Reliability of Overground Running Measures from 2D Video Analyses in a Field Environment

Agreement between 2D Visual- and 3D Motion Capture-based Assessment of Foot Strike Pattern

Background

Foot strike patterns during running are typically categorized into two types: non-rearfoot strike (NRFS) and rearfoot strike (RFS), or as three distinct types: forefoot strike (FFS), midfoot strike (MFS), and RFS, based on which part of the foot lands first. Various methods, including two-dimensional (2D) visual-based methods and three-dimensional (3D) motion capture-based methods utilizing parameters such as the strike index (SI) or strike angle (SA), have been employed to assess these patterns. However, the consistency between the results obtained from each method remains debatable.

Hypothesis/Purpose

The purpose of this study was to examine the agreement for assessing foot strike patterns into two (NRFS and RFS) or three types (FFS, MFS, and RFS) between 2D visual- and 3D motion capture-based methods. The authors hypothesized that using two description types (NRFS and RFS) would have high inter-method reliability; however, using three description types (FFS, MFS and RFS) would have lower inter-method reliability because of the difficulty in distinguishing between FFS and MFS.

Study design

Controlled Laboratory Study.

Methods

Overall, 162 foot strikes from four healthy runners with various foot strike patterns were analyzed. Running kinematics and kinetics were recorded using a 3D motion capture system with a force platform. Each foot strike was filmed at 240 fps from the sagittal perspective. The visual, SI, and SA methods were used, and the kappa values for each method were calculated.

Results

An assessment of the two types of foot strike: NRFS and RFS, revealed almost perfect kappa values (κ = 0.89-0.95) among the visual, SI, and SA methods. In contrast, an assessment of the three types: FFS, MFS, and RFS, revealed relatively low kappa values (κ = 0.58-0.71). Kappa values within the NRFS category, which includes MFS and FFS, ranged from fair to slight (κ = 0.08-0.33).

Conclusion

Previous laboratory findings that categorized foot strike patterns into two distinct types may be applied in observational studies, clinical practice, and training situations.

Level of evidence

Level 2.

Foot and Ankle Muscle Isometric Strength in Nonrearfoot Compared With Rearfoot Endurance Runners

Background

Transitioning to a forefoot strike pattern can be used to manage running-related knee injuries. However, adopting a nonrearfoot strike induces a higher load on foot and ankle structures than rearfoot strike. Sufficient foot muscle strength is also necessary to prevent excessive longitudinal arch (LA) deformation when running with nonrearfoot strike. The aim of this study was to investigate the potential differences in foot-ankle muscle strength between RF and NRF runners.

Methods

A cross-sectional study including 40 RF and 40 NRF runners was conducted. The foot posture and the maximal voluntary isometric strength (MVIS) of 6 foot-ankle muscles were measured. The footstrike pattern was determined using a 2-D camera during a self-paced run on a treadmill.

Results

NRF had higher MVIS for ankle plantar flexor (+12.5%, P = .015), ankle dorsiflexor (+17.7%, P = .01), hallux flexor (+11%, P = .04), and lesser toe flexor (+20.8%, P = .0031). We found a small positive correlation between MVIS of ankle plantar flexor with MVIS of hallux flexor (r = 0.26; P = .01) and lesser toe flexor (r = 0.28; P = .01).

Conclusion

In this cross-sectional study, we found that NRF runners on average have a higher MVIS of hallux and lesser toe flexor compared with RF runners. NRF runners also have a higher MVIS of ankle plantar flexor and dorsiflexor than RF runners. We found only a small correlation between ankle plantar flexor and foot muscle strength.

Level of Evidence

Level III, case-control study.

Validity and reliability of two-dimensional video-based assessment to measure joint angles during running: A systematic review and meta-analysis

Two-dimensional video analysis systems (2DVAS) are commonly used by clinicians and researchers to determine angles during running. The aim of this systematic review (PROSPERO: CRD42022322798) was to synthesize the literature on the criterion validity and reliability of 2DVAS for measuring angles during running compared to three-dimensional motion analysis systems (3DMAS). We searched for articles on MEDLINE/Pubmed, EMBASE, SciELO, and LILACS up to October/2022. We included studies that evaluated the validity of 2DVAS (when compared to 3DMAS) and/or the reliability of 2DVAS measurements of lower limb and trunk angles during running. Qualitative and quantitative analyses were performed. Seven hundred and five studies were found and 17 were included. Ten studies analysed criterion validity between 2DVAS and 3DMAS and the results ranged from poor to excellent, with most of the parameters assessed presenting poor or moderate validity. Inter-rater reliability of 2DVAS was assessed in nine studies and most of the parameters investigated had good to excellent reliability. Intra-rater reliability (between-day processing) of angular running parameters - investigated in ten studies - was considered excellent for most of the parameters analysed. Inter-session reliability was assessed in three studies and was defined as good or excellent for most of the variables assessed. 2DVAS is a reliable method for measuring joint angles during running. However, the validity of 2DVAS compared to 3DMAS ranges from low to moderate for most running parameters. Therefore, based on the available evidence, caution should be taken when applying 2DVAS, particularly for frontal and transverse plane angles.

Common High-Speed Running Thresholds Likely Do Not Correspond to High-Speed Running in Field Sports

ABSTRACT

Freeman, BW, Talpey, SW, James, LP, Opar, DA, and Young, WB. Common high-speed running thresholds likely do not correspond to high-speed running in field sports. J Strength Cond Res 37(7): 1411-1418, 2023-The purpose of this study was to clarify what percentage of maximum speed is associated with various running gaits. Fifteen amateur field sport athletes (age = 23 ± 3.6 years) participated in a series of 55-meter running trials. The speed of each trial was determined by instructions relating to 5 previously identified gait patterns (jog, run, stride, near maximum sprint, and sprint). Each trial was filmed in slow motion (240 fps), whereas running speed was obtained using Global Positioning Systems. Contact time, stride angle, and midstance free-leg knee angle were determined from video footage. Running gaits corresponded with the following running speeds, jogging = 4.51 m·s -1 , 56%Vmax, running = 5.41 m·s -1 , 66%Vmax , striding = 6.37 m·s -1 , 78%Vmax, near maximum sprinting = 7.08 m·s -1 , 87%Vmax, and sprinting = 8.15 m·s -1 , 100%Vmax. Significant ( p < 0.05) increases in stride angle were observed as running speed increased. Significant ( p < 0.05) decreases were observed in contact time and midstance free-leg knee angle as running speed increased. These findings suggest currently used thresholds for high-speed running (HSR) and sprinting most likely correspond with jogging and striding, which likely underestimates the true HSR demands. Therefore, a higher relative speed could be used to describe HSR and sprinting more accurately in field sports.

Study of the kinetics of the determinants of performance during a mountain ultra marathon: Multidisciplinary protocol of the first Trail Scientifique de Clécy 2021 (Preprint)

Background

The growing interest of the scientific community in trail running has highlighted the acute effects of practice at the time of these races on isolated aspects of physiological and structural systems; biological, physiological, cognitive, and muscular functions; and the psychological state of athletes. However, no integrative study has been conducted under these conditions with so many participants and monitoring of pre-, per-, and postrace variables for up to 10 days over a distance close to 100 miles.

Objective

The aim of this study was to evaluate the kinetics of the performance parameters during a 156 km trail run and 6000 m of elevation gain in pre-, per-, and postrace conditions. The general hypothesis is based on significant alterations in the psychological, physiological, mechanical, biological, and cognitive parameters.

Methods

The Trail Scientifique de Clécy took place on November 11, 2021. This prospective experimental study provides a comprehensive exploration of the constraints and adaptations of psychophysiological and sociological variables assessed in real race conditions during a trail running of 156 km on hilly ground and 6000 m of elevation gain (D+). The study protocol allowed for repeatability of study measurements under the same experimental conditions during the race, with the race being divided into 6 identical loops of 26 km and 1000 m D+. Measurements were conducted the day before and the morning of the race, at the end of each lap, after a pit stop, and up to 10 days after the race. A total of 55 participants were included, 43 (78%) men and 12 (22%) women, who were experienced in ultra–trail-running events and with no contraindications to the practice of this sport.

Results

The launch of the study was authorized on October 26, 2021, under the trial number 21-0166 after a favorable opinion from the Comité de Protection des Personnes Ouest III (21.09.61/SIRIPH 2G 21.01586.000009). Of the 55 runners enrolled, 41 (75%) completed the race and 14 (25%) dropped out for various reasons, including gastric problems, hypothermia, fatigue, and musculoskeletal injuries. All the measurements for each team were completed in full. The race times (ie, excluding the measurements) ranged from 17.8206 hours for the first runner to 35.9225 hours for the last runner. The average time to complete all measurements for each lap was 64 (SD 3) minutes.

Conclusions

The Trail Scientifique de Clécy, by its protocol, allowed for a multidisciplinary approach to the discipline. This approach will allow for the explanation of the studied parameters in relation to each other and observation of the systems of dependence and independence. The initial results are expected in June 2022.

International Registered Report Identifier (IRRID)

RR1-10.2196/38027

Agreement Between Sagittal Foot and Tibia Angles During Running Derived From an Open-Source Markerless Motion Capture Platform and Manual Digitization

Several open-source platforms for markerless motion capture offer the ability to track 2-dimensional (2D) kinematics using simple digital video cameras. We sought to establish the performance of one of these platforms, DeepLabCut. Eighty-four runners who had sagittal plane videos recorded of their left lower leg were included in the study. Data from 50 participants were used to train a deep neural network for 2D pose estimation of the foot and tibia segments. The trained model was used to process novel videos from 34 participants for continuous 2D coordinate data. Overall network accuracy was assessed using the train/test errors. Foot and tibia angles were calculated for 7 strides using manual digitization and markerless methods. Agreement was assessed with mean absolute differences and intraclass correlation coefficients. Bland-Altman plots and paired t tests were used to assess systematic bias. The train/test errors for the trained network were 2.87/7.79 pixels, respectively (0.5/1.2 cm). Compared to manual digitization, the markerless method was found to systematically overestimate foot angles and underestimate tibial angles (P < .01, d = 0.06-0.26). However, excellent agreement was found between the segment calculation methods, with mean differences ≤1° and intraclass correlation coefficients ≥.90. Overall, these results demonstrate that open-source, markerless methods are a promising new tool for analyzing human motion.

Long-term effects of school barefoot running program on sprinting biomechanics in children: A case-control study

BACKGROUND

The acute changes of running biomechanics in habitually shod children when running barefoot have been demonstrated. However, the long-term effects of barefoot running on sprinting biomechanics in children is not well understood.

RESEARCH QUESTION

How does four years of participation in a daily school barefoot running program influence sprint biomechanics and stretch-shortening cycle jump ability in children?

METHODS

One hundred and one children from barefoot education school (age, 11.2 ± 0.7 years-old) and 93 children from a control school (age, 11.1 ± 0.7 years-old) performed 50 m maximal shod and barefoot sprints and counter movement jump and five repeated-rebound jumping. To analyse sprint kinematics, a high-speed camera (240 fps) was used. In addition, foot strike patterns were evaluated by using three high-speed cameras (300 fps). Jump heights for both jump types and the contact times for the rebound jump were measured using a contact mat system. Two-way mixed ANOVA was used to examine the effect of school factor (barefoot education school vs control school) and footwear factor (barefoot vs shod) on the sprinting biomechanics.

RESULTS

Sprinting biomechanics in barefoot education school children was characterised by significantly shorter contact times (p = 0.003) and longer flight times (p = 0.005) compared to control school children regardless of footwear condition. In shod sprinting, a greater proportion of barefoot education school children sprinted with a fore-foot or mid-foot strike compared to control school children (p < 0.001). Barefoot education school children also had a significantly higher rebound jump height (p = 0.002) and shorter contact time than control school children (p = 0.001).

SIGNIFICANCE

The results suggest that school-based barefoot running programs may improve aspects of sprint biomechanics and develop the fast stretch-shortening cycle ability in children. In order to confirm this viewpoint, adequately powered randomised controlled trials should be conducted.

Will the Foot Strike Pattern Change at Different Running Speeds with or without Wearing Shoes?

Runners strike their feet with three different patterns during running: forefoot, midfoot, and rearfoot. This study aimed to investigate whether runners maintain consistent patterns while running speed and foot condition change. The foot strike patterns of runners when running on a treadmill at paces ranging from slow to fast were recorded from twenty healthy male regular runners, with and without shoes, in random order. A high-speed camera was used to observe the strike patterns, which were then categorized by an experienced physical therapist. Linear-log and Pearson chi-square analysis with a significance level of α = 0.05 was performed to examine the correlation between foot strike pattern, running speed, and shoe conditions. The results suggest that runners strike with different patterns when running with and without shoes (χ² = 99.07, p < 0.01); runners preferred to adopt heel strike regardless of running speeds when running with shoes. While running barefoot, only 23.8% of landing strikes were rearfoot, and the strike pattern distribution did not change significantly with the running speed (χ² = 2.26, p = 0.89). In summary, the foot strike preference of runners is correlated with the foot condition (barefoot or shod) rather than running speed. For runners who intend to change their strike patterns for any reason, we recommend that they consider adjusting their footwear, which may naturally help with the foot strike adjustment. Future studies should attempt to use advanced techniques to observe further foot biomechanics in order to discover if changing strike pattern is directly correlated with lower limb injuries.

Validity of Using Automated Two-Dimensional Video Analysis to Measure Continuous Sagittal Plane Running Kinematics

Two-dimensional video analysis is commonly used to assess kinematics when three-dimensional motion capture is unavailable. However, videos are often assessed using manual digitization, which limits the ability to extract outcomes that require continuous data. Here, we introduced a method to collect continuous kinematic data in 2D using an inexpensive camera and an open-source automated marker tracking program. We tested the validity of this method by comparing 2D video analysis to 3D motion capture for measuring sagittal-plane running kinematics. Twenty uninjured participants ran on a treadmill for 1-min while lower extremity kinematics were collected simultaneously in 3D using a motion capture system and in 2D using a single digital camera, both at 120 Hz. Knee, ankle, and foot angle at contact, peak knee flexion, knee flexion excursion, and knee-ankle flexion vector coding variability were computed using both the 3D and 2D kinematic data, and were compared using intraclass correlation coefficients and Bland-Altman plots. The agreement between collection methods was excellent for foot angle at contact and knee flexion excursion, good for ankle and knee angle at contact and knee-ankle vector coding variability, and moderate for peak knee flexion. However, Bland-Altman plots revealed significant differences between the 2D and 3D collection methods, which varied across study participants. These low-cost methods could be useful for collecting continuous sagittal plane running kinematics in non-laboratory settings.

Recognition of Foot Strike Pattern in Asian Recreational Runners

Close to 90% of recreational runners rearfoot strike in a long-distance road race. This prevalence has been obtained from North American cohorts of runners. The prevalence of rearfoot strikers has not been extensively examined in an Asian population of recreational runners. Therefore, the aim of this study was to determine the prevalence of rearfoot, midfoot, and forefoot strikers during a long-distance road race in Asian recreational runners and compare this prevalence to reported values in the scientific literature. To do so, we classified the foot strike pattern of 950 recreational runners at the 10 km mark of the Singapore marathon (77% Asian field). We observed 71.1%, 16.6%, 1.7%, and 10.6% of rearfoot, midfoot, forefoot, and asymmetric strikers, respectively. Chi-squared tests revealed significant differences between our foot strike pattern distribution and those reported from North American cohorts (P < 0.001). Our foot strike pattern distribution was similar to one reported from elite half-marathon runners racing in Japan (Fisher exact test, P = 0.168). We conclude that the prevalence of rearfoot strikers is lower in Asian than North American recreational runners. Running research should consider and report ethnicity of participants given that ethnicity can potentially explain biomechanical differences in running patterns.