Running Velocity and Longitudinal Bending Stiffness Influence the Asymmetry of Kinematic Variables of the Lower Limb Joints

ng-related limb asymmetries suggest speci c sports injuries and recovery circum- stances. It is debatable if running speed affected asymmetry, and more research is required to determine how longitudinal bending stiffness (LBS) affected asymmetry. The purpose of this study was to investigate the in uence of running velocity and LBS on kinematic characteristics of the hip, knee, ankle, metatarsophalangeal joint (MTP) and the corresponding asymmetry. Kinematic (200 Hz) running stance phase data were collected bilaterally for 16 healthy male recreational runners (age: 23.13 1.17, height: 175.2 1.6 cm, body mass: 75.7 3.6 kg, BMI: 24.7 1.3 kg/m 2 ) running ona forceplate at three different velocities (10, 12 and 14 km/h) and three increasing-LBS shoes in a randomizedorder. The symmetry angle (SA) was calculated to quantify gait asymmetry magnitude at each running velocity and LBS. Changes in running velocity and LBS led to differences in kinematic variables between the hip, knee, ankle and MTP (p< 0.05).

kg/m 2 ) running ona forceplate at three different velocities (10, 12 and 14 km/h) and three increasing-LBS shoes in a randomizedorder. The symmetry angle (SA) was calculated to quantify gait asymmetry magnitude at each running velocity and LBS. Changes in running velocity and LBS led to differences in kinematic variables between the hip, knee, ankle and MTP (p< 0.05). Signi cant changes in SA caused by running velocity were found in the knee exion angle (p= 0.001) and exion angle peak velocity (p< 0.001), ankle plantar exion angle (p= 0.001) and plantar exion angle peak velocity (p= 0.043) and MTP dorsi exion angle (p= 0.001) and dorsi exion angle peak velocity (p= 0.019). A signi cant change in the SA caused by LBS was found in the MTP dorsi exion peak angle velocity (p= 0.014). There were interaction effects between running velocity and LBS on the MTP plantar exion angle (p= 0.033) and plantar exion angle peak velocity (p= 0.038). These ndings indicate the existence of bilateral lower limb asymmetry. Meanwhile, it was proved that running velocity and LBS can in uence the asymmetry of lower limb joints. Additionally, there was an interaction between running velocity and LBS on the asymmetry of the lower limb. These ndings can provide some information for sports injuries, such as metatarsal stress fractures and anterior cruciate ligament injuries. They can also provide some useful information for running velocities and running shoes. Keywords:longitudinal bending stiffness; running velocity; kinematic; asymmetry; lower limb 1. Introduction Longitudinal bending stiffness (LBS) is a footwear property that is known as one key consideration for footwear performance development [1,2]. A suitable LBS is also thought to be a crucial element in comfort and athletic performance [2,3]. The fast development of footwear technology has increased awareness of LBS. The majority of studies have also found a link between LBS and sports injuries [1,4,5]. Increasing the forefoot bending stiffness of footwear may help with injury prevention in particular by preventing excessive forefoot extension during sports activities to reduce the incidence of injuries such as turf toe [4]. Studies suggest that the stiffness

footwear technology has increased awareness of LBS. The majority of studies have also found a link between LBS and sports injuries [1,4,5]. Increasing the forefoot bending stiffness of footwear may help with injury prevention in particular by preventing excessive forefoot extension during sports activities to reduce the incidence of injuries such as turf toe [4]. Studies suggest that the stiffness of the forefoot bending may have an effect on the prevalence of metatarsal stress fractures. Stiff shoes cause the center of pressure under the foot to shift more anteriorly and alter the peak pressures acting on various foot regions [1]. Performance in long-distance running is in uenced by running economy (RE) [6]. In Bioengineering2022,9, 607.

Bioengineering2022,9, 607 2 of 17 a study by Roy and Stefanyshyn et al. [7], approximately 1% metabolic energy savings were observed when participants ran in a stiff midsole. In addition, studies had shown that stiff carbon- ber plates may reduce the energetic cost of running by 4% [8]. These suggested that enhancing the midsole's LBS would enhance RE. The bulk of research overlooked the asymmetry between the bilateral lower limbs and instead used the unilateral dominant leg to represent the overall performance of the bilateral lower limbs [9] in order to simplify data collection and processing. The human body's symmetry, however, is not perfect. There are asymmetries between the dominant and non- dominant legs, according to studies [10]. Lower limb asymmetry was not only caused by genetics and hormones, but also by biomechanical variables [11,12]. The differences in the load-related dynamics of the bilateral limbs may lead to asymmetry [12]. The existence of lower limb asymmetry was demonstrated in an experiment that included jumping–landing exercises. The knee moment of the dominant leg was greater than that of the non-dominant limb [13]. Additionally, it has been shown that knee exion moment asymmetry predicts re-injury in athletes who had an anterior cruciate ligament reconstruction [14]. In earlier studies, the symmetry angle (SA), which re ects the symmetry of kinematic and kinetic variables of lower extremity joints, was frequently used [15]. In comparison to pre-fatigue, the SA of the knee exion angle, hip exion angle and hip extension angle was signi cantly higher in post-fatigue. In other words, after running, the joint asymmetry of the lower extremities becomes worse [16]. The biomechanical asymmetry of the lower limb can provide some information related to sports injuries. Idiopathic scoliosis may be caused by pelvic and hip angle asymmetry [17] . Kotwicki et al. [18], in a comparison of hip range of motion (ROM) asym- metry between scoliosis and normal adolescents, found that the scoliosis group showed greater asymmetry. For evaluating athletes' return to the eld following anterior cruciate ligament surgery and recuperation, the asymmetry of knee ROM provides important refer- ence data [19]. Although asymmetry

hip angle asymmetry [17] . Kotwicki et al. [18], in a comparison of hip range of motion (ROM) asym- metry between scoliosis and normal adolescents, found that the scoliosis group showed greater asymmetry. For evaluating athletes' return to the eld following anterior cruciate ligament surgery and recuperation, the asymmetry of knee ROM provides important refer- ence data [19]. Although asymmetry has often been often considered a manifestation of pathology, for some lower limb joint movements, the asymmetry in the range of variation of bilateral lower limbs in healthy people remains to be investigated [20]. Lower limb asymmetry has been shown to increase with walking velocity, suggest- ing that running may result in even more asymmetry. Biomechanical asymmetry is not detrimental during walking tasks; however, greater biomechanical demands are imposed on the musculoskeletal system during running [9]. Mo et al. discovered that among recre- ational runners, SA altered nonlinearly and displayed an approximately U-shaped trend across velocities [21]. Running velocity, in contrast, had no impact on the asymmetry of the kinematic characteristics of the joints in the lower limbs, according to Jiang et al. [11]. The negative work performed by the metatarsophalangeal joint (MTP) decreased with the increase in LBS and signi cantly changed the mechanical properties of the ankle and knee [22]. The MTP dorsi exion angle and dorsi exion angle velocity reduced with an increase in LBS to lessen the chance of forefoot injury [1,23]. Research on the kinematic variations of lower limb joints regarding LBS is very extensive. Research on the impact of LBS on lower limb asymmetry is lacking, however. Additionally, the impact of running speed on the kinematics of the lower limbs has always been debatable. As a result, the purpose of this study was to explore the difference and asymmetry in lower limb kinematic variables when wearing increasing-LBS shoes at different running velocities. We analyzed the in uence of running velocity and LBS on angles, angle peak velocities and the SA of the hip, knee, ankle and MTP. 2. Materials and Methods 2.1. Participants The sample size was calculated using G*Power 3.1 (Franz Faul, Germany)

explore the difference and asymmetry in lower limb kinematic variables when wearing increasing-LBS shoes at different running velocities. We analyzed the in uence of running velocity and LBS on angles, angle peak velocities and the SA of the hip, knee, ankle and MTP. 2. Materials and Methods 2.1. Participants The sample size was calculated using G*Power 3.1 (Franz Faul, Germany) for uni- variate analysis of variance for detecting a medium Cohen's effect size (d = 0.4), error probability = 0.05 and power (1 ) = 0.95. Based on these parameters, it was esti- mated that a minimum of 14 participants would be required for this study [24]. A total of

Bioengineering2022,9, 607 3 of 17 16 healthy males (age: 23.13 1.17, height: 175.2 1.6 cm, body mass: 75.7 3.6 kg, BMI: 24.7 1.3 kg/m 2 ) who were recreational runners (no formal running competition, training at least 3 times a week) were recruited [11,25]. The recruitment criteria for recreational runners in this experiment were running for at least 6 months and running a minimum distance of 10 km per week and having the right-side limb as the dominant limb [26]. The dominant limb was de ned as the preferred leg when kicking a ball. All participants were free from health problems and/or neuromuscular disorders and/or known gait impair- ments, and had had no lower limb injuries in the previous six months. All participants were rearfoot strikers and were recruited from Ningbo University for this study. Before the experiment, all participants gave written consent. The study was approved by the Ethics Committee of the Research Institute at Ningbo University. 2.2. The Experimental Process The general process of the experiment is shown in Figureb. Before the formal test, participants had 10 min to warm up and familiarize themselves with experimental settings. In the rst step of the formal test, each participant was asked to stand on a force platform to collect static coordinates by standing parallel to theY-axis of the force platform with arms crossed over shoulders and eyes looking forward until the full static coordinates were captured. All participants were allowed three trials to familiarize themselves with the test maneuvers before the formal test. During the test, participants were asked to wear Shoe 1 (S1), Shoe 2 (S2) and Shoe 3 (S3) at 10 5% km/h (V1), 12 5% km/h (V2) and 14 5% km/h (V3), respectively, over a 10 m track [5,11,15,27]. The shoe information is shown in Table. Additionally, participants were asked to complete a full gait cycle on a 2 m force platform (Kistler, Winterthur, Switzerland) located in the middle of the track. Five trials were achieved to gather eligible data on the dominant leg, in which the running speed of the participant had less than 5% variance

track [5,11,15,27]. The shoe information is shown in Table. Additionally, participants were asked to complete a full gait cycle on a 2 m force platform (Kistler, Winterthur, Switzerland) located in the middle of the track. Five trials were achieved to gather eligible data on the dominant leg, in which the running speed of the participant had less than 5% variance and was within 5% of the prede ned running speed. The full gait cycle was de ned as the time from the right heel strike to the left forefoot coming off the ground in this test. The LBS values of the shoes were measured by a rotational axis material-testing machine (Instron ElectroPuls E1000, Norwood, MA, USA). The force platform recorded the ground reaction force at 1000 Hz to distinguish a complete gait cycle. An eight-camera motion capture system (Vicon Metrics Ltd., Oxford, United Kingdom) was used to record running kinematic data during the stance phase at a frequency of 200 Hz. A threshold of 20 N on the vertical ground reaction force was applied to identify the initial foot contact and toe-off. To manage running velocity, Brower timing lights (Brower Timing System, Draper, UT, USA) were used. Before the experiment, participants were asked to apply 38 re ective markers (diameter: 14 mm) on their bodies. The speci c positions of the markers are shown in Figurea.Bioengineering 2022, 9, x FOR PEER REVIEW 4 of 18 Figure 1. (a) The front, side and back positions of markers. Blue dots: markers. (b) Illustration of experiment design for collecting the kinematics data during the running stance phase. 2.3. Data Analysis This study focused on the sagittal planes of the hip, knee, ankle and MTP. Dominant variation in the sagittal plane is reported to occur during running [28]. Marker trajectories were filtered by zero-latency fourth-order Butterworth low-pass filters at 12 Hz. The C3D file data were converted to formats recognized in OpenSim 4.3 (.mot and .trc) by Matlab R2016a (The MathWorks, Natick, MA, USA), and then imported into OpenSim for data processing [29]. A musculoskeletal model in OpenSim (gait 2392) was used. The model

occur during running [28]. Marker trajectories were filtered by zero-latency fourth-order Butterworth low-pass filters at 12 Hz. The C3D file data were converted to formats recognized in OpenSim 4.3 (.mot and .trc) by Matlab R2016a (The MathWorks, Natick, MA, USA), and then imported into OpenSim for data processing [29]. A musculoskeletal model in OpenSim (gait 2392) was used. The model was scaled using the participant’s marker point location and weight in a static calibration. The static weight of each marker was manually adjusted according to the root mean square (RMS) error value (less than 0.02) between the experimental and virtual markers in the model until it was adjusted to the appropriate position before applying the scaled model to the data calculation. The joint angles were calculated using the inverse kinemat- ics (IK) calculation tool in OpenSim, and the results were optimized using least squares to minimize the error between the experimental and virtual markers. SA was used to evaluate the biomechanical symmetry of the participants’ dominant limb and non-dominant limb. SA can be calculated as follows: í µí±†í µí°´ L k45 ° Farctankí µí±‹ ß Ø Ù çí µí±‹ å Ü Ú Û ç⁄ oo 90° H 100% If :45 ° Farctan :í µí±‹ ß Ø Ù çí µí±‹ å Ü Ú Û ç⁄ ; ; Then í µí±†í µí°´ L :45 ° Farctan :í µí±‹ ß Ø Ù çí µí±‹ å Ü Ú Û ç⁄ ; F 180 â—¦ ; 90° H 100% X left represents the kinematic variables of the left lower limb, and X right represents the kinematic variables of the right lower limb. A score of 0% suggests perfect symmetry and 100% suggests perfect asymmetry between the right and left leg [30]. 2.4. Statistical Analysis SPSS 26.0 (SPSS, Chicago, IL, USA) software was used for statistical analysis. Descriptive statistics were provided as means and standard deviations (SDs). Tests for normality and homogeneity of variances (Shapiro–Wilk and Levene’s, respectively) Figure 1. (a) The front, side and back positions of markers. Blue dots: markers. (b) Illustration of experiment design for collecting the kinematics data during the running stance

26.0 (SPSS, Chicago, IL, USA) software was used for statistical analysis. Descriptive statistics were provided as means and standard deviations (SDs). Tests for normality and homogeneity of variances (Shapiro–Wilk and Levene’s, respectively) Figure 1. (a) The front, side and back positions of markers. Blue dots: markers. (b) Illustration of experiment design for collecting the kinematics data during the running stance phase.

Bioengineering2022,9, 607 4 of 17 Table 1.The information of shoes. S1 S2 S3 LBS value (Nm/rad) 2.7 5.0 8.6 AppearanceBioengineering 2022, 9, x FOR PEER REVIEW 3 of 18 2. Materials and Methods 2.1. Participants The sample size was calculated using G*Power 3.1 (Franz Faul, Germany) for uni- variate analysis of variance for detecting a medium Cohen’s effect size (d = 0.4), α error probability = 0.05 and power (1 − β) = 0.95. Based on these parameters, it was estimated that a minimum of 14 participants would be required for this study [24]. A total of 16 healthy males (age: 23.13 ± 1.17, height: 175.2 ± 1.6 cm, body mass: 75.7 ± 3.6 kg, BMI: 24.7 ± 1.3 kg/m 2 ) who were recreational runners (no formal running competition, training at least 3 times a week) were recruited [11,25]. The recruitment criteria for recreational run- ners in this experiment were running for at least 6 months and running a minimum dis- tance of 10 km per week and having the right-side limb as the dominant limb [26]. The dominant limb was defined as the preferred leg when kicking a ball. All participants were free from health problems and/or neuromuscular disorders and/or known gait impair- ments, and had had no lower limb injuries in the previous six months. All participants were rearfoot strikers and were recruited from Ningbo University for this study. Before the experiment, all participants gave written consent. The study was approved by the Eth- ics Committee of the Research Institute at Ningbo University. 2.2. The Experimental Process The general process of the experiment is shown in Figure 1b. Before the formal test, participants had 10 min to warm up and familiarize themselves with experimental set- tings. In the first step of the formal test, each participant was asked to stand on a force platform to collect static coordinates by standing parallel to the Y-axis of the force plat- form with arms crossed over shoulders and eyes looking forward until the full static co- ordinates were captured. All participants were allowed three trials to familiarize them- selves with

the first step of the formal test, each participant was asked to stand on a force platform to collect static coordinates by standing parallel to the Y-axis of the force plat- form with arms crossed over shoulders and eyes looking forward until the full static co- ordinates were captured. All participants were allowed three trials to familiarize them- selves with the test maneuvers before the formal test. During the test, participants were asked to wear Shoe 1 (S1), Shoe 2 (S2) and Shoe 3 (S3) at 10 ± 5% km/h (V1), 12 ± 5% km/h (V2) and 14 ± 5% km/h (V3), respectively, over a 10 m track [5,11,15,27]. The shoe infor- mation is shown in Table 1. Additionally, participants were asked to complete a full gait cycle on a 2 m force platform (Kistler, Winterthur, Switzerland) located in the middle of the track. Five trials were achieved to gather eligible data on the dominant leg, in which the running speed of the participant had less than 5% variance and was within 5% of the predefined running speed. The full gait cycle was defined as the time from the right heel strike to the left forefoot coming off the ground in this test. The LBS values of the shoes were measured by a rotational axis material-testing machine (Instron ElectroPuls E1000, Norwood, MA, USA). The force platform recorded the ground reaction force at 1000 Hz to distinguish a complete gait cycle. An eight-camera motion capture system (Vicon Met- rics Ltd., Oxford, United Kingdom) was used to record running kinematic data during the stance phase at a frequency of 200 Hz. A threshold of 20 N on the vertical ground reaction force was applied to identify the initial foot contact and toe-off. To manage running ve- locity, Brower timing lights (Brower Timing System, Draper, UT, USA) were used. Before the experiment, participants were asked to apply 38 reflective markers (diameter: 14 mm) on their bodies. The specific positions of the markers are shown in Figure 1a. Table 1. The information of shoes. S1 S2 S3 LBS value (Nm/rad) 2.7 5.0 8.6 Appearance

This study investigates the influence of running velocity and LBS on lower limb kinematic characteristics.