Foot strike pattern, step rate, and trunk posture combined gait modifications to reduce impact loading during running

Increasing cadence with a metronome and running barefoot changes the sagittal kinematics of the lower limbs and trunk

The purpose was to compare two non-laboratory based running retraining programs on lower limb and trunk kinematics in recreational runners. Seventy recreational runners (30 ± 7.3 years old, 40% female) were randomised to a barefoot running group (BAR), a group wearing a digital metronome with their basal cadence increased by 10% (CAD), and a control group (CON). BAR and CAD groups included intervals from 15 to 40 min over 10 weeks and 3 days/week. 3D sagittal kinematics of the ankle, knee, hip, pelvis, and trunk were measured before and after the retraining program, at comfortable and high speeds. A 3 × 2 mixed ANOVA revealed that BAR and CAD groups increased knee and hip flexion at footstrike, increased peak hip flexion during stance and flight phase, decreased peak hip extension during flight phase, and increased anterior pelvic tilt at both speeds after retraining. In addition, BAR increased ankle plantar flexion at footstrike and increased anterior trunk tilt. Both retraining programs demonstrated significant moderate to large effect size changes in parameters that could reduce the mechanical risks of injury associated with excessive knee stress, which is of interest to coaches, runners and those prescribing rehabilitation and injury prevention programs.

Rethinking running biomechanics: a critical review of ground reaction forces, tibial bone loading, and the role of wearable sensors

This study presents a comprehensive review of the correlation between tibial acceleration (TA), ground reaction forces (GRF), and tibial bone loading, emphasizing the critical role of wearable sensor technology in accurately measuring these biomechanical forces in the context of running. This systematic review and meta-analysis searched various electronic databases (PubMed, SPORTDiscus, Scopus, IEEE Xplore, and ScienceDirect) to identify relevant studies. It critically evaluates existing research on GRF and tibial acceleration (TA) as indicators of running-related injuries, revealing mixed findings. Intriguingly, recent empirical data indicate only a marginal link between GRF, TA, and tibial bone stress, thus challenging the conventional understanding in this field. The study also highlights the limitations of current biomechanical models and methodologies, proposing a paradigm shift towards more holistic and integrated approaches. The study underscores wearable sensors' potential, enhanced by machine learning, in transforming the monitoring, prevention, and rehabilitation of running-related injuries.

Biomechanical Analysis of Foot–Ankle Complex during Jogging with Rearfoot Strike versus Forefoot Strike

Background and Aim. In order to reduce foot and ankle injuries induced by jogging, two-foot strike patterns, rearfoot strike (RFS), and forefoot strike (FFS), were adopted and compared. First, RFS jogging and FFS jogging were experimentally studied, so as to acquire kinematic and kinetic data, including foot strike angle, knee flexion angle, and ground reaction force (GRF). Then, a 3D finite element model of foot–ankle complex was reconstructed from the scanned 2D-stacked images. Biomechanical characteristics, including plantar pressure, stress of metatarsals, midfoot bone, calcaneus and cartilage, and tensile force of plantar fascia and ligaments, were obtained. The results showed that RFS jogging and FFS jogging had a similar change trend and a close peak value of GRF. Since possessing more momentum in the push stage and less momentum in the brake stage, FFS jogging could be in favor of a higher jogging speed. However, FFS jogging produced larger metatarsal stress in the 5th metatarsal and much larger tensile force of plantar fascia, which might cause metatarsal fracture and heel pain. While RFS jogging produced larger plantar pressure in the hindfoot area, larger calcaneus stress, and much larger tarsal navicular stress, which might cause heel tissue injury, calcaneus damage, and stress fracture of naviculocuneiform joint. In addition, talocrural and talocalcaneal joint cartilage could bear jogging loads, as the peak contact pressure were both small in RFS jogging and FFS jogging. Therefore, jogging with rearfoot or FFS pattern should be chosen according to the health condition of foot–ankle parts.

What is the Effect of Changing Running Step Rate on Injury, Performance and Biomechanics? A Systematic Review and Meta-analysis

Background

Running-related injuries are prevalent among distance runners. Changing step rate is a commonly used running retraining strategy in the management and prevention of running-related injuries.

Objective

The aims of this review were to synthesise the evidence relating to the effects of changing running step rate on injury, performance and biomechanics.

Design

Systematic review and meta-analysis.

Data Sources

MEDLINE, EMBASE, CINAHL, and SPORTDiscus.

Results

Thirty-seven studies were included that related to injury (n = 2), performance (n = 5), and biomechanics (n = 36). Regarding injury, very limited evidence indicated that increasing running step rate is associated with improvements in pain (4 weeks: standard mean difference (SMD), 95% CI 2.68, 1.52 to 3.83; 12 weeks: 3.62, 2.24 to 4.99) and function (4 weeks: 2.31, 3.39 to 1.24); 12 weeks: 3.42, 4.75 to 2.09) in recreational runners with patellofemoral pain. Regarding performance, very limited evidence indicated that increasing step rate increases perceived exertion ( − 0.49,  − 0.91 to − 0.07) and awkwardness (− 0.72, − 1.38 to − 0.06) and effort (− 0.69, − 1.34, − 0.03); and very limited evidence that an increase in preferred step rate is associated with increased metabolic energy consumption (− 0.84, − 1.57 to − 0.11). Regarding biomechanics, increasing running step rate was associated with strong evidence of reduced peak knee flexion angle (0.66, 0.40 to 0.92); moderate evidence of reduced step length (0.93, 0.49 to 1.37), peak hip adduction (0.40, 0.11 to 0.69), and peak knee extensor moment (0.50, 0.18 to 0.81); moderate evidence of reduced foot strike angle (0.62, 034 to 0.90); limited evidence of reduced braking impulse (0.64, 0.29 to 1.00), peak hip flexion (0.42, 0.10 to 0.75), and peak patellofemoral joint stress (0.56, 0.07 to 1.05); and limited evidence of reduced negative hip (0.55, 0.20 to 0.91) and knee work (0.84, 0.48 to 1.20). Decreasing running step rate was associated with moderate evidence of increased step length (− 0.76, − 1.31 to − 0.21); limited evidence of increased contact time (− 0.95, − 1.49 to − 0.40), braking impulse (− 0.73, − 1.08 to − 0.37), and negative knee work (− 0.88, − 1.25 to − 0.52); and limited evidence of reduced negative ankle work (0.38, 0.03 to 0.73) and negative hip work (0.49, 0.07 to 0.91).

Conclusion

In general, increasing running step rate results in a reduction (or no change), and reducing step rate results in an increase (or no change), to kinetic, kinematic, and loading rate variables at the ankle, knee and hip. At present there is insufficient evidence to conclusively determine the effects of altering running step rate on injury and performance. As most studies included in this review investigated the immediate effects of changing running step rate, the longer-term effects remain largely unknown.

Prospero Registration

CRD42020167657.

Healthy Running Habits for the Distance Runner: Clinical Utility of the American College of Sports Medicine Infographic

ABSTRACT

Healthy running form is characterized by motion that minimizes mechanical musculoskeletal injury risks and improves coactivation of muscles that can buffer impact loading and reduce stresses related to chronic musculoskeletal pain. The American College of Sports Medicine Consumer Outreach Committee recently launched an infographic that describes several healthy habits for the general distance runner. This review provides the supporting evidence, expected acute motion changes with use, and practical considerations for clinical use in patient cases. Healthy habits include: taking short, quick, and soft steps; abdominal bracing; elevating cadence; linearizing arm swing; controlling forward trunk lean, and; avoiding running through fatigue. Introduction of these habits can be done sequentially one at a time to build on form, or more than one over time. Adoption can be supported by various feedback forms and cueing. These habits are most successful against injury when coupled with regular dynamic strengthening of the kinetic chain, adequate recovery with training, and appropriate shoe wear.

Adaptive locomotion: Foot strike pattern and limb mechanical stiffness while running over an obstacle

Previous studies of level running suggest runners adjust foot strike to control leg stiffness. This study aimed to determine how runners adjusted mechanical stiffness and foot strike prior to, during, and after a drop in surface height. Ten healthy subjects (5 male, 5 female; 24.32 ± 5.0 years) were video recorded as they ran on an outdoor path with a single drop in surface height (12.5 cm). Foot strike was recorded, while subject velocity, duty factor (DF), normalized maximum ground reaction force (GRF_bw), vertical hip displacement (Δy), leg compression (ΔL), vertical (K_vert) and leg stiffness (K_leg), touchdown (TD) and takeoff angle (TO), and flight (T_f) and contact time (T_c) were calculated. Compared to the step before the drop, T_f, GRF_bw, K_vert, K_leg, and TO increased, while T_c, DF, Δy, ΔL, and TD decreased in the step after the drop. Across trials, runners had either consistent or variable foot strike patterns. Runners using a consistent pattern most often shifted from rear to fore-foot strike in the steps before and after the drop, while those with a variable pattern showed less dramatic shifts. All parameters, except TD, were significantly different (p < 0.04) based on foot strike pattern, and comparisons between steps before and after the drop (except TD) were significantly different (p < 0.004). Runners with a variable foot strike pattern experienced smaller shifts within mechanical parameters when traveling over the drop, suggesting these runners may be able to stabilize limb mechanics on interrupted surfaces.

Augmented Cooper test: Biomechanical contributions to endurance performance

Running mechanics are modifiable with training and adopting an economical running technique can improve running economy and hence performance. While field measurement of running economy is cumbersome, running mechanics can be assessed accurately and conveniently using wearable inertial measurement units (IMUs). In this work, we extended this wearables-based approach to the Cooper test, by assessing the relative contribution of running biomechanics to the endurance performance. Furthermore, we explored different methods of estimating the distance covered in the Cooper test using a wearable global navigation satellite system (GNSS) receiver. Thirty-three runners (18 highly trained and 15 recreational) performed an incremental laboratory treadmill test to measure their maximum aerobic speed (MAS) and speed at the second ventilatory threshold (sVT2). They completed a 12-minute Cooper running test with foot-worm IMUs and a chest-worn GNSS-IMU on a running track 1–2 weeks later. Using the GNSS receiver, an accurate estimation of the 12-minute distance was obtained (accuracy of 16.5 m and precision of 1.1%). Using this distance, we showed a reliable estimation [R² > 0.9, RMSE ϵ (0.07, 0.25) km/h] of the MAS and sVT2. Biomechanical metrics were extracted using validated algorithm and their association with endurance performance was estimated. Additionally, the high-/low-performance runners were compared using pairwise statistical testing. All performance variables, MAS, sVT2, and average speed during Cooper test, were predicted with an acceptable error (R² ≥ 0.65, RMSE ≤ 1.80 kmh⁻¹) using only the biomechanical metrics. The most relevant metrics were used to develop a biomechanical profile representing the running technique and its temporal evolution with acute fatigue, identifying different profiles for runners with highest and lowest endurance performance. This profile could potentially be used in standardized functional capacity measurements to improve personalization of training and rehabilitation programs.

Biomechanical effects of the addition of a precision constraint on a collective load carriage task

Team lifting is a complex and collective motor task comprising motor and cognitive components. The purpose of this research is to investigate how individual and collective performances are impacted during load transport combined with a cognitive task. Ten dyads performed a first condition in which they transported a load (CC), and a second one in which they transported the load while maintaining a ball on its top (PC). The recovery-rate, amplitude and period of the centre-of-mass (COM) trajectory were computed for the system (dyad + table = PACS). We analysed the forces and moments exerted at each joint of the upper limbs of the participants. We observed a decrease in the overall performance of the dyads during PC: (i) the velocity and amplitude of CoM_PACS decreased by 1.7% and 5.8%, respectively, (ii) inter-participant variability of the Moment-Cost-Function and recovery rate decreased by 95%, and 19.2%, respectively during PC. Kinetic synergy analysis showed that the participants reorganized their coordination in the PC. We demonstrated that adding a precision task affects the economy of collective load carriage at the PACS level while the upper-limbs joint moments were better balanced across the paired participants for the PC.

Acute Effects of Gait Interventions on Tibial Loads During Running: A Systematic Review and Meta-analysis

Introduction

Changing running technique or equipment can alter tibial loads. The efficacy of interventions to modify tibial loads during running is yet to be synthesised and evaluated. This article reviewed the effect of running technique and footwear interventions on tibial loading during running.

Methods

Electronic databases were searched using terms relevant to tibial load and running. Interventions were categorised according to their approach (i.e., footwear; barefoot running; speed; surface; overground versus treadmill; orthotics, insoles and taping; and technique); if necessary, further subgrouping was applied to these categories. Standardised mean differences (SMDs) with 95% confidence intervals (CIs) for changes in tibial loading were calculated and meta-analyses performed where possible.

Results

Database searches yielded 1617 articles, with 36 meeting the inclusion criteria. Tibial loading increased with (1) barefoot running (SMD 1.16; 95% CI 0.50, 1.82); (2) minimalist shoe use by non-habitual users (SMD 0.89; 95% CI 0.40, 1.39); (3) motion control shoe use (SMD 0.46; 95% CI 0.07, 0.84); (4) increased stride length (SMD 0.86; 95% CI 0.18, 1.55); and (5) increased running speed (SMD 1.03; 95% CI 0.74, 1.32). Tibial loading decreased when (1) individuals ran on a treadmill versus overground (SMD − 0.83; 95% CI − 1.53, − 0.12); and (2) targeted biofeedback was used (SMD − 0.93; 95% CI − 1.46, − 0.41).

Conclusions

Running barefoot, in motion control shoes or in unfamiliar minimalist shoes, and with an increased stride length increases tibial loads and may increase the risk of a tibial stress injury during periods of high training load. Adopting interventions such as running on a treadmill versus overground, and using targeted biofeedback during periods of high loads could reduce tibial stress injury.

Injury Prevention, Safe Training Techniques, Rehabilitation, and Return to Sport in Trail Runners

This current concept, narrative review provides the latest integrated evidence of the musculoskeletal injuries involved with trail running and therapeutic strategies to prevent injury and promote safe participation. Running activities that comprise any form of off-road running (trail running, orienteering, short-long distance, different terrain, and climate) are relevant to this review. Literature searches were conducted to 1) identify types and mechanisms of acute and chronic/overuse musculoskeletal injuries in trail runners, 2) injury prevention techniques most relevant to running trails, 3) safe methods of participation and rehabilitation timelines in the sport. The majority of acute and chronic trail running-related musculoskeletal injuries in trail running occur in the lower leg, primarily in the knee and ankle. More than 70% are due to overuse, and ankle sprains are the most common acute injury. Key mechanisms underlying injury and injury progression include inadequate neuromotor control-balance-coordination, running through fatigue, and abnormal kinematics on variable terrain. Complete kinetic chain prehabilitation programs consisting of dynamic flexibility, neuromotor strength and balance, and plyometrics exercise can foster stable, controlled movement on trails. Patient education about early musculoskeletal pain symptoms and training adjustment can help prevent injury from progressing to serious overuse injuries. Real-time adjustments to cadence, step length, and knee flexion on the trail may also mitigate impact-related risk for injury. After injury occurs, rehabilitation will involve similar exercise components, but it will also incorporate rest and active rest based on the type of injury. Multicomponent prehabilitation can help prevent musculoskeletal injuries in trail runners through movement control and fatigue resistance.

Classification Model for Discriminating Trunk Fatigue During Running

PURPOSE

Fatigue is often associated with increased injury risk. Many studies have focused on fatigue in the lower extremity muscles brought on by running, yet few have examined the relationship between fatigue of the core musculature and associated changes in running gait. To investigate the relationship between trunk fatigue and running dynamics, this study had two goals: (1) to use machine learning to determine which gait parameters are most associated with trunk fatigue; and (2) to develop a machine learning algorithm that uses those parameters to classify individuals with trunk fatigue. We hypothesized that we could effectively differentiate between the non-fatigued and fatigued states using machine learning models derived from running gait parameters.

METHODS

Seventy-two individuals performed a trunk fatigue protocol. Lower extremity running biomechanics were collected pre- and post- the trunk fatigue protocol using an instrumented treadmill and 10-camera motion capture system.The fatiguing protocol involved executing a series of trunk fatiguing exercises until established fatigue criteria were reached. Gait variables extracted from the non-fatigued and fatigued states served as model inputs to aid in the development of the machine learning model that would distinguish between non-fatigued and fatigued running.

RESULTS

The machine learning protocol determined three variables - stance time, maximum propulsive GRF and maximum braking GRF - to be the best discriminators between non-fatigued and fatigued running. The SVM with Bagging was the best performing model that discriminated between non-fatigued and fatigued running with an accuracy of 82%, precision of 77%, recall of 90%, and area under the receiver operating curve of 0.91.

CONCLUSION

The machine learning model was effective in classifying between non-fatigued and fatigued running using three gait parameters extracted from GRF waveforms. The ability to classify fatigue using these easy to measure GRF derived parameters enhances the ability for the model to be integrated into wearable technology and the clinical setting to aid in the detection of fatigue and potentially injury, as fatigue is often a precursor to injury.Clinical Relevance- This model has the potential to be implemented in a clinical setting to determine the onset of trunk fatigue through basic gait analysis, involving only the ground reaction forces. This model would be aimed toward injury prevention since fatigue is linked to increased risk of injury.

The effect of two retraining programs, barefoot running vs increasing cadence, on kinematic parameters: A randomized controlled trial

The aim of this study was to compare the effects of two 10-week non-laboratory-based running retraining programs on foot kinematics and spatiotemporal parameters in recreational runners. One hundred and three recreational runners (30 ± 7.2 years old, 39% females) were randomly assigned to either: a barefoot retraining group (BAR) with 3 sessions/week over 10 weeks, a cadence retraining group (CAD) who increased cadence by 10% again with 3 sessions/week over 10 weeks and a control group (CON) who did not perform any retraining. The footstrike pattern, footstrike angle (FSA), and spatial-temporal variables at comfortable and high speeds were measured using 2D/3D photogrammetry and a floor-based photocell system. A 3 × 2 ANOVA was used to compare between the groups and 2 time points. The FSA significantly reduced at the comfortable speed by 5.81° for BAR (p < 0.001; Cohen's d = 0.749) and 4.81° for CAD (p = 0.002; Cohen's d = 0.638), and at high speed by 6.54° for BAR (p < 0.001; Cohen's d = 0.753) and by 4.71° for CAD (p = 0.001; Cohen's d = 0.623). The cadence significantly increased by 2% in the CAD group (p = 0.015; Cohen's d = 0.344) at comfortable speed and the BAR group showed a 1.7% increase at high speed. BAR and CAD retraining programs showed a moderate effect for reducing FSA and rearfoot prevalence, and a small effect for increasing cadence. Both offer low-cost and feasible tools for gait modification within recreational runners in clinical scenarios.

Uneven running: How does trunk-leaning affect the lower-limb joint mechanics and energetics?

This study aimed to investigate the role of trunk posture in running locomotion. Twelve recreational runners ran in the laboratory across even and uneven ground surface (expected 10 cm drop-step) with three trunk-lean angles from the vertical (self-selected, ∼15°; anterior, ∼25°; posterior, ∼0°) while 3D kinematic and kinetic data were collected using a 3D motion-capture-system and two embedded force-plates. Two-way repeated measures ANOVAs (α = 0.05) compared lower-limb joint mechanics (angles, moments, energy absorption and generation) and ground-reaction-force parameters (braking and propulsive impulse) between Step (level and drop) and Posture conditions. The Step-by-Posture interaction revealed decreased hip energy generation, and greater peak knee extension moment in the drop-step during running with posterior versus anterior trunk-lean. Furthermore, energy absorption across hip and ankle nearly doubled in the drop-step across all running conditions. The Step main effect revealed that the knee and ankle energy absorption, ankle energy generation, ground-reaction-force, and braking impulse significantly increased in the drop-step. The Posture main effect revealed that, compared with a self-selected trunk-lean, the knee's energy absorption/generation, ankle's energy generation and the braking impulse were either retained or attenuated when leaning the trunk anteriorly. The opposite effects occurred with a posterior trunk-lean. In conclusion, while the pronounced mechanical ankle stress in drop-steps is marginally affected by posture, changing the trunk-lean reorganizes the load distribution across the knee and hip joints. Leaning the trunk anteriorly in running shifts loading from the knee to the hip not only in level running but also when coping with ground-level changes.Highlights Changing the trunk-lean when running reorganizes the load distribution across the knee and hip joints.Leaning the trunk anteriorly from a habitual trunk posture during running attenuates the mechanical stress on the knee, while the opposite effect occurs with a posterior trunk-lean, irrespective to the ground surface uniformity.The effect of posture on pronounced mechanical ankle stress in small perturbation height during running is marginal.Leaning the trunk anteriorly shifts loading from the knee to the hip not only in level running but also when coping with small perturbation height.

Self-selected running gait modifications reduce acute impact loading, awkwardness, and effort

Impact loading has been associated with running-related injuries, and gait retraining has been suggested as a means of reducing impact loading and lowering the risk of injury. However, gait retraining can lead to increased perceived awkwardness and effort. The influence of specifically trained and self-selected running gait modifications on acute impact loading, perceived awkwardness and effort is currently unclear. Sixteen habitual rearfoot/midfoot runners performed forefoot strike pattern, increased step rate, anterior trunk lean and self-selected running gait modifications on an instrumented treadmill based on real-time biofeedback. Impact loading, perceived awkwardness and effort scores were compared among the four gait retraining conditions. Self-selected gait modification reduced vertical average loading rate (VALR) by 25.3%, vertical instantaneous loading rate (VILR) by 27.0%, vertical impact peak (VIP) by 16.8% as compared with baseline. Forefoot strike pattern reduced VALR, VILR and peak tibial acceleration. Increased step rate reduced VALR. Anterior trunk lean did not reduce any impact loading. Self-selected gait modification was perceived as less awkward and require less effort than the specifically trained gait modification (p < 0.05). These findings suggest that self-selected gait modification could be a more natural and less effortful strategy than specifically trained gait modification to reduce acute impact loading, while the clinical significance remains unknown.

Accurate Impact Loading Rate Estimation During Running via a Subject-Independent Convolutional Neural Network Model and Optimal IMU Placement

OBJECTIVE

Enable accurate estimation of vertical average loading rate (VALR) in runners with one or more wearable inertial measurement units (IMUs).

METHODS

A subject-independent convolutional neural network (CNN) model was developed to estimate VALR from wearable IMUs. Fifteen runners wore IMUs at the trunk, pelvis, thigh, shank, and foot and ran on an instrumented treadmill for combinations of the following conditions: foot-strike (forefoot, mid-foot, rear-foot), step rate (90% to 110% of baseline), running speed (2.4 m/s and 2.8 m/s) and footwear (standard and minimalist running shoes). Thirty-one IMU placement configurations with combinations of one to five IMUs were evaluated. VALR estimations from the wearable IMUs were compared with force-plate VALR measurements.

RESULTS

VALR estimations via the subject-independent CNN model with a single shank-worn IMU were highly correlated (ρ = 0.94) with force-plate VALR measurements and were substantially higher than previously reported peak tibial acceleration correlations with force-plate VALR measurements from shank-worn accelerometers (ρ = 0.44-0.66). Correlation results from the CNN model for a single IMU placed at the foot, pelvis, trunk, and thigh were ρ = 0.91, 0.76, 0.69, and 0.65, respectively. There was no improvement in accuracy from the shank-worn IMU when adding 1-4 additional IMUs from the trunk, pelvis, thigh, or foot.

CONCLUSION

The proposed subject-independent CNN model with a single shank-worn IMU provides more accurate estimation of VALR than previous wearable sensing approaches.

SIGNIFICANCE

This could enable runners to more accurately assess impact loading rates and potentially provide insights into running-related injury risk and prevention.

What are the Benefits and Risks Associated with Changing Foot Strike Pattern During Running? A Systematic Review and Meta-analysis of Injury, Running Economy, and Biomechanics

BACKGROUND

Running participation continues to increase. The ideal strike pattern during running is a controversial topic. Many coaches and therapists promote non-rearfoot strike (NRFS) running with a belief that it can treat and prevent injury, and improve running economy.

OBJECTIVE

The aims of this review were to synthesise the evidence comparing NRFS with rearfoot strike (RFS) running patterns in relation to injury and running economy (primary aim), and biomechanics (secondary aim).

DESIGN

Systematic review and meta-analysis. Consideration was given to within participant, between participant, retrospective, and prospective study designs.

DATA SOURCES

MEDLINE, EMBASE, CINAHL, and SPORTDiscus.

RESULTS

Fifty-three studies were included. Limited evidence indicated that NRFS running is retrospectively associated with lower reported rates of mild (standard mean difference (SMD), 95% CI 3.25, 2.37-4.12), moderate (3.65, 2.71-4.59) and severe (0.93, 0.32-1.55) repetitive stress injury. Studies prospectively comparing injury risk between strike patterns are lacking. Limited evidence indicated that running economy did not differ between habitual RFS and habitual NRFS runners at slow (10.8-11.0 km/h), moderate (12.6-13.5 km/h), and fast (14.0-15.0 km/h) speeds, and was reduced in the immediate term when an NRFS-running pattern was imposed on habitual RFS runners at slow (10.8 km/h; SMD = - 1.67, - 2.82 to - 0.52) and moderate (12.6 km/h; - 1.26, - 2.42 to - 0.10) speeds. Key biomechanical findings, consistently including both comparison between habitual strike patterns and following immediate transition from RFS to NRFS running, indicated that NRFS running was associated with lower average and peak vertical loading rate (limited-moderate evidence; SMDs = 0.72-2.15); lower knee flexion range of motion (moderate-strong evidence; SMDs = 0.76-0.88); reduced patellofemoral joint stress (limited evidence; SMDs = 0.63-0.68); and greater peak internal ankle plantar flexor moment (limited evidence; SMDs = 0.73-1.33).

CONCLUSION

The relationship between strike pattern and injury risk could not be determined, as current evidence is limited to retrospective findings. Considering the lack of evidence to support any improvements in running economy, combined with the associated shift in loading profile (i.e., greater ankle and plantarflexor loading) found in this review, changing strike pattern cannot be recommended for an uninjured RFS runner.

PROSPERO REGISTRATION

CRD42015024523.

Wearable Technology May Assist in Retraining Foot Strike Patterns in Previously Injured Military Service Members: A Prospective Case Series

A rearfoot strike (RFS) pattern with increased average vertical loading rates (AVLR) while running has been associated with injury. This study evaluated the ability of an instrumented sock, which provides real-time foot strike and cadence audio biofeedback, to transition previously injured military service members from a RFS to a non-rearfoot strike (NRFS) running pattern. Nineteen RFS runners (10 males, 9 females) were instructed to wear the instrumented socks to facilitate a change in foot strike while completing an independent walk-to-run progression and lower extremity exercise program. Kinetic data were collected during treadmill running while foot strike was determined using video analysis at initial (T1), post-intervention (T2), and follow-up (T3) data collections. Nearly all runners (18/19) transitioned to a NRFS pattern following intervention (8 ± 2.4 weeks after the initial visit). Most participants (16/18) maintained the transition at follow-up (5 ± 0.8 weeks after the post-intervention visit). AVLR of the involved and uninvolved limb decreased 29% from initial [54.7 ± 13.2 bodyweights per sec (BW/s) and 55.1 ± 12.7 BW/s] to post-intervention (38.7 ± 10.1 BW/s and 38.9 ± 10.0 BW/s), respectively. This effect persisted 5-weeks later at follow-up, representing an overall 30% reduction on the involved limb and 24% reduction on the uninvolved limb. Cadence increased from the initial to the post-intervention time-point (p = 0.045); however, this effect did not persist at follow-up (p = 0.08). With technology provided feedback from instrumented socks, approximately 90% of participants transitioned to a NRFS pattern, decreased AVLR, reduced stance time and maintained these running adaptations 5-weeks later.

The influence of sagittal trunk lean on uneven running mechanics

The role of trunk orientation during uneven running is not well understood. This study compared the running mechanics during the approach step to and the step down for a 10 cm expected drop, positioned halfway through a 15 m runway, with that of the level step in 12 participants at a speed of 3.5 m s-1 while maintaining self-selected (17.7±4.2 deg; mean±s.d.), posterior (1.8±7.4 deg) and anterior (26.6±5.6 deg) trunk leans from the vertical. Our findings reveal that the global (i.e. the spring-mass model dynamics and centre-of-mass height) and local (i.e. knee and ankle kinematics and kinetics) biomechanical adjustments during uneven running are specific to the step nature and trunk posture. Unlike the anterior-leaning posture, running with a posterior trunk lean is characterized by increases in leg angle, leg compression, knee flexion angle and moment, resulting in a stiffer knee and a more compliant spring-leg compared with the self-selected condition. In the approach step versus the level step, reductions in leg length and stiffness through the ankle stiffness yield lower leg force and centre-of-mass position. Contrariwise, significant increases in leg length, angle and force, and ankle moment, reflect in a higher centre-of-mass position during the step down. Plus, ankle stiffness significantly decreases, owing to a substantially increased leg compression. Overall, the step down appears to be dominated by centre-of-mass height changes, regardless of having a trunk lean. Observed adjustments during uneven running can be attributed to anticipation of changes to running posture and height. These findings highlight the role of trunk posture in human perturbed locomotion relevant for the design and development of exoskeleton or humanoid bipedal robots.

Effects of a 10-week running-retraining programme on the foot strike pattern of adolescents: A longitudinal intervention study

BACKGROUND

The purpose of this study was to analyse the effects of ten weeks of different running-retraining programmes on rearfoot strike (RFS) prevalence in adolescents.

RESEARCH QUESTION

it is possible to change foot strike pattern in adolescents?

METHODS

A total of 180 children (45.3% girls), aged 13-16 years, participated in this intervention study. The children were randomly assigned to one of three experimental groups (EGs) that each carried out a different retraining programme, based on running technique (n = 39), a 15% increased step frequency (SF) (n = 37) and barefoot training (n = 30), performed for three days each week. A control group (CG) (n = 43) did not perform any retraining. A 2D video-based analysis (240 Hz) was used to determine the RFS.

RESULTS

At baseline, no significant differences in RFS prevalence were found between the EGs and the CG in either the left (χ² = 2.048; p = 0.559) or the right foot (χ² = 0.898; p = 0.825). In the post-test, no significant differences were found for the left foot (χ² = 7.102; p = 0.069), but there were significant differences for the right foot (χ² = 9.239; p = 0.025) were observed. In the re-test, no significant differences were found for either the left foot (χ² = 2.665; p = 0.273) or the right foot (χ² = 2.182; p = 0.325). In addition, no group displayed significant changes in RFS prevalence from the pre-test to the re-test. There was a trend towards a reduction in the RFS prevalence in both the increased SF group and the barefoot group.

MEANING

The main finding of this study was that certain running-retraining programmes performed three times per week for ten weeks are not enough to modify the adolescent foot strike pattern (FSP).

Effects of spinal coupling and marker set on tracking of spine models during running

Despite the wide-spread use of musculoskeletal simulations and its use in estimating spinal loads, much is not known about how to best collect experimental data for modelling purposes. The primary purposes in this study were to determine the effects of tracking of running motion capture data to a model (1) with and without coupling of lumbar spine segments, and (2) with varying combinations of spinal markers. Running trials were collected from 7 participants, with each at three different speeds. The motion data was fit to the Full-Body Lumbar Spine Model (FBLS) with coupling of the lumbar spine enabled (CS) and disabled and therefore rigid (RS) in OpenSim through the Inverse Kinematics tool (IK). Different combinations of markers were chosen as tracking inputs for IK to represent experimental data collection with different marker sets. Root-mean-square (RMS) marker errors of all 13 markers along the spine for each gait cycle were calculated. The CS model resulted in 23.7% lower errors than the RS model (p < 0.001). The marker subset analysis showed that increasing the number of markers in the experimental data collection decreases the error, with the four marker tracking subsets with the highest number of markers tracked having the lowest errors. The location of the marker and timing in the gait cycle did not affect marker error. When spinal mechanics are of interest, the inclusion of a coupled lumbar spine in the model and a larger spinal marker set help better track experimental kinematics when fitting to a model.

"Controlled Slip" Energy Harvesting While Walking

Rapid development in wearable electronics and systems continues to impose challenges on portable energy storage sustained over time, and thus human energy harvesting is a potentially attractive means of sustainable, long-term energy. We introduce a novel 'controlled slip' energy harvesting approach for capturing energy during human locomotion. While slip is normally considered undesirable, controlled slip holds potential to enable a significant amount of energy harvesting during each step of human gait. Custom-designed 'controlled slip' energy harvesting shoes were fabricated by mounting a sliding plate and a generator with a one-way bearing to the sole of standard walking shoes, which induces controlled forward slip during early stance while energy is harvested. Fourteen healthy subjects performed treadmill walking trials with the 'controlled slip' energy harvesting shoes which generated average electrical power of 1.15-1.44 W at walking speeds of 2.9-4.3 km/h. Interestingly, without prompting, subjects chose to walk with the 'controlled slip' energy harvesting shoes in either one of two distinct ways: landing with the heel first (heel strikers) or landing with the toe first (toe strikers). While heel strikers and toe strikers exhibited similar electrical power output and hip flexion angle at initial foot contact, heel strikers had higher peak ankle power and lower knee flexion angle at initial foot contact than toe strikers. 'Controlled slip' energy harvesting could potentially generate electrical power for a broad spectrum of wearable devices.

Real-time feedback by wearables in running: Current approaches, challenges and suggestions for improvements

Injuries and lack of motivation are common reasons for discontinuation of running. Real-time feedback from wearables can reduce discontinuation by reducing injury risk and improving performance and motivation. There are however several limitations and challenges with current real-time feedback approaches. We discuss these limitations and challenges and provide a framework to optimise real-time feedback for reducing injury risk and improving performance and motivation. We first discuss the reasons why individuals run and propose that feedback targeted to these reasons can improve motivation and compliance. Secondly, we review the association of running technique and running workload with injuries and performance and we elaborate how real-time feedback on running technique and workload can be applied to reduce injury risk and improve performance and motivation. We also review different feedback modalities and motor learning feedback strategies and their application to real-time feedback. Briefly, the most effective feedback modality and frequency differ between variables and individuals, but a combination of modalities and mixture of real-time and delayed feedback is most effective. Moreover, feedback promoting perceived competence, autonomy and an external focus can improve motivation, learning and performance. Although the focus is on wearables, the challenges and practical applications are also relevant for laboratory-based gait retraining.

Acute changes in sagittal plane kinematics while wearing a novel belt device during treadmill running

Somatosensory feedback is used in walking retraining; however, its utility in running is less feasible due to the greater associated speeds. The purpose of this study was to examine the acute effects of wearing a novel running belt device on sagittal plane running kinematics. Ten healthy runners ran on a treadmill with and without the use of a running belt device within a repeated measures study design. Temporal-spatial characteristics and sagittal plane knee and ankle kinematics were recorded with three-dimensional motion analysis. Wilcoxon Signed-Rank Tests revealed significant decreases in centre of mass vertical displacement (z = -2.083, p = 0.003), tibial inclination at initial contact (z = -2.803, p = 0.003), and stance phase knee joint excursion (z = -2.701, p = 0.003), and greater knee flexion at initial contact (z = -2.803, p = 0.003) when the belt was donned. No differences were observed in step rate (z = -0.351, p = 0.363), foot inclination angle at initial contact (z = -2.090, p = 0.018), or peak knee flexion during stance (z = -1.172, p = 0.121). Findings suggest that donning a running belt can minimise specific high-risk biomechanical characteristics in runners with particular kinematic profiles.

Running biomechanics before and after Pose® method gait retraining in distance runners

Pose® Method gait retraining has been claimed to modify running form and prevent injury. This study examined the running biomechanics before and after Pose® Method gait retraining. Fourteen runners underwent a 4-week Pose® Method gait retraining program delivered by a certified coach. Paired t-tests were employed to compare vertical average (VALR) and instantaneous loading rates (VILR), lower limb kinematics, footstrike angle and trunk flexion in the sagittal plane before and after the training. Kinetically, there were no significant differences in the VALR (p= 0.693) and VILR (p= 0.782) before and after the training. Kinematically, participants exhibited greater peak hip flexion (p= 0.008) and knee flexion (p= 0.003) during swing. Footstrikeangle also reduced significantly (p= 0.008), indicating a footstrike pattern switch from rearfoot strike to midfoot strike. There was no significant difference in the trunk flexion in the sagittal plane after training (p= 0.658). After a course of Pose® Method gait retraining, runners demonstrated a footstrike pattern switch and some kinematics changes at the hip and knee joint during swing. However, injury-related biomechanical markers (e.g., VALR and VILR) and the trunk kinematics remained similar after training. Runners may consider other gait retraining programs for impact loading reduction.