Gait-training devices in the treatment of lower extremity injuries in sports medicine: current status and future prospects

Field-Based Gait Retraining to Reduce Impact Loading Using Tibial Accelerometers in High-Impact Recreational Runners: A Feasibility Study

This study investigated the feasibility of a field-based gait retraining program using real-time axial peak tibial acceleration (PTA) feedback in high-impact recreational runners and explored the effects on running biomechanics and economy. We recruited eight recreational runners with high landing impacts to undertake eight field-based sessions with real-time axial PTA feedback. Feasibility outcomes were assessed through program retention rates, retraining session adherence, and perceived difficulty of the gait retraining program. Adverse events and pain outcomes were also recorded. Running biomechanics were assessed during field and laboratory testing at baseline, following retraining, and one-month post-retraining. Running economy was evaluated during laboratory testing sessions. Seven participants completed the retraining program, with one participant withdrawing due to illness before commencing retraining. An additional participant withdrew due to a foot injury after retraining. Adherence to retraining sessions was 100%. The mean (SD) perceived difficulty of the program was 4.3/10 (2.2). Following retraining, the mean axial PTA decreased in field (-29%) and laboratory (-33%) testing. The mean instantaneous vertical loading rate (IVLR) reduced by 36% post-retraining. At one-month follow-up, the mean axial PTA remained lower for field (-24%) and laboratory (-34%) testing, and the IVLR remained 36% lower than baseline measures. Submaximal oxygen consumption increased following gait retraining (+5.6%) but reverted to baseline at one month. This feasibility study supports the use of field-based gait retraining to reduce axial PTA and vertical loading rates in recreational runners without adversely affecting the running economy.

Biomechanical differences and variability during sustained motorized treadmill running versus outdoor overground running using wearable sensors

This study aimed to compare running biomechanics and biomechanical variability across 3 run segments and between conditions for 5-km outdoor overground and indoor treadmill running. Seventy-one recreationally-active adults (31F, 40 M; age: 37 ± 11 years; body mass index: 22.9 ± 2.5 kg/m2) completed aerobic fitness assessments at baseline (VO2max), outdoor overground 5 km runs on a standardized route, and indoor treadmill 5 km runs on a motorized system (12.6 ± 4.9 days apart). Wearable sensors recorded step-by-step spatiotemporal, kinetic, and kinematic biomechanics. Repeated measures analyses of covariance were used to compare mean and coefficient of variation (CV) of sensor-derived metrics across run segments, conditions, and limbs (covariates: pace, VO2max). Tukey's post-hoc tests with mean differences and Cohen's d effect sizes were used to determine the difference magnitudes across comparisons. Most biomechanical measures significantly differed between running conditions (p < 0.001); contact time (mean difference and standard error: 8 ± 3 ms; d = 0.20), stride length (0.20 ± 0.12 m; d: 0.31), kinetics (shock, impact, braking; 0.17-1.30 g; d-range: 0.36-0.57), and pronation velocity (138 ± 16°/s; d: 0.61) were all higher during indoor treadmill running. Indoor treadmill running biomechanics CV were significantly higher for most measures compared to outdoor overground running (p < 0.001; d-range: 0.18-0.52). Only spatiotemporal measures and CV significantly differed across run segments (d-range: 0.16-0.68). Clinicians should expect that indoor treadmill biomechanics, particularly kinetic and pronation, will be significantly higher than patients' outdoor overground running biomechanics and tailor subsequent recommendations accordingly. Furthermore, clinicians should expect that indoor treadmill running analyses may result in more variable biomechanics, potentially attributed to consistent speed and surface, and tailor assessments to preferred run environments.

Digital manufacturing of personalised footwear with embedded sensors

The strong clinical demand for more accurate and personalized health monitoring technologies has called for the development of additively manufactured wearable devices. While the materials palette for additive manufacturing continues to expand, the integration of materials, designs and digital fabrication methods in a unified workflow remains challenging. In this work, a 3D printing platform is proposed for the integrated fabrication of silicone-based soft wearables with embedded piezoresistive sensors. Silicone-based inks containing cellulose nanocrystals and/or carbon black fillers were thoroughly designed and used for the direct ink writing of a shoe insole demonstrator with encapsulated sensors capable of measuring both normal and shear forces. By fine-tuning the material properties to the expected plantar pressures, the patient-customized shoe insole was fully 3D printed at room temperature to measure in-situ gait forces during physical activity. Moreover, the digitized approach allows for rapid adaptation of the sensor layout to meet specific user needs and thereby fabricate improved insoles in multiple quick iterations. The developed materials and workflow enable a new generation of fully 3D printed soft electronic devices for health monitoring.

Sensor-based gait training to reduce contact time for runners with exercise-related lower leg pain: a randomised controlled trial

Objectives

To assess the effects of a 4-week randomised controlled trial comparing an outdoor gait-training programme to reduce contact time in conjunction with home exercises (contact time gait-training feedback with home exercises (FBHE)) to home exercises (HEs) alone for runners with exercise-related lower leg pain on sensor-derived biomechanics and patient-reported outcomes.

Design

Randomised controlled trial.

Setting

Laboratory and field-based study.

Participants

20 runners with exercise-related lower leg pain were randomly allocated into FBHE (4 male (M), 6 female (F), 23±4 years, 22.0±4.3 kg/m²) or HE groups (3 M, 7 F, 25±5 years, 23.6±3.9 kg/m²).

Interventions

Both groups completed eight sessions of HEs over 4 weeks. The FBHE group received vibrotactile feedback through wearable sensors to reduce contact time during outdoor running.

Primary and secondary outcome measures

Patient-reported outcome measures (PROMs) and outdoor gait assessments were conducted for both groups at baseline and 4 weeks. PROMs were repeated at 6 weeks, and feedback retention was assessed at 6 weeks for the FBHE group. Repeated measures analyses of variance were used to assess the influence of group and timepoint on primary outcomes.

Results

The FBHE group reported increased function and recovery on PROMs beyond the HE group at 6 weeks (p<0.001). There was a significant group by time interaction for Global Rating of Change (p=0.004) and contact time (p=0.002); the FBHE group reported greater subjective improvement and reduced contact time at 4 and 6 weeks compared with the HE group and compared with baseline. The FBHE group had increased cadence (mean difference: 7 steps/min, p=0.01) at 4 weeks during outdoor running compared with baseline.

Conclusion

FBHE was more effective than HE alone for runners with exercise-related lower leg pain, manifested with improved PROMs, reduced contact time and increased cadence.

Trial registration number

NCT04270565.

Cadence in youth long-distance runners is predicted by leg length and running speed

BACKGROUND

Lower cadence has been previously associated with injury in long-distance runners. Variations in cadence may be related to experience, speed, and anthropometric variables. It is unknown what factors, if any, predict cadence in healthy youth long-distance runners.

RESEARCH QUESTION

Are demographic, anthropometric and/or biomechanical variables able to predict cadence in healthy youth long-distance runners.

METHODS

A cohort of 138 uninjured youth long-distance runners (M = 62, F = 76; Mean ± SD; age = 13.7 ± 2.7; mass = 47.9 ± 13.6 kg; height = 157.9 ± 14.5 cm; running volume = 19.2 ± 20.6 km/wk; running experience: males = 3.5 ± 2.1 yrs, females = 3.3 ± 2.0 yrs) were recruited for the study. Multiple linear regression (MLR) models were developed for total sample and for each sex independently that only included variables that were significantly correlated to self-selected cadence. A variance inflation factor (VIF) assessed multicollinearity of variables. If VIF≥ 5, variable(s) were removed and the MLR analysis was conducted again.

RESULTS

For all models, VIF was > 5 between speed and normalized stride length, therefore we removed normalized stride length from all models. Only leg length and speed were significantly correlated (p < .001) with cadence in the regression models for total sample (R² = 51.9 %) and females (R² = 48.2 %). The regression model for all participants was Cadence = -1.251 *Leg Length + 3.665 *Speed + 254.858. The regression model for females was Cadence = -1.190 *Leg Length + 3.705 *Speed + 249.688. For males, leg length, cadence, and running experience were significantly predictive (p < .001) of cadence in the model (R² = 54.7 %). The regression model for males was Cadence = -1.268 *Leg Length + 3.471 *Speed - 1.087 *Running Experience + 261.378.

SIGNIFICANCE

Approximately 50 % of the variance in cadence was explained by the individual's leg length and running speed. Shorter leg lengths and faster running speeds were associated with higher cadence. For males, fewer years of running experience was associated with a higher cadence.

Use of wearable sensors to identify biomechanical alterations in runners with Exercise-Related lower leg pain

Exercise-related lower leg pain (ERLLP) is one of the most prevalent running-related injuries, however little is known about injured runners' mechanics during outdoor running. Establishing biomechanical alterations among ERLLP runners would help guide clinical interventions. Therefore, we sought to a) identify defining biomechanical features among ERLLP runners compared to healthy runners during outdoor running, and b) identify biomechanical thresholds to generate objective gait-training recommendations. Thirty-two ERLLP (13 M, age: 21 ± 5 years, BMI: 22.69 ± 2.25 kg/m²) and 32 healthy runners (13 M, age: 23 ± 6 years, BMI: 22.33 ± 3.20 kg/m²) were assessed using wearable sensors during one week of typical outdoor training. Step-by-step data were extracted to assess kinetic, kinematic, and spatiotemporal measures. Preliminary feature extraction analyses were conducted to determine key biomechanical differences between healthy and ERLLP groups. Analyses of covariance (ANCOVA) and variability assessments were used compare groups on the identified features. Participants were split into 3 pace bands, and mean differences across groups were calculated to establish biomechanical thresholds. Contact time was the key differentiating feature for ERRLP runners. ANCOVA assessments reflected that the ERLLP group had increased contact time (Mean Difference [95% Confidence Interval] = 8 ms [6.9,9.1], p < .001), and approximate entropy analyses reflected greater contact time variability. Contact time differences were dependent upon running pace, with larger between-group differences being exhibited at faster paces. In all, ERLLP runners demonstrated longer contact time than healthy runners during outdoor training. Clinicians should consider contact time when assessing and treating these ERLLP runner patients.

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.

Effects of Wearable Devices with Biofeedback on Biomechanical Performance of Running-A Systematic Review

This present review includes a systematic search for peer-reviewed articles published between March 2009 and March 2020 that evaluated the effects of wearable devices with biofeedback on the biomechanics of running. The included articles did not focus on physiological and metabolic metrics. Articles with patients, animals, orthoses, exoskeletons and virtual reality were not included. Following the PRISMA guidelines, 417 articles were first identified, and nineteen were selected following the removal of duplicates and articles which did not meet the inclusion criteria. Most reviewed articles reported a significant reduction in positive peak acceleration, which was found to be related to tibial stress fractures in running. Some previous studies provided biofeedback aiming to increase stride frequencies. They produced some positive effects on running, as they reduced vertical load in knee and ankle joints and vertical displacement of the body and increased knee flexion. Some other parameters, including contact ground time and speed, were fed back by wearable devices for running. Such devices reduced running time and increased swing phase time. This article reviews challenges in this area and suggests future studies can evaluate the long-term effects in running biomechanics produced by wearable devices with biofeedback.