = 5; male: n = 17) volunteered to participate in the study. All subjects gave written informed consent before participating in the study. All study procedures were approved by the ethics committee Bern (17.01.2017; Project-ID: 2016-01970) and conducted in accordance with the current version of the Declaration of Helsinki, the ICH-GCP, ISO EN 14155, and all national legal and regulatory requirements.

In total, 38 vaults were used for assessment. These included vaults from the three most important vault categories (handspring, Tsukahara, and Yurchenko) and comprised a variety of different sagittal plane rotations (tuck/double tuck, pike/double pike, and layout), which were combined with up to three turns around the longitudinal axis. These vaults were simultaneously recorded with conventional 2D video and a 3D motion capture system (Vicon Motion System, Denver, CO, USA) and analyzed to determine hpeak and L in the second flight phase.

For 2D analysis, vaults were filmed using an iPad (iPad Pro 9.7", Apple Corporation, Cupertino, CA, USA) at 100 frames/s. The lens of the iPad was placed at a height of 1.55 m and at a distance of 10 m from the vaulting table, so that the take-off, first and second flight phases, and landing were all visible. The height and width of the image were calibrated within the analytical software (Dartfish SA, Fribourg, CH) by using a rod of known length (2.78 m) that was held vertically and horizontally along the landing zone (Figure 1). With the Dartfish software, hpeak was measured as the vertical distance between the landing mat and the gymnast's center of gravity at its highest point during the second flight phase of the vault. For this, the gymnast's center of gravity was estimated visually in the video frame at which the maximal height was deemed to have occurred. L was determined as the horizontal distance between the ankle at the foot's first contact with the mat upon landing and the end of the vaulting table (Figure 2). The software then automatically calculated hpeak and L by using the reference height and length.

For the 3D analysis, all vaults were captured by 14 Vicon Vantage Cameras (Vicon Motion System, Denver, CO, USA) that were arranged in two planes: eight cameras were placed at a height of 5.50 m and six were placed at a height of 1.70 m (Figure 3) above ground level. Forty-three reflective markers were placed on the gymnasts' bodies, according to the Vicon Plug-in Gait model [10] (Figure 4). For

capturing and, afterward, determining hpeak and L, Vicon Nexus, version 2.6, Vicon Motion System, Denver, CO, USA) software was used.

The 2D videos were analyzed by a first-time assessor and an experienced assessor. The first-time assessor was only briefly introduced to the relevant functions of the software (reference measurements) and the important aspects of the measurement of hpeak and L (e.g., determination of the center of gravity at the maximum height of flight) before evaluating the trials.

The parameters determined by the first-time assessor (2D1) were compared to those obtained by 3D analysis to assess criterion validity of 2D analysis (2D1 vs. 3D). Further, the parameters were determined with Dartfish (Dartfish SA, Fribourg, CH) by the same assessor at two different points in time (first measurement: 2D1; second measurement: 2D2) and by an experienced assessor (2De) to verify intrarater (2D1 vs. 2D2) and interrater reliability (2D1 vs. 2De).

**Figure 1.** 2D calibration: calibration of measuring range by definition of reference height and width with the calibration rod (2.78 m) in the 2D-video software Dartfish (Dartfish SA, Fribourg, CH).

**Figure 2.** 2D measurements: determination of peak height (hpeak) and length of flight (L) for a "Yeo" Vault (CoG: position of center of gravity at the highest point of the second flight phase; A: position of the ankle at first foot contact).

**Figure 3.** Placement of 3D cameras: positioning of the 14 Vicon Vantage Cameras (C1–C14) in an upper and lower plane for three-dimensional recording of vaults.

**Figure 4.** Plug-in Gait model: positioning of 43 markers for 3D analysis, attached to the athlete according to Vicon Plug-in Gait model [10].

Mean, standard deviation, Pearson's correlation coefficient (r), random error (*CV%*), typical error (*TE*), and systematic error (t-test: p) of hpeak and L measurements were calculated to determine criterion validity (3D vs. 2D1) and both intrarater (2D1 vs. 2D2) and interrater reliability (2D1 vs. 2De), according to Hopkins et al. [11]. The comparison between the 3D and 2D1 measurements (criterion validity) is displayed in a Bland–Altman diagram [12]. In order to determine the influence of lateral displacement at landing on the accuracy of the 2D measurements, the relationship between the difference in L (2D–3D measurement) and displacement along the *x* axis (to the left or right) was calculated. The level of statistical significance was set to p < 0.05. Data analysis was conducted using Microsoft Excel spreadsheets (Microsoft Excel 2016, Microsoft Corporation, Redmond, WA, USA).

#### **3. Results**

Two-dimensional analysis (2D1) showed small differences in mean compared to 3D analysis (Table 1). The ±95% limits of agreement corresponded to measurement errors of ±3.6% for hpeak and ±7.6% for L (Figure 5). Regarding the validity and reliability of 2D analysis, high correlation coefficients and minor random errors for the hpeak and L of vaults were found (Table 2). In contrast, there was a tendency for a systematic error for hpeak with 2D compared to 3D analysis. Further, we found a significant correlation between the lateral displacement (*x* axis) at landing and the difference in L between 2D and 3D analysis (r = 0.58; p < 0.01). The ex post facto power analysis revealed a power of ~1 for all investigated correlations. The data of all measurements in this study can be found in the supplementary material (Table S1).

**Table 1.** Mean (± standard deviation) of peak height (hpeak) and length of flight (L) of all recorded vaults (n = 38) for 3D (Vicon Motion System, Denver, USA) and 2D analyses (Dartfish SA, Fribourg, CH; 2D1: first-time assessor; 2D2: second measurement of first-time assessor; 2De: expert assessor).

**Figure 5.** Validity: Bland–Altman diagrams comparing 2D and 3D analyses of peak height (hpeak) and length of flight (L) of vaults (n = 38). 2D1: two-dimensional video analysis with Dartfish SA of a first-time assessor); 3D: three-dimensional motion capture with Vicon Motion System).


**Table 2.** Random error (CV%), typical error (TE), correlation coefficient, and systematic error (p) of peak height (hpeak) and length of flight (L) of vauls, when comparing first 2D video analysis (2D1) evaluations to 3D motion capture (validity) and to second 2D analysis (intrarater reliability), as well as second 2D video analysis (2D2) and expert 2D video analysis (2De) (interrater reliability).

#### **4. Discussion**

This paper is the first to evaluate the validity and reliability of 2D video analysis of the hpeak and L of vaults in artistic gymnastics. Compared to 3D analysis (validity), 2D analysis showed smaller ±95% limits of agreement for hpeak (±3.6%) than for L (±7.6%). Further, we found smaller random errors for hpeak (CV% = 2.24%) than for L (CV% = 4.64%). In contrast, there was a tendency toward a systematic error of hpeak (p = 0.06), but not for L (p = 0.43). Regarding reliability, the hpeak and L of vaults can be repeatedly (intrarater reliability: hpeak: CV% = 0.44%, r = 0.99; L: CV% = 0.87%, r > 0.99) and independently (interrater reliability: hpeak: CV% = 0.51%, r = 0.99; L: CV% = 0.72%, r > 0.99) determined by 2D analysis.

The results support 2D video analysis as a valid measurement tool—particularly for determining the hpeak, but slightly less so for the L, of vaults in gymnastics. Our findings are in line with those of Balsalobre-Fernandez, Tejero-Gonzalez, del Campo-Vecino, and Bavaresco [9], who have shown that 2D analysis is a valid technique for accurately measuring the flight height of vertical jumps. Thus, under the described measurement conditions, an increase of at least 6.16 cm in hpeak or of at least 10.59 cm in L, measured by 2D video analysis, can be considered a true performance increase.

Differences in the validity between the hpeak and L of vaults, as shown in the Bland–Altman diagram, may have several reasons. The most obvious is that 2D analysis measures the height and length of flight in the sagittal plane only. Accordingly, lateral displacement at the landing cannot be detected by 2D analysis and presents a possible confounding factor. This was shown by the significant relationship between lateral displacement upon landing and the difference between 2D and 3D determinations of L. This result supports research by Oyama, Sosa, Campbell, and Correa [1], who compared 2D to 3D analysis of joint angles during complex movements. They found that 2D analysis is a valid measure only when cameras are placed perpendicular to the segment of interest. This limitation of 2D analysis was less important for the measurement of hpeak, because the lateral displacement is at its maximum at landing, long after the attainment of hpeak. Further, since L was determined as the distance between the vaulting table and the ankle, even straddled legs at landing may result in a lateral displacement and may lead to a measurement error of 2D analysis. In contrast, hpeak was measured vertically from the landing mat to the center of gravity. Therefore, the determination of hpeak did not depend on the position of one single extremity but on the highest point on the center of gravity's smooth trajectory.

Another reason for the less accurate measurement of L could be the quality of the 2D videos (resolution and frame rate). The still frame at landing was often slightly blurred due to the velocity of the recorded movement. Therefore, it was difficult in some cases to determine the position of the ankle precisely, and, for this reason, small measurement errors may have occurred. In contrast, the slightly blurred image did not affect the determination of the center of gravity for the measurement of hpeak, since the determination of the center of gravity depends on a global view of the body and not on a small single part of the body.

One more reason for the larger inaccuracy in the determination of L may be the slight bend in the calibration rod when it was held horizontally to scale the image width (Figure 1). This would have caused the reference length to be slightly too long, although this effect was too small to be apparent in our results (nonsignificant p-value).

In this study, we observed a tendency toward a systematic underestimation of hpeak with 2D analysis. Since the measurements of the experienced assessor were not statistically different from the values of the first-time assessor, it can be assumed that both assessors encountered the same basic problem that may have led to this tendency. In particular, it was difficult to determine the zero-point on the landing mat vertically underneath the highest point of the center of gravity during the second flight phase. We assume that this was the reason for the (almost significant) underestimation of hpeak. Nonetheless, considering the small measurement error when determining hpeak, 2D analysis may be considered a valid method. This knowledge is especially worthwhile since the height of flight dictates the potential to perform somersaults and twists during the second flight phase, and it is therefore an important performance-determining factor for vaults.

When comparing 2D analysis at two consecutive points in time, the variation coefficients of the hpeak and L of vaults were very low. For instance, the differences of 2D analysis were only 1.21 cm (hpeak) and 1.98cm (L), at a mean height of 2.75 m and a mean length of 2.28 m. These minor random errors are likely due to slightly different definitions of the zero-points (on the landing mat or at the end of the vaulting table), or of the gymnast's center of gravity (hpeak) or ankle (L), rather than a different determination of the frame at which hpeak or L were determined. Therefore, the almost perfect correlation of the first and second 2D analysis and the low variation coefficient values demonstrate a very high intrarater reliability. Thus, 2D analysis using Dartfish (Dartfish SA, Fribourg, CH) is a reliable and reproducible measure for the hpeak and L of vaults. This result is in line with the findings of Maykut, Taylor-Haas, Paterno, DiCesare, and Ford (2015), who, among other things, examined intrarater reliability of 2D analyses of joint angles during running. They measured kinematic variables during running on a treadmill with the same video analytical software we used (Dartfish SA, Fribourg, CH), and they reported excellent intrarater reliability [7]. Other studies have also shown 2D analyses to be reliable for measuring joint angles [6] and flight height [9].

Lastly, we compared the values of hpeak and L evaluated by an experienced assessor with those evaluated by a first-time assessor. Our results show that the hpeak and L of vaults are similar, as the coefficients of variance are low and the correlations are high. In this context, it should be mentioned that a brief introduction to the measurement software and determination of center of gravity is sufficient but indispensable. Therefore, 2D analysis is a straightforward measurement tool, where values of an inexperienced assessor, for example, those evaluated by a coach, are comparable to those of an expert. Therefore, our results show good interrater reliability with 2D analysis.

When evaluating data-collection procedures, it is important to evaluate practicality and not only validity and reliability. As there are few studies regarding the validity and reliability of 2D analysis, comparisons are difficult. Nevertheless, our results are similar to the results reached by Brehmer and Naundorf [4], as well as Schurr, Marshall, Resch, and Saliba [5], in regard to validity. As such, 2D analysis seems to be a reasonable, inexpensive, and portable alternative to 3D motion capture analysis. Furthermore, 2D analysis is time efficient, as video analysis of the hpeak and L of complex skills only takes about one minute for practiced evaluators. Additionally, the equipment needed for 2D analysis (video camera, tripod, analytical software, and calibration rod) is normally readily available in an artistic-gymnastics facility, making the described method an easy and cost-effective analytical tool. Lastly, even first-time assessors can precisely determine the important parameters of complex skills if they are briefly introduced to the measurement method. Thus, 2D analysis is a useful analytical tool for practical use in training and for scientific research, as the financial, spatial, and temporal costs are minimal.

#### **5. Conclusions**

This study evaluated the validity and reliability of 2D video analysis of the hpeak and L of vaults in artistic gymnastics. We conclude that 2D video analysis is a valid and reliable alternative to 3D motion capture, particularly for determining the hpeak, but slightly less so for the assessment of the L, of vaults. Thus, the ease of use and cost-effectiveness of 2D analysis, along with the results from this study, support the use of 2D analysis in routine training and scientific research.

**Supplementary Materials:** The following are available online: http://www.mdpi.com/2076-3417/9/19/3975/s1. Table S1. Supplementary material (raw data).

**Author Contributions:** Conceptualization, C.S. and L.v.S.; methodology, C.S. and L.v.S.; formal analysis, C.S. and L.v.S.; investigation, C.S., L.v.S., and M.G.; data curation, C.S., L.v.S., and M.G.; writing—original-draft preparation, C.S. and I.L.; writing—review and editing, K.H. and W.T.; supervision, K.H. and W.T.; project administration, C.S.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflicts of interest.

#### **References**


© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Shoe Cushioning E**ff**ects on Foot Loading and Comfort Perception during Typical Basketball Maneuvers**

#### **Xini Zhang 1, Zhen Luo 1, Xi Wang 1, Yang Yang 1, Jiaxin Niu <sup>1</sup> and Weijie Fu 1,2,\***


Received: 21 August 2019; Accepted: 12 September 2019; Published: 17 September 2019

**Abstract:** Purpose: This study aimed to explore the relationship between foot loading and comfort perception in two basketball shoes during basketball-specific maneuvers. Methods: Twelve male collegiate basketball players were required to complete three basketball maneuvers (i.e., side-step cutting, 90◦ L-direction running, and lay-up jumping) in two basketball shoe conditions (shoe L and shoe N, with different midsole cushioning types). Two Kistler force plates and a Medilogic insole plantar pressure system were used to collect kinetic data (i.e., impact force, peak loading rate, and plantar pressure variables). Perception scales were used to evaluate comfort perception. Results: No significant difference was observed between the two shoes during maneuvers in terms of ground reaction force. However, the plantar pressure of shoe L in the midfoot and lateral foot regions was significantly greater than that of shoe N during side-step cutting and lay-up jumping. Shoe N was significantly superior to shoe L, especially in dynamic scale in terms of the perception of comfort. The plantar pressure and perception characteristics in the two shoes were significantly different but inconsistent with each other. Conclusion: The biomechanical characteristics of the shoes themselves and the perception evaluation of the athletes should be considered in comprehensive shoe-cushioning design and evaluation.

**Keywords:** basketball shoe; comfort perception; foot loading; plantar pressure; maneuver

#### **1. Introduction**

In basketball, the lower limbs of athletes are subjected to large impact forces during each landing [1]. Players complete 70 jumps/landings in a single game and attenuate impacts of up to nine times their body weight every time [2], which increases the risk of knee and ankle injuries [3]. Reducing impact forces (which includes both magnitude and loading rate characteristics) may help prevent foot injuries [4]. The shock absorption characteristics and comfort of basketball shoes, as core equipment of the sport, have important influences not only on the performance of the players but also on the prevention of lower extremity injuries [5]. The impact force and pressure distribution characteristics between the feet and the shoes must be understood to effectively optimize the technical movements, reduce foot injuries, and improve the design of specialized shoes [6]. However, the existing studies on foot loading have mainly focused on common gait characteristics, such as walking and running [7,8], and studies on specific sports maneuvers, such as cross-over running and lay-up jumping [9–11], are limited.

Meanwhile, comfort and stability have been identified as the principal factors of specialized sports shoes [12], in addition to meeting the functional requirements of specific sports and strengthening the foot protection function [13]. However, these factors are easily neglected. The comfort of basketball shoes is closely related to the performance of basketball athletes, as well as to ankle injury and its prevention [2]. The subjective perception scale has been proven to be an effective and credible method for assessing the aforementioned variables [14,15]. Hennig et al. [16] found that a close relationship exists between runners' subjective perception of shoes' cushioning performance and their impacts on plantar pressure during running. Meanwhile, foot comfort is also closely related to the impact load on the lower limbs at initial contact [17]. Thus, the functionality and comfort of basketball shoes for typical maneuvers in basketball must be explored through both the subjective perception and foot biomechanical tests [18].

Therefore, the current study aims to determine the effect of different basketball shoes on the ground reaction force (GRF) and plantar pressure characteristics in three typical basketball maneuvers and to further understand foot loading characteristics in basketball and their relationship with comfort through the subjective perception scale evaluation of basketball shoes. It was hypothesized that wearing different shoes would affect comfort perception, and correspondingly change GRF and plantar pressure characteristics during basketball maneuvers.

#### **2. Materials and Methods**

#### *2.1. Participants*

Twelve healthy male collegiate basketball players (age: 23.1 ± 2.0 years; height: 176.3 ± 4.5 cm; body mass: 70.5 ± 7.5 kg) with an average of 8.4 years of experience in basketball events were recruited for this experiment. An observational cross-sectional research design according to the Strengthening The Reporting of OBservational Studies in Epidemiology (STROBE) criteria [19,20]. The inclusion criteria were: (1) at least five years of experience in basketball events; (2) none has suffered musculoskeletal injuries of the lower extremity over the last six months; (3) none has engaged in strenuous training within 24 h. A two-tailed *t*-test was executed via the G\*Power 3.1 software to determine whether a sample size of 12 was sufficient to minimize the probability of type II errors for all the variables (P = 80% at α = 0.05). All the participants signed an informed consent form, and ethical approval was granted by the Institutional Review Board of Shanghai University of Sports prior to the study (2017007).

#### *2.2. Shoes and Instrumentations*

Two types of U.S. size nine basketball shoes were used in this study. One of the shoes was a new sample provided by a local sports science laboratory (hereinafter referred to as shoe L), and the other (Figure 1) was a commercially available type with a popular international brand (hereinafter referred to as shoe N). The following are some details of the property of Shoe N: (1) upper: Black synthetic leather and Phyposite technology—Breathable tongue inner sleeve with a traditional lacing system; (2) midsole: Phylon midsole design that minimizes weight while maximizing cushioning with animpact absorption system; (3) outsole: Non-traditional outsole to reduce weight and optimize traction. Overall, the two types of shoes were similar in the abovementioned materials, design, color, weight (≈530 g), and so on, and only differed in the impact absorption systems of the midsole.

Two 90 cm × 60 cm three-dimensional force plates (9287B, Kistler Corporation, Switzerland) were utilized to collect GRF data, with a sampling rate of 1200 Hz.

The insole measurement system (Medilogic Corporation, Germany) was used to capture the plantar pressure of different regions. This system has been validated [21]. Each insole was calibrated using the manufacturer's calibration device (T&T medilogic Medizintechnik GmbH, Schönefeld, Germany) prior to the study. The size of the pressure insole was 8/9 according to the participants' foot size. The pressure insole consisted of 225 pressure sensors (0.6 cm × 0.4 cm), with a pressure range of

0-64 N/cm2 and a maximum sampling rate of 300 Hz (Figure 2a). The plantar regions were divided into five parts, namely, the forefoot, the midfoot, the heel, the lateral, and the medial (Figure 2b).

**Figure 1.** Basketball shoes (shoe N) from a famous international manufacturer.

**Figure 2.** (**a**) Composition of insole pressure sensors with a pressure range of 0–64 N/cm2; (**b**) region division of plantar pressure, including the forefoot, the midfoot, the heel, the lateral, and the medial parts.

#### *2.3. Experimental Protocol*

Three typical maneuvers, which are the most frequently used in basketball games according to the video observation and the coach interview, were selected, namely, side-step cutting (SS), 90◦ L-direction running (90◦ LR), and lay-up toe-off (LUTO) and touch-down (LUTD). The sports surface used in this study is the most common wooden floor used in basketball games. The participants first set their pace according to their personal movement habits and then tried their best to complete the movements. They were required to achieve the three typical maneuvers (SS, 90◦ LR, and lay-up) in the two different shoes in random order. Five successful trials were obtained for each condition. The pressure insoles were placed flat in the shoes before the experiment, and data were transmitted to the computer in real-time via a wireless receiver. The participants were required to familiarize themselves with the maneuvers before the formal tests began. The familiarization period for each participant was 10–15 min. To avoid the influence of fatigue on the results, 1–2 min breaks were given between each trial [22].

The perception-comfort scale used in this experiment was adapted from the perception scale provided by a famous shoe research center in the US. The scale includes two parts, namely, general fit and dynamic scale (Figure 3). The indices of the general fit test include the toe-box height, the toe-box width, the ball girth, the waist/instep, the elasticity at the heel, and the shoe length. The index scores range from 1 to 9: 1 means too low (toe-box height), too narrow (toe-box width), too tight (ball girth, waist/instep, heel), or too short (length); 9 means too high, too wide, too loose, or too long; and 5 means just right (Figure 3a). A dynamic scale was used to evaluate the fit of the basketball shoes during the

maneuvers, including overall liking, heel cushioning, heel responsiveness, heel stability, heel-to-toe transition, and forefoot cushioning, which were also scored 1–9 points (1 for extremely dislike, 5 for neutral, and 9 for extremely like). In addition to overall liking, the intensity aspects were also rated 1–9: 1 means soft (heel and forefoot cushioning), no response (heel responsiveness), very unstable (heel stability), no smoothness (heel-toe transition), and so on; and 9 means hard, very reactive, very stable, very smooth, and so on (Figure 3b). The experiment process included a 10-minute regular-intensity basketball maneuver practice (including SS, 90◦ LR, and lay-up). The tongue and logos of the basketball shoes were completely covered before testing to avoid the brand effect and the influence of other factors on the scoring results.


#### (**a**)


#### (**b**)

**Figure 3.** (**a**) General fit scale includes the toe-box height, the toe-box width, the ball girth, the waist/instep, the elasticity at the heel, and the shoe length. The index scores range from 1 to 9 points; (**b**) dynamic scale includes overall liking, heel cushioning, heel responsiveness, heel stability, heel-to-toe transition, and forefoot cushioning, which were scored 1–9 points.

#### *2.4. Data Processing and Analysis*

The main variables of the GRF included the following: (1) peak vertical GRF (Fz) and appearance time (tF) and (2) peak loading rate (Gz) and appearance time (tG). Fz and Gz were normalized by bodyweight (BW).

According to Bontrager's study on the settings of the insole area and the structure of the pressure insoles [20], the peak pressure (normalized by BW) and the peak pressure distribution (contact area) were measured for six plantar areas, namely, the entire sole, the forefoot, the midfoot, the rearfoot, the medial, and the lateral (Figure 2).

The shoe comfort characteristics included (1) general fit: toe-box height, toe-box width, ball girth, waist/instep, heel, and length; and (2) dynamic fit: overall liking, heel cushioning, heel responsiveness, heel stability, heel-to-toe transition, and forefoot cushioning. Liking and intensity were involved in each dynamic fit variable.

#### *2.5. Statistics*

All data were normally distributed based on the Shapiro–Wilk test. The paired sample t-test was used to determine the effects of different basketball shoe cushioning on the GRF and the plantar pressure characteristics. The comfort perception variables were determined by the Wilcoxon rank-sum test (SPSS 19.0, SPSS Inc., Chicago, IL, USA). The significance level was set at 0.05.

#### **3. Results**

#### *3.1. Vertical GRF*

The passive impact phase in SS and 90◦ LR occurred within 100 ms after ground contact, with the Fz approximately twice that of the BW (Figure 4a). The vertical GRF increased rapidly in LUTO and LUTD during contact, that is, the Fz during the push-off phase and after landing could be as large as four and eight-times the BW, respectively (Figure 4b). However, no significant differences in Fz, Gz, tF, and tG were observed between the two basketball shoes during SS, 90◦ LR, LUTO, and LUTD (Table 1).

**Figure 4.** (**a**) Vertical ground reaction force-time curves during side-step cutting (SS) and 90◦ L-direction running (90◦ LR) maneuvers; (**b**) vertical ground reaction force-time curves during lay-up toe-off (LUTO) and lay-up touch-down (LUTD) maneuvers. Notes: GRF is ground reaction force, Fz is peak vertical GRF, and BW is bodyweight.

**Table 1.** Effect of different basketball shoes on ground reaction force during side-step cutting, 90◦ L-direction running, and lay-up toe-off and lay-up touch-down maneuvers.


Notes: GRF is ground reaction force, Fz is peak vertical GRF, Gz is peak loading rate, tF is time to peak vertical GRF, tG is time to peak loading rate, BW is bodyweight, SS is side-step cutting, 90◦ LR is 90◦ L-direction running, LUTO is lay-up toe-off, and LUTD is lay-up touch-down.

#### *3.2. Maximum Plantar Pressure*

Shoe L showed a lower maximum pressure in the entire sole (p < 0.05) and midfoot (p < 0.01) regions during SS (Table 2) compared with shoe N. Although shoe L showed a low plantar pressure in the entire sole and in the forefoot, the heel, the medial, and in the lateral regions, no significant differences were observed between the two shoes during 90◦ LR.

**Table 2.** Effect of different basketball shoes on maximum pressure of each plantar region during side-step cutting, 90◦ L-direction running, and lay-up toe-off and lay-up touch-down maneuvers.


Notes: SS is side-step cutting, 90◦ LR is 90◦ L-direction running, LUTO is lay-up toe-off, and LUTD is lay-up touch-down. \* p < 0.05; \*\* p < 0.01.

Notably, shoe L showed a lower maximum pressure in the midfoot and in the lateral regions during LUTO (p < 0.01) and LUTD (p < 0.01) compared with shoe N. Although no statistical differences were observed in plantar pressure on the rest of the regions, the maximum pressure was evidently lower in shoe L than in shoe N.

#### *3.3. Foot Pressure Distribution*

In general, the overall pressure distribution in the two shoes was similar but wider in shoe L than in shoe N, and the pressure value of each region was lower in shoe L than in shoe N. Specifically, less fore-lateral pressure distribution was noted in shoe L during SS; a wide heel pressure distribution was observed in shoe L during 90◦ LR, with pressure concentrated at the first metatarsal head, the first phalanges, and the fifth metatarsal head (Figure 5a); the foot pressure of each region in shoe L was smaller than that in shoe N during LUTO; and a smaller pressure at the first phalanges and a wider heel pressure distribution were noted in shoe N compared with shoe L during LUTD (Figure 5b).

**Figure 5.** (**a**) Effect of different basketball shoes (L vs. N) on plantar pressure distribution during side-step cutting (SS) and 90◦ L-direction running (90◦ LR) maneuvers; (**b**) effect of different basketball shoes (L vs. N) on plantar pressure distribution during lay-up toe-off (LUTO), and lay-up touch-down (LUTD) maneuvers. Different colors represented different pressure values. The pressure values from small to large were blue, green, yellow and red.

#### *3.4. Comfort Perception*

No significant differences were observed in the general fit between shoe L and shoe N (Figure 6). From the dynamic comfort scale perspective, the overall liking of shoe N was significantly higher than that of shoe L (p < 0.01) owing to forefoot and heel cushioning (p < 0.01). The heel responsiveness and stability of shoe N were greater than those of shoe L (p < 0.05), but no significant differences were observed in the heel-to-toe transition between the two shoes (Figure 7). The forefoot and heel cushioning of shoe L were significantly higher than those of shoe N (p < 0.05) (Figure 7) in terms of dynamic intensity. Meanwhile, no significant difference was observed in the heel-to-toe transition, heel response, and heel stability between the two types of shoes.

**Figure 6.** Effect of different basketball shoes (N vs. L) on general fit.

**Figure 7.** (**a**) Effect of different basketball shoes (N vs. L) on preference of dynamic scale; (**b**) effect of different basketball shoes (N vs. L) on intensity in dynamic scale.

#### **4. Discussion**

This study aimed to investigate the effect of two different shoe cushionings on foot loading (GRF and plantar pressure) and the perception of comfort during three basketball-specific maneuvers (i.e., SS, 90◦ LR, and LUTO/LUTD). Consistent with our hypothesis, compared to shoe N, shoe L showed a lower maximum pressure in the entire and midfoot regions during SS and a lower maximum pressure in the midfoot and lateral regions during LUTO and LUTD. The overall pressure distribution was wider in shoe L than in shoe N. In terms of the perception of comfort, shoe N was significantly superior to shoe L, especially in the dynamic scale. However, contrary to our hypothesis, no significant differences in Fz, Gz, tF, and tG were noted between the two basketball shoes during SS, 90◦ LR, LUTO, and LUTD.

#### *4.1. Vertical GRF*

In general, two peaks appeared in the vertical GRF on the lower limbs when running or jumping, namely, the impact force (first peak) and the active force (second peak). The impact force is closely related to sports injuries [2,23]. This study analyzed the characteristics of GRF during three kinds of basketball-specific maneuvers, namely, side-step cutting (SS), 90◦ varied-direction running (90◦ LR), and lay-up toe-off (LUTO) and lay-up touch-down (LUTD). Notably, the impact forces, which were approximately twice the BW, were identified as passive forces that appeared within 100 ms at the initial contact during SS and 90◦ LR, and the active forces were regarded as the principal components. However, the results indicated that no significant differences in GRF existed between the two pairs of shoes during SS and 90◦ LR.

Among the numerous basketball maneuvers, the lay-up is one of the most representative and relatively complex movements that include the acceleration, take-off, and landing phases. The results of the present study showed that the GRF curves during LUTO and LUTD were very similar to the those when running with a heel strike pattern [24,25]. Although the force would not cause impact damage to the lower extremity at take-off, which was nearly four times the BW, the participants were subjected to up to eight times of the BW impact force during landing because of the high jumps performed in this study. The repeated impacts loaded on the lower limbs can easily lead to injuries, especially when high impacts cannot be loaded [26]. Therefore, the results indicated that the high impacts during LUTD caused overuse injuries. However, we found no significant differences in Fz, Gz, tF, and tG regardless of shoe conditions. This finding suggests that though the two midsole materials were different, the impacts of the active movements on the lower extremities made a small difference.

#### *4.2. Plantar Pressure Characteristics*

We found that shoe L exhibited a significantly lower maximum pressure on the entire sole and on the midfoot regions compared with shoe N. Although shoe L showed a lower plantar pressure on the entire sole and on the forefoot, the heel, the medial, and the lateral regions, no significant differences were noted between the two shoes during 90◦ LR. In addition, shoe L showed a lower maximum pressure on the midfoot and lateral regions during LUTO and LUTD compared with shoe N. Although no statistical differences were observed in the rest of the plantar pressure regions, the maximum pressure was lower in shoe L than in shoe N.

The overall plantar pressure distribution in the two shoes was similar but wider in shoe L than in shoe N, and the pressure value of each region was lower in shoe L than in shoe N. Specifically, the fore-lateral pressure distribution of shoe L during SS was low; the heel pressure distribution of shoe L during 90◦ LR was wide, with the pressure was concentrated at the first metatarsal head, the first phalanges, and the fifth metatarsal head; the foot pressure of each region of shoe L was smaller than that of shoe N during LUTO; the pressure was smaller at the first phalanges; and the heel pressure distribution was wider for shoe N than those for shoe L during LUTD. At present, plantar pressure distribution has been measured for efficiency in studies on the characteristics and biomechanical mechanism of plantar pressure in various sports. These studies have provided key technologies for sports shoes of different events, especially in terms of individualized design and manufacturing. The material of the sole and its structure for energy absorption and release are important factors in attenuating impacts and protecting the lower extremity from injury [27].

A significant difference was noted in the present study on the plantar pressure of the two shoes during the different maneuvers. However, no significant differences were observed in the GRF or loading rates, which suggests that the mechanical relationship between the foot and the ground became an indirect one owing to the intervention of shoe conditions. This change was mainly due to the special medium of the midsole. A special patented cushioning material was used in the midsole of shoe L. The materials and structures of the midsoles differed in the two shoes, thereby resulting in significant differences in plantar pressure during the three maneuvers despite the similar GRF. This finding suggests that the mechanical performance of shoes and feet and the relationship between feet and shoes caused by different midsole materials should be considered when exploring the function of sports shoes [28]. These factors should then be combined with plantar pressure to create a comprehensive design and to improve sports shoes effectively.

#### *4.3. Comfort Perception*

In addition to meeting the functional requirements of specific sporting events and strengthening foot protection, the most important element in specialized sport's shoes is comfort [12,29]. At present, subjective scoring is still the most frequently applied method for internationally applicable comfort testing; however, the scales and questionnaires used in each study differ. The perception test which was used in this experiment mainly includes two parts, namely, the general fit and the dynamic scale, which have been proven reliable.

For the general fit, the two shoes provided comfort with no significant differences. However, shoe N outperformed shoe L significantly on each index for liking in the dynamic scale, especially in heel stability, heel response, heel cushioning, forefoot cushioning, and overall impression. Moreover, shoe N had above five scores in all the indices. The other feedback from the participants regarding shoe L included poor appearance, dehumanized overall design, thick sponge behind the shoes, and lack of details. In terms of dynamic comfort intensity, shoe L was insufficiently stable at the heel, while shoe N was not only stable but also responsive. Although the cushioning of shoe N was softer at the forefoot, the forefoot and heel cushioning of shoe L were better than those of shoe N, based on the participants' feedback. This finding is probably due to the fact that shoe N was too soft to provide sufficient cushioning. The general fit in the perceptual test was preferred for assessing the appropriateness of the shoes, while the dynamic scale was preferred for evaluating the perceptual likings and performance of the two shoes from a functional aspect. The deficiency of shoe L was mainly due to its lack of ergonomic design for fit or may be related to the materials and structural design.

Notably, the results of plantar pressure were inconsistent with the perceptual comfort of shoe L and shoe N in the above-mentioned plantar pressure and perceptual comfort scale tests [30]. Although shoe L has a lower plantar pressure on the forefoot, it is not as comfortable as shoe N. The results of plantar pressure indicated the advantage of the forefoot cushioning performance of shoe L. However, the midsole structure of shoe L should be improved to avoid excessive force concentration under intense impact from the pressure distribution. Che et al. [31] found that the plantar pressure index affects comfort assessment. Similarly, the midsole material and structure could affect individual comfort assessment [32]. Therefore, we assumed that the plantar pressure distribution was related to perceptual comfort to some extent because the human being, as an active organism, self-evaluates the perceptual information of sneakers [33]. Differences were observed in the midsole cushioning performance obtained by the mechanical/biomechanical test or the perception of comfort, which could directly affect people's choice of sports shoes. Ignoring these differences would inevitably affect the evaluation of sports shoes in terms of function. However, relevant studies on the reasons for these differences are limited. Therefore, further studies are required.

#### *4.4. Limitations*

In the present study, it is noteworthy that marker trajectories and surface electromyographic data were not collected to simplify the design by focusing on the foot loading and mimicking basketball maneuvers by limiting the experimental devices that were attached to the participants. However, future studies including electromyography results with different sports shoes in basketball players should be carried out in order to determine muscle activity [19,20,34]. Besides, it is considered that different trajectories performed by players could influence the trial times, as well as the impact on shoes [35].

#### **5. Conclusions**

No differences were observed in the impact forces and the average maximum plantar pressure between the two shoes during the three basketball-specific maneuvers. However, compared to shoe N, the plantar pressure range of shoe L was wider and showed a lower pressure at the midfoot and the lateral foot. Moreover, the comfort perception results indicated that though the general fit of the two shoes was equal, shoe L provided less overall comfort, forefoot flexibility, heel cushioning, heel stability, and heel response. Interestingly, the plantar pressure results were inconsistent with the perceptual comfort of the two shoes, which suggests that the biomechanical characteristics of the shoes themselves and the perception evaluation of the athletes should be considered in comprehensive shoe cushioning design and evaluation.

**Author Contributions:** X.Z., Z.L. and X.W. contributed equally. Conceptualization, W.F.; methodology, X.Z., Z.L. and X.W.; formal analysis, X.Z., Z.L., Y.Y., J.N. and X.W.; investigation, X.Z., Z.L., X.W., Y.Y., J.N. and W.F.; resources, W.F.; data curation, X.Z.; writing—original draft preparation, X.Z., Z.L., X.W. and J.N.; writing—review and editing, W.F.; project administration, W.F.; funding acquisition, W.F.

**Funding:** This work was supported by the National Natural Science Foundation of China (11772201, 11572202), the Talent Development Fund of Shanghai Municipal, China (2018107), the National Key Technology Research and Development Program of the Ministry of Science and Technology of China and the "Dawn" Program of Shanghai Education Commission, China.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

#### *Article*
